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2021 | Book

Advances in Industrial and Production Engineering

Select Proceedings of FLAME 2020

Editors: Dr. Rakesh Kumar Phanden, Dr. K. Mathiyazhagan, Dr. Ravinder Kumar, Prof. J. Paulo Davim

Publisher: Springer Singapore

Book Series : Lecture Notes in Mechanical Engineering

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About this book

This book comprises the select proceedings of the 2nd International Conference on Future Learning Aspects of Mechanical Engineering (FLAME) 2020. In particular, this volume discusses different topics of industrial and production engineering such as sustainable manufacturing processes, logistics, Industry 4.0 practices, circular economy, lean six sigma, agile manufacturing, additive manufacturing, IoT and Big Data in manufacturing, 3D printing, simulation, manufacturing management and automation, surface roughness, multi-objective optimization and modelling for production processes, developments in casting, welding, machining, and machine tools. The contents of this book will be useful for researchers as well as industry professionals.

Table of Contents

Frontmatter
An Explorative Analysis of IoT Applications in Cold Chain Logistics

This research aims to investigate the main operational challenges of sensitive products (e.g., food, drugs) and propose a framework for the enhancement of the quality and efficiency of the respective logistics process. Four semi-structured interviews were conducted with senior executives of a Cypriot company, which specializes in the provision of Warehousing and Distribution logistics services, in order to obtain insight regarding the company’s processes, monitoring systems and difficulties. Based on the interview findings and the literature’s suggestions, an IoT platform is introduced with the aim to achieve real-time monitoring of the products’ and vehicle’s temperature and humidity as well as other transportation parameters, including the vehicle’s position. The platform provides real-time, easily accessible information making use of appropriate technologies and applications, such as the Radio Frequency Identification (RFID) tags, Wireless Sensor Network (WSN) and cloud computing. The proposed platform is beneficial for companies involved in cold-chain logistics (CCL), and it leads to operations typified by much higher efficiency levels while increasing the satisfaction level of the end consumers.

Marina Marinelli, Mukund Janardhanan, Nicos Koumi
Improvements in Production Line Using ProModel© Simulation Software: A Case Study of Beer Beverage Company in India

In the present competitive market scenarios, the beverage industries are working hard to increase the production volume without compromising the quality of products. There are many ways to improve the effectiveness and performance of the production lines, such as minimizing the transportation time between the locations, utilizing the buffer storages, removing and replacing manually operated and semi-automatic machines, use of group technology and many more methods. In the present study, a beer production company located in Sonipat (Haryana) India is a Small-to-Medium Enterprise (SME) striving to improve its production line layout. Thus, the exiting layout of the production line has been simulated using ProModel© 7.5 simulation software and two alternative production line layouts have been suggested with improved work-in-progress, higher production volume and less transportation time. In one alternative layout, the buffer storage and rearrangement of machines for shortening the travel distance have been introduced and in another alternative layout, the automatic guided vehicle has been replaced with the conveyor as well as two machines namely filling machine and capping machine have been replaced by a machine called Filling and Capping machine in order to perform both operation at the same time. Various conclusions have been drawn and the cost analysis has been presented to justify the suggested changes.

Rakesh Kumar Phanden, Jatinder Chhabra, Tushar Chaudhary, Akash Kaliramna
Analyzing the Critical Success Factors for Industrial Symbiosis—A Chinese Perspective

Due to globalization and industrialization, several industrial developments have been evident, which increases the global revenue significantly in recent years. Meanwhile, such increasing industrial activities prints many negative impacts on the environment through resources scavenging, an increase in waste, pollution and so on. Several strategies have been introduced to reduce these negative characteristics of industrial operations without comprising in production quantities. Industrial symbiosis is one such strategy that assists the industries in the industrial parks to engage in eco-efficient operations. Despite its key advantages, very limited studies exist in the developing context, especially with China industries. Though there are several attempts made in industrial symbiosis for its effective implementation, but no previous study details the success factors of implementation of industrial symbiosis even with the Chinese context. Addressing this gap, this study identified the common success factors for industrial symbiosis and analyzed the effective factors within the Chinese industrial context. The analytical hierarchy process has been adapted for this analysis, in which the China industrial eco park design managers are considered as case decision-makers. The results revealed that among considered 12 factors, technological factors are the key success factor for the effective implementation of industrial symbiosis in the Chinese context. With the findings, this study is having both scientific and societal contributions toward the implementation of industrial symbiosis in the Chinese context. Further, the future scope for research in addition to limitations has been presented.

Yongbo Li, Mark Christhian Barrueta Pinto
Implementation of Industry 4.0 Practices in Indian Organization: A Case Study

Digitization of manufacturing processes is the need for hours for industries. Indian manufacturing industries are currently changing from mass to customized production. The rapid advancements in applications of technologies help in increasing the productivity of processes. The term Industry 4.0 stands for the fourth industrial revolution, which includes the blend of technologies such as big data analytics, simulation, augmented reality, cloud computing, internet of things, cyber-physical systems, system integration, autonomous robots, additive manufacturing. The objective of this paper is to discuss the implementation of Industry 4.0 practices in Indian organizations and their outcomes after successful implementation. The authors have used the situation actor process and learning action performance technique (SAP-LAP) for the case study.

Ravinder Kumar, Piyush Gupta, Sahil Singh, Dishank Jain
Analytical and Decision Modeling Approaches in Circular Economy: A Review

With the increasing concerns of the world towards environmental, social and economic factors, a multi-lateral attitude towards sustainable development and management policies is much needed now, hence a shift of the linear economy to the circular economy, famously known as closed-loop supply chain, is being exercised. The increase in exploration by academicians and industrialists to address various implementation issues and challenges is now vital and transition in many industries has been initiated. Numerous decision-making approaches are evaluated for the major domains of industry, namely, optimization of activity, processes, coordination, network design and marketing issues. With the categorization of the closed-loop supply chain as circular economy and emission reduction, the three factors (environmental, social and economic factors) are evaluated single-handedly. The present paper attempts to discuss various decision approaches and analytical models realized, evaluated and implemented by industries after careful assessment, based on the respective and customized network design models.

Priyanshu Sharma, Bhupendra Prakash Sharma, Umesh Kumar Vates, Sanjay Kumar Jha, Shyam Sunder Sharma
Analyzing the Production of the Plastic Manufacturing Through Fuzzy Analytic Hierarchy Process

This paper presents a successful implementation of six sigma methodology in manufacturing unit of small- and large-scale plastic industries by identifying the root causes and by improving the economic benefits of the firm through project selection. The present study aims to develop and improve the project selection by weight evaluation criteria and by ranking using fuzzy analytic hierarchy process (FAHP). This FAHP is based on triangular fuzzy numbers to increase the overall productivity, profitability, and quality of the organization. The study follows the application of the DMAIC technique for investigating the defects and provides a solution to reduce these defects by evaluating the best process environment which could simultaneously satisfy requirements of operational excellence. The optimum settings of the parameters during machining process for various plastic products were found using design of experiments. An empirical case study is carried out to show the effectiveness of the project. The results are checked by fuzzy linear regression control charts which would help the organization to create eco-friendly environment.

P. Abirami, O. S. Deepa
Probabilistic and Fuzzy Models for Risk Analysis of Processing and Manufacturing System

Risk is defined as the chance of failures or a state occurrence of the possible loss. The risk of one can be a benefit to others. To survive in today's competitive market situation, proper risk management is essential. In the present study, various models, that is, probabilistic and fuzzy models used for risk analysis in processing and manufacturing systems, have been discussed. This article critically reviews the use of probabilistic and fuzzy models in context with the type of publications, area of application, region-specific details, citations results to answer the research questions framed. This main contribution of this article is the examination of the current state of the art for risk analysis. The findings from this article will be helpful for risk managers and analysts, respectively, for proper understanding, identification, analysis, and management of risk.

Priyank Srivastava, Navnidh, Sarthak Bali, Rishabh Gupta, Rajendra Kumar Shukla, Ruchika Gupta, Dinesh Khanduja, Melfi Alrasheedi, Rakesh Kumar Phanden
Analyzing the Influence of Leagile Manufacturing Tools in Peru Context

Recent manufacturing sectors facing several challenges worldwide due to various disruptions and economic instabilities. Hence, it becomes necessary for the industries to think about new strategies that could sustain in these tough environments. Such a strategy has been discussed in this paper, Leagile manufacturing within Peru context. Despite having several benefits with the implementation of Leagile manufacturing system, since there are many tangible and intangible barriers hinders its effective implementation in Peru industries. These barriers mainly rise due to less clarity among the tools and lack of ease to implementation within the concern of an industrial perspective. This study considers addressing this gap by evaluating the most influential tools for the effective implementation of Leagile manufacturing. From the combined support of both primary and secondary data, this study considered 12 Leagile manufacturing tools, which further evaluated based on their influence in implementation on Peru context with Decision Making and Trial Evaluation Laboratory (DEMATEL).

Mark Christhian Barrueta Pinto, Yongbo Li
Analyzing the Cause-Effect Relationship Among Deming’s Quality Principles to Improve TQM Using DEMATEL

Total Quality Management (TQM) is a systematic approach to the management of an organization. TQM focuses on improving the quality of the products of a company, including goods and services, by continuously improving organizational processes. The purpose of this paper is to study the 14 Deming’s quality principles and analyze the cause-effect relationship among them to improve the TQM process. No research is reported on such a relationship in TQM. To fill this gap, DEMATEL technique is used to understand the cause-effect of the 14 Deming’s principles. DEMATEL is a semi-qualitative Multi-Criteria Decision Making (MCDM) technique. By this, it can be analyzed and understand what are the principles which need more control. By controlling this cause group principle, practitioners can control effectively to the effect group principles. In the implementation of TQM, this cause-effect analysis has been recommended to the manufacturing and service industry as a new focus area.

Sucheta Agarwal, Vivek Agrawal, Jitendra Kumar Dixit, A. M. Agrawal
Security in Manufacturing Systems in the Age of Industry 4.0: Pitfalls and Possibilities

The manufacturing industry is swiftly entering Industry 4.0, wherein the supply chains, operations, factories and customers are becoming digitally interconnected. This interconnection, coupled with advanced automation driven by technologies such as robotics, cloud computing, artificial intelligence and big data, makes the manufacturing systems increasingly vulnerable to cyber-attacks. The motive and impact of these attacks may vary, but all such attacks cost time and money to the manufacturers and their customers. If these challenges are not adequately addressed, Industry 4.0’s true potential may never be realized. It is, therefore, imperative for the manufacturers to have a well-designed mitigation plan in place to secure their systems from such attacks. Therefore, the purpose of this study is to explore the numerous possibilities offered by these advanced technologies and also to identify the pitfalls in the existing security measures of manufacturing systems. The study also focuses on evaluating the level of awareness and preparedness for potential future cyber-attacks. Based on the findings, the study suggests several strategies to mitigate these attacks, which would possibly serve as a valuable reference for practitioners and other researchers.

Ruchika Gupta, Rakesh Kumar Phanden, Shubham Sharma, Priyank Srivastava, Prateek Chaturvedi
Application of Structured Maintenance Reliability Programme in Oil and Gas Industry—A Case Study

This paper explores the maintenance of equipment to provide optimum capabilities at minimum/reasonable cost in giant Oil and Gas Industry. The maintenance of equipment is required to increase life cycle and mitigate operational risk. Maintenance activities focus on three prime factors of any equipment viz Reliability (of equipment 100%) availability (95–99%) and maintainability. In prevailing maintenance practices RCM (Reliability centered maintenance) is very common. Reliability and availability are crucial to the success of any project as they underlie the higher order, but less tangible, project requirements for operability and maintainability. Based on literature review and input from industrial experts, this paper discusses a structured MRP (Maintenance Reliability program) that may be established by doing proper planning, scheduling, execution and auditing and also outcome of this paper establish the relationship among reliability, availability and maintainability.

Kumar Ratendra, Narula Virender
Six Sigma with Optimization and Probability Models in Healthcare Management

A population of rapid growth, a place of the booming economy, whistle-stop urbanization along with disease escalation requires persistent improvement in healthcare services. However, delays, medical errors, measurement errors and variability weaken the coherence of healthcare, which increases the pressure in redesigning the process for quality improvement. In this paper, Six sigma is implemented for selecting the parameters in health care management. Then optimization based on nonlinear programming is performed for minimizing the total cost in bed scheduling, where the constraints depend on the budget spent, types of doctors, the technicians, the medical equipment, etc. It also aims to minimize the total cost associated with packaging medications and emergency department allocation. Optimized results showed that the emergency department has to be taken care in order to gain a superlative performance of healthcare maintenance. Hence the usage of probability models based on Poisson regression has been imposed on bed occupancy of the emergency department by considering the number of arrivals and the number of departures of patients on specific days. The results are then examined using DMAIC techniques and are found to be under control using an exponentially weighted moving average chart. The computational behavior, the efficiency of the proposed model and the practical applicability is exemplified by a case study. This novel methodology of integrating six sigma with optimization techniques and probability models has gained a strong potential success related to cost reduction, increase in patient satisfaction and enables continuous monitoring of health care service, thereby promoting economic sustainability.

S. Madhura Mokana, O. S. Deepa
Study on Important Techniques and Processes for the Management of Waste Electrical Wires

With the expansion of modern and communication industries, a diversity of metal wires and cables are used in a variety of applications, simultaneously wastes in the form of wire are also increasing which is also responsible for environmental pollution. The disposal of this type of waste is a worldwide problem. Therefore, recycling is very important for economic savings and a positive effect on the environment. Earlier, recycling techniques involved burning of the plastic layer of wire and then recovery is done for copper, aluminium and steel but this process is highly harmful to the environment because it releases toxic gases. In this study, various types of important techniques and processes for recycling of waste electrical wires are discussed which are less harmful to the environment.

Abhishek Kumar Gupta, Anand Kumar, Vinay Pratap Singh
A Case Study of Manpower Productivity Improvement in Moulding Section of Automotive Industry by Using Man Machine Chart

Nowadays all companies want to increase their output without increasing the input so that their productivity will improve and profit will increase. This paper discusses time study methodology using Man Machine Chart through which the work study has been successfully implemented. It provides the case study of manpower productivity improvement in moulding section of automotive industry. From our study in moulding section shots/hour increased and there is reduction in manpower in terms of saving/month.

Tarun Kumar Verma, Niraj Gupta
Lean Tool Selection in a Die Casting Industry: A Fuzzy AHP-Based Decision Support Heuristic

As the government of India has recently put a lot of focus on its new policy, i.e., “Make in India,” the Indian manufacturing sector has been looking forward to be on the cusps of being the manufacturing hub on the globe. And hence, a large number of manufacturing organizations are looking forward to implementing lean philosophy in their units in order to cut down the various wastes and gain sustainable advantages over the competitors in the global market. The problem arises when the tools which are to be implemented are vast in number and the need to select the tools when lean philosophy implementation arises. The lean tools need to be ranked as per their efficiency based on a number of criteria and then implemented in the manufacturing organizations. The current research work deals with the selection of lean tool for a die casting industry using Fuzzy AHP. FAHP makes use of a triplet of triangular fuzzy numbers (TFN) to include the ambiguity in the priorities during pairwise comparisons. The lean tools under consideration are Poka Yoke, value stream mapping (VSM), Heijunka (Level Scheduling), SMED (Single minute exchange of dies), and Kaizen. These lean tools are to be evaluated on the basis of three criteria, i.e., material, time, and energy. The tools are evaluated using Fuzzy AHP and ranked accordingly. The lean tool with the best rank is chosen for implementation in the die casting industry.

Sanatan Ratna, B. Kumar
Comprehensive Study of Artificial Intelligence Tools in Supply Chain

The global supply chain has become more complex in recent years, and the advent of artificial intelligence tools is set to improve the functioning of supply chain. This paper examines the effect of artificial intelligence tools on key parameters of supply chain such as cost, quality, pace, reliability, and sustainability. The Blockchain, the internet of things, the big data technologies, and the machine learning are the new potential enablers of sustainable manufacturing supply chain. This study reviews the current state-of-art research efforts and provides a systematic overview of the current and potential research directions to recognize the market trend in the adoption of these new technologies and some of the challenges as well.

Manish Kumar Ojha, Bal Krishna Sharma, Rajat Rana, Sumit Kumar, Sumit Gupta, Poonam Ojha
Industry 4.0 Technologies and Ethical Sustainability

Industry 4.0 technologies are finding applications in many industrial sectors. But industrial development is societal, ethically sustainable only when the technologies used are cleaner and ethical sustainable. In this research paper, authors have shortlisted eight technologies that act as major pillars of Industry 4.0 (I4.0). These technologies have been critically examined on aspects of ethical sustainability considering Indian micro and small enterprises. For this study, authors have reviewed 55 research papers from different sources such as science direct, emerald insight, Taylor and Frances. The authors have also developed a framework, which reveals the ten major contributors toward ethical sustainable manufacturing in the digital era. Contributors or enablers such as availability of better software /hardware, reduction in e-wastage and manufacturing cost, and awareness on government policies and supports help to enable ethical sustainable manufacturing in the modern digital era.

Dhairya Garg, Omar A. Mustaqueem, Ravinder Kumar
Computer-Aided Diagnostic System for Classification and Segmentation of Brain Tumors Using Image Feature Processing, Deep Learning, and Convolutional Neural Network

This research aims at the detection of the tumor clusters, found in the brain and classifying the type of tumor using Convolutional Neural Network (CNN) using MR Images of the patient. The proposed technique/mechanism consists of several phases, namely, Acquisition, Refining, Segmentation, and finally the Classification. The image refining process includes several sub-processes such as Noise Removal and Edge Detection. Further, based upon the input of the end-user, the class variance value gets calculated from the extracted features for segmentation and gets stored in a matrix called the convolutional pattern. The developed system classifies the type of tumor that either it is malignant or benign using Neural Network and Deep Learning Algorithms. The Idea of this project is to understand how we can develop industry grade, doctor acceptable, and diagnosable correct; an engineered mechanism for evaluating tumor presence in the subject so that faster and better measures can be taken to provide a good cure to the patient at the early stage.

Shivanshu Rastogi, Mohammad Akbar, Dhruv Mittal
Modeling Interrelationships of Sustainable Manufacturing Barriers by Using Interpretive Structural Modeling

The growing demand in the manufacturing sector has yielded serious negative impact on 3Ps (people, planet, and profit), and it requires the most change among the businesses with sustainability goals. Therefore, it becomes very crucial to identify and diminish the outcomes of critical barriers of sustainable manufacturing (SM). This paper analyzes eight vital barriers selected with the opinion of various researchers and industry experts on the basis of their importance; they are then analyzed and prioritize by using interpretive structural modeling (ISM). This technique is used to develop an anatomy model and its findings give a vital insight to managers regarding factors pushing them back for not incorporating SM practices.

Deepak Sharma, Pravin Kumar, Rajesh Kumar Singh
Energy-Economic Study of Smart Lighting Infrastructure for Low-Carbon Economy

Fossil fuel-based energy generation and day-by-day increasing load on power are prominent issues which are globally discussed. Electricity is an essential need for any nation’s development. 67% of electricity production is generated from the thermal power sector in India at present and 30% of carbon emission globally accounted from coal-fired thermal power plant. This paper is focused on the energy-economic analysis of all categories of lighting systems for the implementation of energy-efficient infrastructure in urban and rural areas of Indian states to achieve economic and environmental goals while reducing greenhouse gas emissions and escalating resilience to climate change impacts. The employment of solar photovoltaic (SPV)-based lighting system is anappropriate solution for eminence light for households with least consumption of energy and able to map the decarbonized economy. The major comparative study of all the mentioned lighting system has been investigated. The single unit of 11 W (equivalent to 60 W, 13 W of conventional bulb and CFL respectively) LED-based lighting system is able to save yearly 40–41 unit of energy consumption, and it can reduce 82% of carbon emission also as compared to equivalent lighting systems.

Shivendra Nandan, Rishikesh Trivedi, Gunjan Aggarwal, Kaushalendra Kumar Dubey
Analysis of Lean Six Sigma Implementation Indicators in Health Care sector—A Customer Perspective

This paper presents a combinatorial approach which helps the customer / patient choose from the multiple alternatives of hospitals which have implemented Lean Six Sigma (LSS) in their business. The methodology adopted was to recognize the key indicators or attributes of LSS implementation in five hospitals at Bangalore city, which relate to the benefits a customer can gain. A technique for Order Preference by Similarity to Ideal Solution (TOPSIS) along with Analytical Hierarchical Process (AHP) has been applied to analyze the survey responses that are collected from the customers visiting these hospitals for varied reasons and arrive at ranks for these hospitals. This work presents in-sights into the LSS implementation benefits to customers and helps to choose the hospital depending upon the customer preference. In the current work, five hospitals and eight LSS implementation indicators are analyzed; this can be extended to other hospitals and a greater number of indicators from different processes can be studied.

M. Shilpa, M. R. Shivakumar, S. Hamritha, V. G. Ajay Kumar, S. Shreyansh
Supplier Selection for Sustainable Supply Chain Using an Integrated GRA-VIKOR Approach in an SME

The traditional supply chain management has evolved over the years due to the changing government regulations which intend to save the environment. The focus has shifted on sustainability which means that the needs of the present generation are fulfilled without making any significant impact on the resources which would be required by the future generations. As a result, it has become quite obvious that supplier selection in any sector needs to consider factors which affect the environment. In the current research work, six criteria for supplier selection in GSCM (green supply chain management) are considered initially, out of which the four major ones are shortlisted using GRA (grey relation analysis). The shortlisted criteria are used for supplier selection in the bicycle parts manufacturing industry. This selection of supplier using the shortlisted GSCM criteria is done using VIKOR which is based on finding the utility measure as well as regret measure of each alternative.

Sanatan Ratna, B. Kumar
Assessment of Key Barriers of Sustainable Additive Manufacturing in Indian Automotive Company

Sustainability is an emerging issue that product development engineers must engage with to remain relevant, competitive and most importantly, responsible. The advent of additive manufacturing technologies presents several opportunities that have the potential to benefit designers greatly and contribute to the sustainability of products. Products can be extensively customized for the user, thus potentially increasing their desirability, pleasure and attachment and therefore longevity. This paper presents the key barriers of sustainable additive manufacturing in Indian automotive companies.

Hema Sudarsan Rao, Devarapalli Sai Kishor Reddy, Chandrakant Sharma, Sumit Gupta, Anbesh Jamwal, Rajeev Agrawal
Rejection Minimization Through Lean Tools in Assembly Line of an Automotive Industry

In order to compete in the ‘Automotive Industry’ which is the world’s largest manufacturing industry, manufacturing managers have to put their efforts in motivating their personnel to increase their efficiency and improve the processes to achieve a common successful goal of improved productivity and quality. In this research, focus has been made to reduce the MUDA work elements associated with the activities in manufacturing cycle at different workstations on the line by using some advanced methods and tools, which have characteristics to prevent or trace the fault in the very beginning of its occurrence. In context of the above, focus has been made to implement the Lean Concepts (Kaizen, 5S and Poka-yoke) to improve the productivity and quality of its product by reducing cycle time, lead time and rejection. In this research, the five steps of DMAIC cycle has been used to synchronize the findings and their effects throughout the manufacturing cycle. The results indicate that after implementing the lean components integrated with DMAIC cycle, productivity has improved, and rejection reduces to Zero from 0.8% at illumination testing station in assembly line of HVAC Switch.

Rakesh Giri, Ashok Kumar Mishra
Implementation of Six Sigma in CNC Turning Machine—A Case Study

This study focuses on implementing the DMAIC methodology of Six Sigma to reduce the quality defects of the products occurring in the manufacturing process within a CNC (Computer Numeric Control) turning component machining company. The study follows the application of the DMAIC technique to investigate the defects, root causes and provide a solution to reduce these defects by evaluating the best process environment which could simultaneously satisfy requirements of both quality and as well as productivity. In this paper, six sigma with fuzzy analytic hierarchy process, for the manufacturing of a CNC turning component called front end cover is selected out of three projects and DMAIC model is adopted to investigate the defects obtained in the manufacturing process and also provides a solution to reduce these defects by improving the performance of the process. Normality test followed by process capability index and control chart has been computed for each major component of the process. Factorial experiments are also carried out to show the efficiency of the machine.

G. Shruthi, O. S. Deepa
“5 s Housekeeping”-A Lean Tool: A Case Study

The research paper pertains to the implementation of “5S Housekeeping” in the Sheet Metal Workshop of a manufacturer/supplier of Hero MotoCorp Ltd. The objective for the implementation of 5S arises due to reasons like uneasy work environment, excessive wastage, and inefficient workstations in the company. Therefore, in order to efficiently work on the above-mentioned factors arises the need to implement 5S in the organization. The reduction of 7 wastes defined by Toyota is a major part of the process. The effective implementation and follow-through for 5S in the workshop by all staff members work as a catalyst for improving work ethics, fundamental practices, manufacturing performance and in-house capability. After the implementation of this technique, a visible improvement in the working conditions and employee satisfaction is achieved.

Sarthak Jain, Gaurav Chaudhry, Mohd Talha, Richa Sharma
Role of Industry 4.0 Technologies in Sustainability Accounting and Reporting-Research Opportunities in India and Other Emerging Economies

The GRI standard is a global reporting framework for sustainability accounting and reporting (SAR). In India, SEBI has mandated SAR for listed companies to be integrated with the annual reporting. GRI has developed custom standards for regulatory compliance of multiple countries. The global unlisted small and medium scale manufacturers can also benefit from it. Regulatory, Stock Exchange and Investor pressures are common denominators for SAR in multiple emerging economies. This paper proposes the path of Industry 4.0 adoption. Based on study of the GRI standards and the capabilities of Industry 4.0 technologies, this paper presents the recommended material topics under the triple bottom line objectives that can be targeted through strategic attachments of Industrial Internet-of-Things (IIoTs) with equipment, systems, machinery, and robots using the piping and instrumentation (PI) diagram, real-time data collection and analysis using IIoTs attached to cyber-physical sensors, big data, and artificial intelligence. The recommendations also include a few use case examples and the methods of targeting the material topics in them.

Kamlesh Tiwari, Mohammad Shadab Khan
Theoretical Analysis of Isentropic and Alternative Refrigerant Based Cooling System and Low Carbon Economy

The current trend of energy supply and its uses are very unstable economically, socially and environmentally. Greenhouse gas emissions are continuing to increase, and it will affect the environment globally. The scope of alternative refrigeration system like vapour absorption (VARS), vapour adsorption and ejector cooling can play significant role in the modern industry with low carbon emission. The experimental setup of 03 Ton of cooling (TR) of dry compression vapour compression refrigeration (VCRS) has been evaluated and compared with single-stage of LiBr-H2O-based VARS cooling system. The operating condition of condenser, evaporator temperature and pressure have been considered for performance analysis of both systems. The higher value of condenser temperature not suitable for efficient cooling and also decreases the energy performance ratio (EPR or COP) of system. The R134a is commercially useful eco-friendly refrigerant but applicable in VCRS (Energy consumption by VCRS is much more than VARS). The employment of VARS have tremendous potential for space cooling and water chilling application at same range of VCRS operating temperature of condenser with low-grade energy source or solar energy utilization. VARS is low carbon emission and non-toxic technology and able to map decarbonize economy for industrial sector.

Kaushalendra Kumar Dubey, Karan Sharma, RS Mishra, Sudhir Kumar Singh, Brahma Nand Agarwal
Role of Artificial Intelligence in Railways: An Overview

The worldwide increase in population joined with urbanization and a more appeal for versatility has pressurized the railroad systems of the world. The solution to this problem is to develop the infrastructure or enhancing the software with the integration of the internet for providing better services to the passengers. The combination of these three aspects of a railway system formed the Artificial Intelligence (AI). The objective of this work is to explore the role of AI in railway Transportation. The overview concludes by addressing the challenges and limitations of AI applications in railway transportation.

Neeraj Kumar, Abhishek Mishra
Selection of Turbine Seal Strip Material by MCDM Approach

The process of selecting a material among various available materials is a tedious process. Depending upon the applications and the need of the product, the most suitable materials are to be analysed on various parameters before making a decision for the selection of best material. Multiple-Criteria Decision-Making (MCDM) approaches have been used widely to solve similar types of decision-making problems. This paper focuses on the use of Analytical Hierarchy Process (AHP) and Modified-TOPSIS for selecting suitable stainless steel (SS) material for turbine seal strips. In the current work, five materials have been considered and compared for different material properties such as: toughness, yield strength, coefficient of thermal expansion, limit strain, creep strength and resistance to oxidation. Material AISI 316 SS is found to be the most feasible material for the seal strip of turbines.

Shwetank Avikal, Akhilesh Sharma, Anup Kumar Mishra, Rohit Singh, Amit Kumar Singh, K. C. Nithin Kumar
Impact of Six Sigma in Dairy Production for Enhancing the Quality

This paper proposes the implementation of six sigma for improving the quality of milk production process. Six sigma focuses on establishing world class business performance by means of statistical and systematic approach. It is a business strategy that emphasises on customer necessities, financial enhancements and overall productivity. The growing demand for milk and milk products had made the producers to enhance their livelihood by increased production. This paper illustrates the application of six sigma in diary products by systematic role of DMAIC by using gauge R&R and quality function deployment. Various six sigma tools were also used to show the efficiency of the work. In this study, the use of six sigma creates a competitive spirit among producers, which will boost them to manufacture milk at low cost.

O. S. Deepa, Sreeja M. Krishnan
Kaizen Implementation in Rolling Mill: A Case Study

The operational issues in the Rolling Mills industries such as productivity; resource consumptions; wastes creation and breakdown etc., bound the researchers to do research in rolling industries. That is why, it has never been taken in the mainstream for the research work. The present paper aims to enhance the operational efficiency and efficacy of rolling mill industry with Kaizen implementation. The existing data such as miss roll production, spare part consumption, productivity and breakdowns were collected for the study. These data further used for finding the operational efficiency of rolling mill and while analyzing it were observed that the rolling mill is performing lesser than its original working capacity. Thus, Kaizen approach was suggested for the implementation in rolling mill industry and on analyzing the data after the Kaizen implementation, it is observed that the productivity of rolling mill goes by 30% increment whereas the 70% decrease reported in miss roll. In addition, the spare part consumptions are also reduced because of lesser number of breakdowns.

Rahul Sharma, Abhishek Kumar, Rajender Kumar, Tarsem Singh
Identification of Factors for Lean and Agile Manufacturing Systems in Rolling Industry

The rolling industries have significant contribution to produce the sheet metal-based components. To obtain better outcome and enhanced performance, the implementation of integrated lean and agile manufacturing concept is highly important for such industries. In the present paper, the issues related to the influence of applying of lean and agile system have been recognized at the initial stage. In addition, ordinary issues (factors) were also explored at the later stage. The paper will be helpful for the authors and managers in identifying as well as developing the basis of LM and AM simultaneously and their impact on rolling industries.

Rahul Sindhwani, Rahul Dev Gupta, Punj Lata Singh, Vipin Kaushik, Sumit Sharma, Rakesh Kumar Phanden, Rajender Kumar
Development of an Industry 4.0-Enabled Biogas Plant for Sustainable Development

In India, apart from having huge population, it has limited skilled workers. The handling of organic waste requires a lot of care since it may lead to unwanted diseases if not properly handled. This research study employs a modern approach of Industry 4.0 in order to eliminate human intervention in the process of production using advanced concepts and IoT devices. It is proposed to use the old technique of producing biogas from organic waste and combines it with modern techniques to make an efficient and reliable process and supporting the nation’s most crucial requirement of energy. It can be concluded that the proposed work may help the nation’s sanitation and sustainable development initiative.

B. Rajesh Reddy, Sumit Gupta, Rakesh Kumar Phanden
Sustainable Supplier Selection in Automobile Sector Using GRA–TOP Model

In automobile sector, supply chain management plays a very important role we can consider it as a spinal code of manufacturing system. Major part of automobile sector is transportation, storage facility, retailers and even the customers who are going to be benefitted the most that are the user. Supply chain can be distributed into two parts or we can say factors physical distribution and supply chain management system. The issues faced by the supply chains in the current scenario are environment based. There is an immediate need to select the suppliers based on factors, which are important for sustainability. The criteria for supplier selection are shortlisted using Grey Relational Analysis (GRA). Finally, the best supplier is selected using TOPSIS that is based on calculating the Euclidean distances from the ideal best and the ideal worst. We can learn deeply and vastly about this concept to make our process more efficient, that is, by using green supply chain management. Selecting best supplier is very important in this competitive world that can be done using supply chain management.

Sanatan Ratna, Mohit Bhat, Nirbhay Pratap Singh, Mitansh Saxena, Sheelam Misra, Prem Narayan Vishwakarma, B. Kumar
Human Empowerment by Industry 5.0 in Digital Era: Analysis of Enablers

In modern digital era, technology has dominated in all sectors of society. In manufacturing sectors, technology development has been divided into different time zones (Industry 1.0–4.0). These industrial upheavals have highly focused on technology applications. But modern challenges of customization, personalization and technology upgrading can only be done by human involvement. These modern challenges have led to new industrial revolution called “Industry 5.0,” which emphasizes on technology advancement with human empowerment. In this research paper, authors have studied the enablers, which help in execution of Industry 5.0 in Indian manufacturing sector. Eight enablers have been distinguished by literature review and specialist’s supposition. By using total interpretative structural modeling (TISM) technique, authors have studied the relationship between these enablers. Authors have developed a diagraph to show structural relationship between different enablers influencing implementation of Industry 5.0 in Indian manufacturing sector.

Ravinder Kumar, Piyush Gupta, Sahil Singh, Dishank Jain
Analyzing the Role of Six Big Losses in OEE to Enhance the Performance: Literature Review and Directions

The engineering sectors have a considerable contribution toward a nation’s economy. These industries are amid the principle-focused industries around the globe. Hence, appropriate utilization of available resources as well as equipment is a high priority in task list of every industry. Since many of these industries are dealing with hurdles to keep all the activities, operations, and synchronized use of equipment with a considerable reduction of time losses. These time losses (so called Six Big Losses) have a set of analyzing factors, which affect the overall performance. Six Big Losses (SBL) are now becoming the real cause of focus to attain world class manufacturing standards in association with strategic tool such as OEE (Overall Equipment Effectiveness). To cover the wide-ranging and dynamic time loss analysis, the corrective measure is OEE. The aim of implementation of OEE is to enhance and acquire the equipment’s effectiveness by removing all the potential losses of the industry. This paper discloses the importance of the extensive literature for analysis of these losses systematically. This study also covers a powerful organized strategy, i.e., OEE and the actual time losses in the industries to bring transformation in the attitude of management, managers and workers. This paper tunes up the literature related to SBL to find the potential errors through optimized approach to improve decision-making.

Sandeep Singh, Jaimal Singh Khamba, Davinder Singh
Optimization of Inventory Decisions Using Fuzzy Cognitive Mapping in an Automobile Component Manufacturing SME

Inventory optimization is a serious challenge to industries around the globe. It poses a challenge to the decision-makers as poor judgment or decision can be catastrophic to any enterprise’s fortunes regardless of its size and sector. The complexity arises due to the dynamic movement behavior of various inventories in the supply chain. The main aim of the current research work is to identify the most central and important concepts affecting inventory optimization in an automobile component manufacturing SME located in Delhi-NCR. The variables considered for inventory optimization are identified through a thorough literature review. The variables affecting inventory optimization are capital available, usage level, cost of procurement, credit time and material availability. The current research work makes use of Fuzzy cognitive mapping (FCM) for inventory optimization by identifying the interrelations between the various factors and the most central concept. Also, the paper aims at identifying the positive and negative associations among the various variables under study, which affect the inventory optimization decisions. The importance of the various variables is measured by making a note of the incoming and outgoing arcs for each variable in the directed graph. It is found that the most central concept is the cost of procurement.

Sanatan Ratna, Absar Ahmad, Deepak Kumar Sonu, Kushank Gupta, B. Kumar
A Preliminary Study on Six Sigma to Reduce the Waiting Time of the Patients in Hospitals

This paper is based on a preliminary study of six sigma methodology for reducing the waiting time thereby increasing the patient satisfaction and to minimize the cost in a hospital. An optimization model is developed with regard to minimize waiting time and minimize cost. Various factors like time taken by the doctors to examine the patient, time taken to administer the medicines, number of skilled persons, total time taken to shift to the ward or to the scanning center were considered for testing the hypothesis. A nonparametric approach is used to test the significant difference between certain factors also collected data were tested to determine the need for the waiting time in the anesthetic lab. DMAIC technique is used for continuous improvement on quality and for achieving operational superiority. By identifying the key factors as the root cause and thereby deriving solutions is the main aim of this paper, which ultimately leads to success of the hospitals and hence offers the potentiality to implement the suggestions on every small and medium hospitals for gaining patient satisfaction.

S. Anjana, O. S. Deepa
Prioritization of Sustainable Development Methods in the Manufacturing Sector: An Entropy TOPSIS Approach

The intergovernmental policies on climate change and the shorter product lifecycle of the product have forced the organization to adopt sustainable methods. The industrial organizations are in the constant run to search for sustainable technologies that meet the modern demand of the industry. The main concern for the manufacturing organizations is the selection of the approaches that are best suitable for the modern demand of the industry. The present study deals with the selection of a sustainable development approach based on the criterion. The selection of the sustainable methods has been done through the TOPSIS and the weights of the criterion were found through the entropy method. It has been found the Green Lean Six Sigma and Six Sigma methodology has found the prominent sustainable development methods with the closeness coefficients 0.938 and 0.322, respectively. The present will facilitate the practitioners and managers to select a sustainable approach that will make the holistic development of the organization.

Mahender Singh Kaswan, Rajeev Rathi
Green Supplier Selection for Nickel Coating Industries Using a Hybrid GRAF-VIK Model

The traditional supply chain needs to be upgraded in order to address the concerns for environment. The scientists and researchers have stressed that the industrial growth needs to address the sustainability issue in supply chain and the suppliers must be evaluated in order to measure their performance on ‘Green’ front. The current research work addresses this issue of selecting a Green supplier in the Nickel Coating industry using a hybrid MCDM model. The hybrid MCDM model used is GRAF-VIK model, which consists of Grey Relational Analysis (GRA), Fuzzy analytical hierarchy process (FAHP) and VIKOR. The GRA tool is used for selecting important green supplier selection criteria among a number of criteria. The Fuzzy AHP tool is used for giving weightage to the selected criteria and finally VIKOR is used for selecting the best supplier in Nickel coating industry based on the chosen weighted criteria. Improving solid waste disposal, recycling and complying with the government regulations will definitely lead to a sustainable growth.

Sanatan Ratna, B. Kumar
Reducing the Time Delay in Curing Process by the Implementation of DMAIC in Tyre Production

Evidence shows that six sigma and its tools have helped in the manufacturing process in a medium and small-scale organization. However, there are still many industries where six sigma implementations are not been so predominant. Hence this paper deals with the application of DMAIC methodology in the tyre production process to reduce the cycle time in the curing process. Steam that is needed to generate heat and pressure has many disadvantages like the price of steam energy, difficulties during handling, the nonexistence of tractability in fixing parameters, risk in quality due to overheating and many other factors. Hence to enrich the quality of tyre and to maintain sustainability, it is necessary to implement optimization techniques. In this paper, integration of DMAIC and multi-objective optimization is carried out, which offers companies and managers a better understanding of the strategies and their operational measures. Balancing six sigma and multi-objective optimization is a complicated and challenging task to reduce variability. DPU and DPMO are carried out for each sub-process in the curing process to find the root cause of the problem. Also, studies on multiple linear regression and signal to noise ratio have been implemented to strengthen the work. The objective of this paper is to reduce the cycle time in the curing process so that defects are reduced, which leads to good quality by the implementation of planning strategies thereby stabilizing the process by continuous improvement.

M. Sreelakshmi, J. Devika, Ananya Theres John, O. S. Deepa
Digitization of Biogas Plant for Improving Production Efficiency

In the current competitive world, the digitization of biogas plants is much needed. This can be achieved by employing the most modern technologies in the biogas plant. In the traditional biogas plant, the process is uncontrolled, and the efficiency of the model is low as it requires high inputs and the chances of leakage of gas are high. To overcome these issues, Industry 4.0 practices are implemented to improve the efficiency of the system. This paper is focused on the modification of the existing biogas plant. In the modified biogas plant, a closed chamber with the help of a gate valve is developed that closed the digester with no leakage of gas and add safety features to the process. In the proposed design, heat efficiency has been significantly improved and produced optimum methane gas during the winter session. In the proposed automated plant, human work has been optimized.

Kural Azhagan, Sumit Gupta, Rakesh Kumar Phanden
Identification of Drivers in Implementing Green Supply Chain in Indian Perspective

It’s a well-known fact that the Japanese Automobile Sector identified the various approaches for improvement in the business performance which caused the transition of manufacturing sector from push to pull production. Eventually, the major role in this transition phase was played by Supply Chain Management approach with which the industries integrate the whole industrial setups in a network to balance the supply and demand gap. In the early stage, Supply Chain was having the major concern to fill/eliminate the gap between supply and demand through efficient information processing systems. Later the earlier concern of SCM includes the environmental aspect because of eco-friendly products/services demand. Such kind of concerns in manufacturing sector solicits the deeper intervention from all the allied network partners. The present paper discusses the role played by GSCM in the industries to produce the eco-friendly product and in addition, utilizing the environment-friendly processes. In addition, the paper reveals the drivers responsible for driving the GSCM implementation smoothly in Indian Context and helping in achieving the excellence in terms of tangible and intangible outcomes both.

Neeraj Lamba, Priyavrat Thareja
Understanding the Blockchain Technology Beyond Bitcoin

A blockchain is a decentralized distributed public and digital ledger consisting of blocks that record transactions across many systems, ensuring security as these blocks cannot be altered retroactively. This technology enables individuals and companies to participate with trust and transparency. A well-known application of blockchain is the cryptographic currencies Bitcoin, an emerging technology like Ethereum and many more applications are possible. Blockchain, with great potential, allows us to create, value, trust, truthfully by clever use of distributed ledger, cryptography, and computation. It emphasizes the potential of a decentralized world, where users of technology can be empowered without being bound by a third-party power broker and many other benefits this technology presents to us. Blockchain technology is the driving force behind the next basic change in information technology. Many uses of blockchain technology are widely available today, each with the potential of a specific application domain. A blockchain is a diary that is almost impossible to forge. Blockchain technology is an interesting and a safe alternative for people, using this does not demand you to have a technical background, it will somehow have a positive effect on citizens. It will prove to be a better financial system and excites us to make blockchain more mainstream. Here, we have provided a brief survey on blockchain technology and how it is establishing itself to make an impact on the future of technology.

Javeriya Shah, Suraiya Parveen
The Impact of Internet of Things in Manufacturing Industry

The study was done to understand the impact of internet of things on manufacturing industry. It was a 2-part research in which first the previous research and findings were studied to understand the IoT technologies and the overall impact these technologies were having on various industries, and in the second part, a survey was conducted to find out how application of internet of things technology can affect the manufacturing industry. Literature study was done to understand the parameters and the factors that affect manufacturing industries. On the basis of the study, five crucial parameters that were having the maximum impact on manufacturing were found, namely Quality, Reduction of Errors, Employee Satisfaction, Productivity, and Cost Reduction, and a linear grading was done to see if there was a positive or negative impact of IoT technologies on these parameters. Through survey and single-tailed t-Test, it was found that IoT was having positive impact on all the parameters, and it was interpreted that with time IoT technologies could be integrated into manufacturing industries for sustainable growth and increased overall profitability.

Vishal Jain, Anand Kumar Mishra, Manish Kumar Ojha
Big Data-Based Structural Health Monitoring of Concrete structures—A Perspective Review

Structural health monitoring (SHM) comes with the real data that is collected and calculated from the structures, which is not possible by mere visual inspection. The working principle of SHM is basically collecting essential data, including strain, temperature conditions, moisture content, etc., which are further transformed into digital data for the interpretation. It serves a tool in the synchronizing of the collected data, also with the responsibility of making it available at all times. It stores the data for the meticulous research and analysis. SHM is enabled with the leading-edge technology of big data, which has an added advantage of collecting and storing extensive data related to the structures. Different types of sensors are used for collecting the data; hence, with these data, real-time information about the structures is extracted. The elaborate process involves the big data, for exploring and analyzing a variety of datasets with different patterns to determine damages, and defects lying under the structures. Hence, health monitoring of the existing structures is possible and with high precision and information. SHM is a continuous process of measurement, collection, processing, and storage of massive amounts of data of the existing structures for diagnosing structural health. Hence, in this paper, various examples of the contemporary structural monitoring system and the ongoing efforts being made in the big data-based structural health monitoring of concrete structures has been presented. The work is dedicated to present the different monitoring sensors of structures to evaluate damage, defects, and serviceability by taking account of available literature.

Priyanka Singh
Sustainable Circular Manufacturing in the Digital Era: Analysis of Enablers

In the digital era, advanced technologies and strategies are required to cope with the changing demands of consumers. “Sustainable circular manufacturing” is the new ray of hope meeting all standards of sustainable manufacturing and circular economy. It focuses on environment friendly production with the philosophy of reuse, remanufacture, and recycle and also endorses a close loop manufacturing pattern. This pattern not only aims to improve the product life cycle but also decrease resource consumption. Authors in this research paper authors identified nine key factors which enable the sustainable circular manufacturing by literature review and expert opinion. To determine a structural link amongst these enablers “Total Interpretive Structural Modelling (TISM)” methodology is used. Authors also derive the most dependent and independent enablers with the help of MICMAC analysis chart.

Dhairya Garg, Omar A. Mustaqueem, Ravinder Kumar
A Business Process Modeling Approach in Human Resource Management for Small and Medium-Sized Enterprises

The primary objective of this research paper to highlight the research work carried out in the area of human resource management for SMEs using a business process modeling approach. This paper provides a method of developing a human resource management model from the perspective of business process modeling that has not to be investigated before to the best of our knowledge. Hence, the aim of this paper is to design the human resource management model for SMEs, and to do that business process modeling instruments were employed. The proposed conceptual model represents the workflow regarding human resource activities in small and medium-sized enterprises. The presented human resource business process model is expected to help researchers, business modelers, and analysts, as well as for real professionals for further studies in the domain of human resources management in the SME context.

T. Ramadas
Capability Enhancement in the Manufacturing Industry to Achieve Zero Defect

Manufacturing industries are continually facing the challenge of operating their production processes and systems to achieve the required production levels of high-quality goods while maximizing resource utilization. Zero Defects Manufacturing (ZDM) aims to go further than traditional six-sigma approaches. Traditional Six Sigma techniques have limitations in highly variable production contexts, characterized by small batch productions, customized or even product mix. Manufacturing and design capabilities are essential pillars of the organization. These consist of quality, cost, delivery, flexibility, process capability, and inspection capability. The inspection system plays an important role in achieving zero-defect in the process. Inspection capability and inspector certification are the resultant of an inspection system. Environment health and safety, people development, measurement systems, and continuous improvement systems are also important to achieve zero-defect. In this paper, we plan to improve the existing system to control defect flow-out to the customer end.

Narottam, K. Mathiyazhagan, Pramod Bhatia
Analysis of the Challenges of Industry 4.0-Enabled Sustainable Manufacturing Through DEMATEL Approach

In the present conditions, Industry 4.0-enabled sustainable manufacturing practices can affect whole business system by methods for changing the techniques the things are organized, made, passed on and discarded. Industry 4.0 is reasonably novel to making nations, especially in India and necessities an obvious definition for fitting understanding and practice in business. This paper intends to analyse the key challenges to Industry 4.0-enabled sustainable manufacturing. Decision-making trail & evaluation laboratory (DEMATEL) Process is used to analyse challenges of Industry 4.0-enabled sustainable manufacturing. This work is exceptionally valuable for experts, approach producers, administrative bodies and directors to build up an inside and out comprehension of Industry 4.0 activities and destroy the potential difficulties in receiving Industry 4.0 activities for sustainability.

Bala Sai Prathipati, Anbesh Jamwal, Rajeev Agrawal, Sumit Gupta
Six Sigma in Piston Manufacturing

Process improvement is a key for any company to make profits and improve their quality standards. One of the widely used techniques to do process improvement is by implementation of Six Sigma. In this paper, a Six Sigma analysis was done to reduce the scrap and rework of pistons which are rejected in order to improve the quality and decrease the wastage from money invested. The process variations of skirt diameter and pinhole diameter were controlled by changing a few manufacturing parameters which produced good results.

A. Vamsikrishna, Medha Shruti, S. G. Divya Sharma
Adopting Shop Floor Digitalization in Indian Manufacturing SMEs—A Transformational Study

The objective of this paper is to enumerate a study of the transformation of a brownfield manufacturing facility producing Electro-Mechanical Devices (EMD). Essentially this study can be termed as a testimonial for “Digitalize and Transform” initiative. A Production Digital Twin was developed leveraging the IIoT ready shop floor and adopting appropriate digital technologies. The proven DES model and digital twin methodology can be leveraged for future simulations to support market variability. Discrete Event Simulation (DES) method was deployed to create digital models of the shop floor resources and their interplay to help explore the plant characteristics and optimize its performance. The digital simulation model was integrated with the shop floor IIoT framework in a closed-loop, to run experiments and what-if scenarios with variable input parameters. Using this setup, physical shop floor and the digital simulation model share operational data in a continuous closed-loop to provide decision support for improving plant operations. EDM manufacturer’s target was to set up a re-usable DES model to arrive at actionable insights those can help them improve assembly line performance and get ready for the variable demand and product variants that subsequently would help them in driving business and profitability. Significant improvements were realized across all operational indicators—efficiency, quality, productivity and flexibility. Manufacturing SMEs across India are implementing IIoT and data analytics with the objective of acquiring real-time data thus enabling quick and accurate decision making. The closed-loop discrete event simulation methodology has the potential of enhancing IIoT investments further. Especially in the post-COVID scenario, when manufacturers are challenged with disrupted supply-chain, inconsistent demand and manpower shortages, this methodology can help execute shop-floor plans efficiently with optimum resources.

Gautam Dutta, Ravinder Kumar, Rahul Sindhwani, Rajesh Kumar Singh
Using Hybrid AHP-ISM Technique for Modelling of Lean Management Enablers in MSMEs

The following article explores the use of a hybrid model of Analytic Hierarchy Process (AHP) & Interpretive Structure Modelling (ISM) technique for identification, ranking and modelling of various enablers in Micro Small and Medium Enterprises (MSMEs). The first step involves the identification of various enablers which was accomplished by rigorous literature survey of the available literature and consultation from a panel consisting of experts from academia as well as industry working specifically in MSME industry. The process was further accentuated by the ranking of the various enablers identified earlier, using results of survey sheets circulated amongst the panel members depicting a subjective opinion of rankings by them. The cumulative results of the survey sheets were quantified in the final form using AHP technique depicting final ranking of the enablers. Furthermore, the complex interrelationship amongst the various enablers is represented in a comprehensive manner using ISM technique. The hybrid AHP-ISM model can be used by the industry to identify the key techniques to be focused while adapting the lean manufacturing methods in their operations.

Vivek Prabhakar, Ankit Sagar
Analysis of Influential Enablers for Sustainable Smart Manufacturing in Indian Manufacturing Industries Using TOPSIS Approach

Sustainable Smart Manufacturing (SSM) has played an important role in current competitive business environment. Manufacturing organizations generate waste and environmental pollution through various manufacturing process. This research presents the development of TOPSIS based model for sustainable smart manufacturing practices in Indian industries. TOPSIS method gives an order of preference based on the separation from ideal solution. This paper provides suggestions and directions for manufacturing industries to implement sustainable smart manufacturing practices towards sustainable competitiveness. This research is very much useful for the industry people for selecting the right enabler to implement SSM in the organization.

Sharjil Talib, Abhimanyu Sharma, Sumit Gupta, Gaurav Gaurav, Vimal Pathak, Rajendra Kumar Shukla
Lean Manufacturing Implementation in Crankshaft Manufacturing Company

Companies that are experiencing vast improvements in production and quality in terms of products are widely using lean manufacturing techniques. Lean manufacturing is a systematic approach with the scope of identifying and eliminating the wastes by continuous improvement. Waste can include any activity, step or process that does not add value to the product. Value stream mapping is a lean tool that helps to identify the current flow of material and information in the process and highlights opportunities for improvement that will significantly impact the overall production. This paper illustrates the application of value stream mapping for implementing lean manufacturing in the crankshaft manufacturing company. The current state map was prepared and improvements in the line are suggested and implemented. After implementing future state map, the results show that on application of lean techniques there is a reduction in lead time, material movement and work in process inventory and that in turn lead to increase in productivity to meet the customer demand.

Sagar Sapkal, Abhishek Joshi
Transient Numerical Simulation of Solidification in Continuous Casting Slab Caster

A three-dimensional transient coupled model is developed to investigate the flow field, temperature distribution and solidification in slab caster mold. Finite volume code Fluent is used for solving the governing differential equations of continuity, momentum, energy and turbulence. The enthalpy porosity technique is used for solidification. Different parameters, such as solidification thickness, temperature distribution, velocity vectors are investigated. Solidification thickness is computed at different time intervals: 50, 100, 150 s. The results show that solidification in the mold achieves equilibrium after 100 s. Maximum heat removal occurs at the corners of the mold. Two circulation loop forms after jet strike at narrow face and contributes in superheat transfer and inclusion removal. Solid shell thickness first increases from meniscus then decrease at impinge point due to high superheat transfer and then further increase.

Vipul Kumar Gupta, Pradeep Kumar Jha, Pramod Kumar Jain
Filler Composition Effect on the Mechanical Behavior of the Dissimilar Welds Joint

The dissimilar welding of nuclear grade P91 and P92 steel was carried out using the shielded metal arc welding (SMAW) process. The dissimilar welded joint (DWJ) was subjected to mechanical and metallographic testing for as welded and post-weld heat treatment (PWHT) conditions. The SMAW joint was produced using the different filler composition (P91 filler and P92 filler). For the mechanical behavior of the DWJ, room temperature tensile tests, and Charpy toughness test was conducted for as welded and PWHT state. PWHT of the DWJ contributed a good amount of the ductility of the welded joint. The W and Mo-enriched P92 filler showed a higher tendency to unwanted δ ferrite phase formation as compared to the P91 filler.

Sanjeev Kumar, Chandan Pandey, Amit Goyal
Trochoidal Tool Path Planning Method for Slot Milling with Constant Cutter Engagement

For high-speed machining, special tool paths are required wherewith the tool load is well-controlled, and the path is sufficiently smooth. One of the most effective solutions for controlling the tool load is to keep the cutter engagement constant. For this purpose, advanced tool path generating cycles are available in CAM systems. In case of slot machining, these cycles result in a trochoidal tool path. Since the CAM systems generate these tool paths regardless of the special geometric boundary conditions, each trochoidal period must be calculated separately. However, in our previous researches, it has been observed that the loops of the trochoidal tool path which provide a constant cutter engagement become uniform after a few periods. In this paper, a new method is presented, which can be used for generating this uniform trochoidal tool path shape. The developed method was compared to conventional trochoidal strategies, that were using circular or cycloid curves, and it proved to be significantly better than the traditional solutions. Considering its improved machining efficiency, simplifying the calculation process of this modern strategy can facilitate a wider use. In addition, the formal description of the path generation method provides further opportunities for optimisation.

A. Jacso, Gy. Matyasi, T. Szalay
Modeling and Optimization of Turning Process Using White Coconut Oil as Metalworking Fluid Through Desirability Function

Rapid demand of advanced materials for high-performance applications an immense pact of industrial issue; they also have considerable confront in machining due to poor machinability characteristics. On the other hand, environmental friendly machining techniques have been given major fame and use of coconut oil as metalworking fluid was one of them. For long haul natural contamination and risk to worker’s well-being, the utilization of mineral and synthetic oils based as metalworking liquids has incredible imminent. Machining characteristic under different parametric conditions such as Spindle speed (Ss), Feed rate (Fr), Depth of cut (t), and work material (D) was investigated through response surface methodology using coconut oil as metalworking fluid. Box–Behnken design approach was employed to perform the experimental runs and further they have been optimized through desirability approach. The analysis of variance was applied to identify the significance of created model. The test outcomes approve and sufficiency of the created model. The test results support and adequacy of the made model. The results evidently indicated the favorable aspects of coconut oil.

Anish Kumar, Jatinder Chhabra, Rakesh Kumar Phanden, Arun Kumar Gupta
Surface Veracity Investigation for the WireEDM of Al/ZrO2(P)-MMC

This paper presents investigation of surface veracity of WireEDM surface of Al/ZrO2(P)-MMC. The optimal set of process parameters for WireEDM of considered MMC are obtained using response surface methodology (RSM) for maximum MRR and minimum SR (Ra). In the present paper, surface veracity aspects that include composition, surface defects, and thickness of recast layer are investigated for the machined surfaces which are obtained from the set of optimal process parameters. From the investigation, it can safely be concluded that for the WireEDM of of Al/ZrO2(P)-MMCs, lower parameter setting values of PW and SPT along with higher parameter setting value of TBP are desirable from the viewpoint of good surface finish and surface topography of the machined surfaces, however, higher parameter setting values of PW and SPT along with lower parameter setting value of TBP are desirable from the viewpoint of good material removal rate but surface topography of the machined surfaces contains more micro-cracks, porosity, and deep craters. Further, there is transfer of Cu and Zn ions from diffused wire electrode to the obtained surface.

Sanjeev Kumar Garg, Alakesh Manna, Ajai Jain
Processing and Characterization of Plasma Sprayed LD Slag Coatings on Mild Steel Substrate

Indeed in spite of the fact that kind of metal and ceramic powders are recycled as coating fabric, the usage of fabricating squanders for this reason has not been enough found. Hence, the current study reports on the advancement and execution of plasma sprayed coatings using Linz-Donawitz (LD) slag as the leading material. LD slag coatings are kept on mild steel substrates in several weight proportions at input control levels of the plasma torch. The various mechanical properties such as thickness, hardness, strength, and porosity are discussed in this analysis. This type of coating is measured by computing deposition efficiency. The adhesion strength, efficiency, and coating thickness are affected by the control level of the plasma torch. This effort also exposes that LD slag is especially coated on mild steel substrate.

Pravat Ranjan Pati
Role of Bio-cutting Fluids Under Minimum Quantity Lubrication: An Experimental Investigation of a Sustainable Machining Technique

Cutting fluids with their important characteristics like cooling, lubrication and chip removal functions are always admired highly in the machining industries. Earlier studies show the improvements in overall machining performance with respect to tool life, surface quality, process efficiency and reduced cutting forces. However, environmental and health problems are noted with the use of traditional cutting fluids. Therefore, time demands for alternative to synthetic oil, so bio-cutting fluids are the best possible solution for the same. This study emphasizes on investigations of surface roughness and chip thickness with bio-cutting fluids under the application of minimum quantity lubrication (MQL) condition using Taguchi method. Taguchi orthogonal array has been used for finding best vegetable cutting fluid from three cutting fluids, namely cotton seed, canola and palm oil. Surface finish and chip thickness during turning of AISI 316 is measured. Spindle speed, feed rate and depth of cut are considered as machining parameters. Investigations indicate that the least surface roughness is the outcome of lower feed rate, whereas cutting speed and depth of cut have least impact on surface finish. Shear angle is calculated to find the lowest specific energy required for machining using canola and palm oil.

Shrikant U. Gunjal, Sudarshan B. Sanap, Laxman Jadhav, Nilesh G. Patil
Optimization of Inconel Die-In EDD Steel Deep Drawing with Influence of Punch Coating Using RSM

In the present industrial applications, conventional methods of metal forming and deep-drawn components of various metals and alloys are uneconomical, and the degree of accuracy, as well as responses, is not reported up to the mark. As far as the modern development and challenges are concerned, the present research has aimed to perform the efficient deep-drawing process for the difficult-to-draw materials by applying different coatings on punch materials. The appropriate Inconel 600 material is selected for the die and punches to perform deep drawing on extra deep-drawn (EDD) steel blank. Deep-drawing process performance is reported quite better using tetrahedral amorphous carbon coating on Inconel punch. In the present research, the selected coating exhibits the best choice among coating of molybdenum disulfide and brycoat titanium nitride. Clearance, blank thickness, and blank holding force are selected as critical input parameters to get the desired deep-drawing responses as limiting draw ratio (LDR), surface roughness, residual stress, and thinning. During the tetrahedral amorphous carbon coating on the punch, responses LDR, surface roughness, residual stress, and thinning are optimized as 1.8586, 0.8934, 268.1440, and 2.7201 by selecting the clearance as 2.7899, blank thickness 4.40, and blank holding force 11.00 using response surface methodology (RSM).

Naveen Anand Daniel, Umesh Kumar Vates, Bhupendra Prakash Sharma, Nand Jee Kanu, Sivarao Subramonian
Effect of Current on the Hardness of Weld Bead Generated by TIG Welding on Mild Steel

TIG welding is the most common metal-joining process widely used in all manufacturing industries. The welder strikes an arc at the start of the weld, and creates a puddle, holding the electrode at a 10°–15° angle from the vertical. The electrode is pointed in the direction of the weld, and the welder “pushes” the molten metal forward by moving the electrode and the arc in the same direction. The quality of weld bead decides the reliability of the structure. The quality of weld mainly enhances the mechanical properties of the weld. In this paper the authors propose the correct welding parameter to get good weld bead quality. It is observed that the bead quality effect of welding speed and welding current on the hardness has been investigated, and that the hardness of welded joint has increased with the increase in current up to 110 A for 6 mm thick plate; then the hardness is reduced with increase in current. Higher current can lead to splash and workpiece damage. Due to thinner workpiece, high current can lead to widening of the material gap. This can also lead to heat damage and a much larger weld-affected area, and longer period of time to deposit the same amount of filling materials. Inverted microscopic analysis has been done on the weld zone to evaluate the effect of welding parameters on weld quality. To enhance the property of TIG quality of weld bead, dye penetration test is also performed.

Moazzam Mahmood, Vijay K. Dwivedi, Rajat Yadav
Hot Corrosion Study on Dissimilar Weld Joints of Austenitic Stainless Steel and High Strength Low Alloy Steel

Amalgamation of austenitic stainless steel (ASS) and high strength low alloy steel (HSLA) as tube is used in many applications of boiler and heat exchanger where high temperature occurs. Owing to the availability of welding, weld joint faces high temperature. Keeping in view, weight gain studies have been carried out on weld joints assembled with shielded metal arc welding (SMAW), pulse current gas metal arc welding (P-GMAW) and tungsten inert gas welding (TIG) under the environment of Na2SO4 and V2O5 (60%) in melted condition at 600 and 650 °C for 1 h heating and 20 min cooling as cycle. It has been found that the specimen layered with this mixture obeys the parabolic rate law. The thickness of scale on HSLA steel side was higher and more liable to spalling. The impact of coating of melted salt atmosphere on hot corrosion behaviour of weld is further explained. It was observed that the higher the temperature of exposure, the greater will be the corrosion and weight gain by the weld joint.

B. P. Agrawal, Ramkishor Anant
Quality Improvement in Assembly of ‘Head Lamp Leveling Switch (HLLS)’ by Continuous Improvement Methods Utilization

The automotive industry is the world’s largest manufacturing industry with an activity that is frequently impacted by trade, investment regulation, manufacturing process, and environmental standards. In order to compete in such an industry, manufacturing managers have to put their efforts in motivating their personnel to increase their efficiency and improve the processes to achieve a common successful goal of improved productivity and quality. In the context of the above, focus was made to implement the lean concepts (Kaizen and Poka-yoke) to improve the quality of one of its products ‘head lamp leveling switch (HLLS)’ in the assembly line by reducing cycle time, lead time, and rejection. In this research five steps of the DMAIC cycle were used to synchronize the findings and their effects throughout the manufacturing cycle. After implementing the solutions switch rejection gap has been reduced from 6 to 0 in a shift of 7.5 h.

Anil Kumar, Rakesh Giri
Modeling and Control of Arc Welding Processes Using Artificial Neural Networks

The strength of artificial neural networks (ANN) for prediction of output welding process parameters for given input welding process parameters is shown in this work. Some important concepts of ANN are discussed. A model for weld bead geometry relating to input process parameters is made with the help of a computer program in C++. Feed-forward back propagation algorithm of ANN is used in this work. Real TIG welding data are used for the evaluation of the performance of the ANN. After comparison of the experimental dimensions with the predicted dimensions of the weld bead geometry, it is concluded that the ANN model is capable of forecasting the output parameters accurately if the input welding parameters are known.

Rudra Pratap Singh, Aman Singh, Somil Dubey, Subodh Kumar
Influence of Process Parameters on Reinforcement Height of Tungsten Inert Gas Welded Joints for Low Carbon Steel AISI 1010 Plates

In the present work, tungsten inert gas welding process was used to analyze the effects of input process parameters on reinforcement height of weldment. The input process parameters were used as current, voltage, speed of welding and the feed rate. Low carbon steel AISI 1010 plates of dimensions 75 mm × 50 mm × 5 mm were used to obtain the weld. Totally, 16 pairs of plates were welded to obtain 16 welds using tungsten inert gas welding process. At first, current, voltage and speed of welding were kept at constant values and the feed rate was varied one by one as 2.12, 4.23, 6.35 and 8.47 mm/s, respectively, for four welds. In each case the reinforcement height was measured. This was used to investigate the effect of feed rate on reinforcement height. In the similar manner, other three sets, each having four welds were used to investigate the effect of welding speed, welding voltage and welding current on reinforcement height, respectively, by keeping other variables at some fixed values. The results were tabulated and were expressed in four diagrams to investigate the effect of feed rate, welding speed, welding voltage and welding current on reinforcement height in each case. It is concluded that the reinforcement height increased with increase of current, voltage and feed rate and decreased with welding speed.

Rudra Pratap Singh, Ashu Kumar Verma, Abhishek Mishra, Abhishek Chauhan
Effect of Process Parameters on Spark Energy and Material Removal Rate in Electro-Discharge Machining Process

Electro-discharge machining process is a very important non-traditional, cost-effective and non-contact technique of machining electrically conductive materials which are extremely tough, brittle and difficult-to-cut. The material removal takes place electro thermally with the help of several discrete discharges between the work and the electrode. It is used to manufacture complex geometries and intricate shaped sections with very high accuracy. The material removal rate and spark energy both depend on the input process parameters in this process. The efficiency of the machining process can be maximized by optimizing the input process parameters. The material selected for this study was Inconel-925. In this work the effects of input parameters like pulse on time, current and voltage were studied on the metal removal rate and spark energy by applying the sensitivity analysis. This was performed by taking two input parameters as fixed and the third one as varying for all the three input variables. The variations were tabulated, and the graphs were drawn to understand the effect of individual input parameters on the metal removal rate and spark energy. After the sensitivity analysis it was found that metal removal rate in electro-discharge machining process increases with increase in current, increases nonlinearly with increase in voltage and increases with an increment in pulse on time up to a certain limit and then keeps on decreasing.

Rudra Pratap Singh, Ashish Pal, Deepak Raghuvanshi
Multi-objective Optimization of Aerofoil

NACA 0012 aerofoil has been optimized for maximum lift and minimum drag in different environmental conditions. This redevelopment has been achieved by two modern lift maximization techniques together, vortex generator and morphing. The vortex generator provides a proper path to the air flow that leads to increase in the lift, and morphing enables the structure of aerofoil to change according to the environmental conditions of flight. Keeping all the factors in mind, an aerofoil has been generated and optimized using ANSYS 14.0 software. The result indicates that the coefficient of lift (Cl) has increased in noticeable proportion of 16.67% and the coefficient of drag (Cd) has increased but in small proportion of 6.67%, which suggest that our target has been achieved.

Prateet Dosi, Prem Kumar Bharti, Niharika Borah, Anjan Barman, Mriganka Baishnab, Soumyabrata Bhattacharjee
Preliminary Investigation of Wire Cut EDM on Polycrystalline Silicon Ingot

The semiconductor and solar industry face the great difficulty in cutting of silicon ingots in conventional machining to facilitate the manufacturing of solar cells. In this research work the wire cut EDM non-conventional tool was selected for cutting of polycrystalline silicon. The individual influence of various input parameters such as Ton, Toff, IP, SGv, WF, WT and WP on cutting speed and kerf width was investigated. The influences of all the parameters were examined through one factor at a time approach. The results obtained through this preliminary investigation due to increase of Ton, IP and decrease of Toff, SGv have significant influence on cutting speed and kerf width. The WF, WT and WP have less influence observed on performance measures. The machined surfaces were examined through scanning electron microscope and also the element migration through energy-dispersive X-ray analysis was examined. Further, this preliminary investigation has been employed to fix the level of parameters for the main study and the results find the application in photovoltaic and semiconductor industries.

Raminder Singh, Anish Kumar, Renu Sharma
Taguchi-Based Hardness Optimization of Friction Stir Welding Process

Friction stir welding (FSW) has been widely acceptable in various welding applications nowadays due to its versatility like the ease in use and eco-friendly. FSW is a solid-phase joining process. It has the inherent property to weld aluminum and other such metals over conventional or solid/liquid phase joining process. FSW seems to be an efficient and one of the new developments in the field of joining process. In the present study, the Taguchi optimization technique is used to improve the hardness and other operational parameters on AA4015. Results show that for maximizing the hardness and optimizing operational parameters of the welded joint, the feed rate is the most influential factor.

Shwetank Avikal, Jasmeet S. Kalra, Rohit Singh, K. C. Nithin Kumar
A Fundamental Introduction and Recent Developments of Magnetic Abrasive Finishing: A Review

Recent industrial progress demands various advance machining operations for achieving the superfinishing surfaces. These types of surface cannot be achieved by conventional finishing processes such as grinding, burnishing, honing and lapping. In many cases, some parts of machine do not have requisite surface finish and properties of surface. Firstly, honing superfinishing and other finishing operations are used to finish the small part of a machine. Medical instruments, components of aerospace and other atomic energy parts demand accuracy in surface finish. For finding this type of finishing, a recent or novel finishing operation is denominated, which is known as magnetic abrasive finishing process. The magnetic abrasive finishing is a non-traditional finishing process. This process is applicable to achieve good surface finish and enhance mechanical properties. In magnetic abrasive finishing, the workpiece is put between the magnetic North and South Poles and the gap between the poles and the workpiece is filled with magnetic abrasive particles. The magnetic abrasive flexible brush is made when abrasive particles interact with each other and magnetic field is created in the finishing zone for removing materials to achieve good surface quality of the workpiece material. In this paper, we discuss the different parameters of MAF which have a huge impact on the achievement of surface finish as well as on surface quality of various alloys.

Ashutosh Pandey, Swati Gangwar
Study of the Effect of Dielectric on Performance Measure in EDM

Electrical discharge machining (EDM) is an electro-thermal machining process, which is basically a nonconventional method and is broadly used for machining of intricate cut of the hard materials like super alloys or composites with high precision and accuracy. In this process, a pulse discharge is generated between the workpiece and the tool, and also the removal of material from the workpiece takes place. This removal occurs in the presence of dielectric fluid, due to melting and vaporization. In machining process, the dielectric fluid plays a significant role, affecting the different response variables such as material removal rate (MRR), kerf width, surface roughness (SR), tool wear rate (TWR), and so on. So many important factors are considered when we use dielectric fluid in EDM machining such as health, safety and environment, especially when hydrocarbon-based dielectric fluids are used. Toxic emission in this machining process leads to various environmental problem, several health issues due to release of toxic fumes, vapors and aerosols during the machining process. This paper presents the study of different dielectric fluids used in electro-discharge machining and suggests the alternate green dielectric to minimize the environmental impact, leading toward the sustainability.

Md. Ehsan Asgar, Ajay Kumar Singh Singholi
Optimization of Cylindrical Grinding for Material Removal Rate of Alloy Steel EN9 by Using Taguchi Method

Grinding is a machining process used to finish the component. The composition of abrasive grains forms the grinding wheel. The grinding tool made up of abrasive grains is used to remove tiny-sized material from the workpiece. The parts which are machined from an initial shape are generally cylindrical. Increasing the material removal rate (MMR) is often accompanied by tool wear. The primary objective of the study is to use the Alloy Steel EN9 in cylindrical grinding machining to determine the cutting speed, depth of cut, and feed rate on the process of performance as material removal rate. The experiment is conducted using the aluminum oxide (Al2O3) grinding wheel. In this work, the test is outlined using the Taguchi method and the gray relational analysis (GRA) method. For single optimization, it is found that the depth of cut affects more on MRR. Based on the experimental results for single optimization Alloy Steel EN9 for cylindrical grinding may be used with MRR. It is observed that the depth of cut is the most important factor by 92.05% and then the minimum influence due to cutting speed by 4.66% and feed rate by 0.94%. The maximum MRR obtained is 2.675 g/min, by using a cutting speed 1900 rpm, depth of cut 0.06 mm, and feed rate 0.04 mm/rev. MRR is linearly raised with a depth of cut. Finally, an attempt has been made for the estimation of the optimum cylindrical grinding machining conditions to produce the best desirable response within the experimental constraint.

Pravin Jadhav, Pranali Patil, Sharadchandra Patil
Adaptation of 3D Printing Technology for Fabrication of Economical Upper Limb Prostheses

Fabrication of prostheses with accurate size, comfort and patient-specific shape is the desired feature. Moreover, the need to fabricate economical prostheses is also crucial, especially for children who outgrow the prostheses over time. In this regard, the type of prostheses and selection of the fabrication process plays an important role as it can critically affect the cost. 3D printing technology offers tremendous design freedom as any complex geometry can be fabricated with ease as compared with other manufacturing processes. The technology also provides customization, which is one of the unique requirements for the fabrication of prostheses. The present paper discusses the feasibility of adaptation of 3D printing technology for research and development of the prosthetic hand. Moreover, a case study is provided for designing a prosthetic hand and utilization of 3D printing for its fabrication. It can be inferred that for the fabrication of customized prosthetic hand, 3D printing can be effectively utilized. It can provide an effective route for developing an economical yet functional prosthesis.

Vishal Francis, Sushil Kumar Singh, Raksha G. Bhonde, Yash H. Tichkule, Vaishnavi S. Gupta, Swaraj P. Farande
Effect of EMG Denoising on Classification Accuracy of Sit to Stand Phases

Electromyography (EMG) signals have been used in clinical diagnosis and rehabilitation owing to the information that the signal carries about motion intent. However, EMG signals are inherent to noise which degrades the performance of classifiers. In the present study, denoising of the EMG signal was studied with its effect on the classification accuracy of sit to stand (STS) phases. Four different phases of STS task were marked with the help of knee and trunk angular deviation data as acquired during the experimentation on five healthy participants. Two different denoising methods were considered; one method (D1) deals with seventh-order Daubechies wavelet denoising, while in the second method (D2), Teager–Kaiser energy operator (TKEO) was applied over the previously denoised EMG signal in D1. Method D2 was found to improve the overall accuracy of the K-nearest neighbors (KNN) classifier with the highest improvement in the true positive rate of intention phase (Phase II) of STS task.

Siddharth Bhardwaj, Abid Ali Khan, Mohammad Muzammil
Study of Consistency Establishment of Deviation in Quality Norms During Manufacturing of Crown Wheel Pinion

Deviation in norms is a standard used to measure the manufacturing quality of product. The aim is to achieve desired quality output for the manufacturing process of crown wheel pinion, to expel the inconsistency for the variation of deviation standard. The manufacturing process is categorized into various subprocesses on which the quality of parameters depends. Due to the process errors, these DIN values are going beyond actual quality standard and it has to be as low as possible to improve the product functioning toward maximum efficiency. Various tests are performed over the manufacturing process to find out the root cause for inconsistency in quality standard of product. The analysis is conducted by varying the cutting tool speed and accuracy over the number of jobs done. Significant enhancement over the smoothness and manufacturing quality of product was observed, with the comparative analysis being done to verify the actual results with the conventional one.

Jadhav Piyush Kishor, Anoop Kumar Shukla, Meeta Sharma
Parametric Optimization of Gas Tungsten Arc Welding Using AHP-Based Taguchi Method

In the present paper, AHP-based Taguchi approach is used to choose the perfect combination of welding process variables for the gas tungsten arc welding (GTAW) process of two different metals, MS (AISI 1040) and SS (AISI304). Initially, the Taguchi method is used to discover an optimum mix of process parameters. Since the Taguchi method could not address the multi-objective optimization problem, therefore the MODM method (AHP) is used to find the best combination of input process parameters based on the set criteria. Process variables considered for the study are travel speed of the weld, current, gas flow rate, and weld angle. During this study, methodology of this approach is explained in detail. This AHP-based Taguchi method helps to select the best combination of process parameters from among many different combinations of the process parameters.

V. Naranje, Mohammad Nadeem Khalid, Avinash Kamble, Mohammad Arif
Parametric Evaluation of Lathe Boring Operation to Improve the Surface Finish of Gray Cast Iron (SG-260) Under Dry Condition

The role of surface roughness is very important in machining processes. The surface finish and tolerances are most critical quality measures in various mechanical products. The main objective of this paper is to find out the effect of machining parameters on a surface roughness in a lathe boring operation in dry condition. This paper shows the study of surface roughness for boring of gray cast iron (250BHN) by using carbide tool under dry condition. The effect of boring parameters (tool nose radius, feed, spindle speed and depth of cut) was analyzed using analysis of variance. These variables were computed using Taguchi’s design of experiments (DOE). The DOE gives the optimal values of speed, feed and depth of cut for tool nose radius of 0.4 and 0.8 mm. The three-factor three-level fractional experiments were conducted. This result shows that the effects of speed, feed, depth of cut and tool nose radius on surface finish are statistically significant. The results observed that using larger tool nose radius always gives a good surface finish. The results also revealed that the following level for each of the factors produces the smooth surface finish within the range of experiments: larger tool nose radius, lower feed, higher speed and lower depth of cut.

Dayanand A. Ghatge, R. Ramanujam, Dipali Ghatge
Impact of Casting Parameters on Surface Roughness and Hardness of Squeeze Cast Beta Brass

In the present study endeavor has been made to research the castability of brass alloy, that is, beta brass using squeeze casting process. The castability was assessed by examining the impact of squeeze casting parameters, namely pouring temperature at 950, 975 and 1000 C levels, squeeze pressure of 80, 120 and 160 MPa and dwell time of 15, 30 and 45 s, on surface roughness and hardness using Taguchi design of experimentation method. Signal-to-noise ratio, smaller is better for surface roughness and larger is better for hardness, is used for the analysis. The results of the study showed that the optimum condition in order to get minimum surface roughness for squeeze cast Beta Brass is pouring temperature with 950 C, squeeze pressure with 120 MPa and dwell time with 30 s as most significant parameter. The optimum condition in order to get maximum hardness for squeeze cast Beta Brass is pouring temperature with 1000 °C, squeeze pressure with 120 MPa and dwell time with 15 s, with squeeze pressure as most significant parameter.

Mohd Talha Khan, Deepak Singh, Udit Vasishthta
Impact of Step Size, Spindle Speed and Sheet Thickness on Forming Force in SPIF

Single Point Incremental Forming (SPIF) is a viable and flexible forming technique that has great potential to fulfil the need of various emerging areas like automobile and aerospace sectors. In addition, this technique has the ability to trigger the revolution in rapid prototyping and batch-type production of sheet material components. The flexibility and the ability to be economical can save the energy that in turn makes this process ready for green manufacturing. The prediction and measurement of forming forces during the SPIF process determine the size of forming machinery and additional hardware along with preventing the failures of facilities. This work focuses on the investigation of some significant input factors of this die-less process on maximum axial forming forces. The detailed knowledge about the impact of input factors would help the researchers and engineers to increase the viability of this process on an industrial scale. Results showed that components can be formed by minimal axial forces (886 N) when a combination of lower sheet thickness (0.8 mm, in this case) and lower step size (0.2 mm, in this case) are taken into account. Thicker sheets can be formed with smaller forming forces by employing higher spindle speed, and energy can be saved up to a larger extent.

Ajay Kumar, Parveen Kumar, Vishal Gulati, Yajvinder Singh, Vinay Singh, Ravi Kant Mittal
Straightness Accuracy Estimation of Different Cavity Geometries Produced by Micro-electrical Discharge Milling

The purpose of this paper is to present the results of an investigation on the straightness achievable on three cavities: channel, square and cross-channel (square pillars). The steps included machining of cavities in series of three having a nominal dimension of 1000 µm on a steel sample using 200 µm tungsten carbide electrode in micro-electrical discharge-milling (µ-ED-milling). An Olympus optical microscope was utilized to examine the geometry of micro-cavities. The Least Square Method (LSM), which is commonly used in metrology for fitting reference elements, has been used. The LSM solutions for the primary set of data points obtained through Olympus Analysis Five software measurements were calculated to find the achievable straightness. It was found that straightness tolerance of square pillars (19.19 μm) is better than microchannels (31.33 μm) and far better than square geometries (50.66 μm).

Shrikant Vidya, Reeta Wattal, P. Venkateswara Rao, Nagahanumaiah
Deform 3D Simulation Analysis for Temperature Variation in Turning Operation on Titanium Grade 2 Using CCD-Coated Carbide Insert

In machining, tool life plays a significant role in proclaiming the manufacturing process appropriate for the fabrication of a product with desired properties. Machining experiments require complex conduct and testing setups. DEFORM 3D is an adequate tool that provides a limitless range of factors and conditions along with a graphical analysis of results. Simulation has been carried out for the turning operation on titanium grade 2 using a CVD-coated tungsten carbide insert using DEFORM 3D software. The effect of cutting speed as well as feed on the cutting tool-chip interface temperature has been studied and validated with experiments with an error percentage of 3%. It is perceived that the increase in cutting speed and feed both has raised the tool-chip interface temperature.

Rahul Sharma, Swastik Pradhan
Estimation of Surface Roughness in Turning Operations Using Multivariate Polynomial Regression

Surface Roughness plays a huge role in determining the durability of components. Surfaces are required to be within desired limits of roughness values to ensure high performance. Being able to predict the surface roughness without using stylus-based instruments reduces the tool changing and measuring time hence decreasing the overall machining time. The experiment suggests a statistical approach to predict the surface roughness before the machining operation based on the previous performance of the tool. The cumulative length of the chips generated was used along with the three cutting parameters, i.e. cutting speed, feed, and depth of cut to predict the surface roughness of the material depending on the number of operations performed on the lathe machine. An algorithm based on multivariate polynomial regression was used to predict the surface roughness of the material corresponding to the usage based on the experiments that were conducted on the Mild Steel Rod by using an HSS tool. This dynamic prediction will help determine the right time to change the tool according to the given machining parameters and hence increase the tool life.

Hrishabh Jha, Ashutosh Panpalia, Devanshu Suneja, Geetanshu Ashpilya, Hitesh Kumar, Vijay Gautam
Effects of Cutting Parameters and Cutting Fluids in Turning of Aluminium Alloy

The purpose of this paper is to explore the effects of cutting parameters (feed rate, cutting speed, depth of cut, and cutting fluid) on material removal rate (MRR) and surface roughness in turning of Aluminium 6063-T6 alloy by employing the Taguchi method. Experiments have been conducted using L16 orthogonal array, and a new cutting tool was used for each test to maintain accurateness of the performance measures. The effects of feed rate, cutting speed, and depth of cut on surface roughness and MRR under dissimilar cutting fluids were analysed by analysing the Signal-to-Noise (S/N) ratio calculated through the Minitab software.

Farhan Akhtar, Sakim Hasan, Shrikant Vidya, Kamlendra Kumar, Amit Kumar
Multi-objective Optimization and Modelling of AISI D2 Steel Using Grey Relational Analysis and RSM Approaches Under Nano-based MQL Hard Turning

AISI D2 is a high-carbon and high-chromium cold-work tool steel, which exhibits various properties such as high wear resistance, high hardness, high strength and rapid strain hardening. Because of such kind of properties, the AISI D2 cold work steel is considered as a difficult material to be machined. The selection of process parameters plays a very vital role in terms of output quality characteristics such as surface roughness and cutting force. The current work focuses on the application of grey relation theory combined with central composite design (CCD) for optimizing the process parameters for machining AISI D2 hardened steel (54 ± 1HRC). TiAlN PVD-coated inserts of different geometry are selected to machine the AISI D2. Surface roughness and cutting force are chosen as an output response. By executing the confirmation experiments, it is observed that grey relational analysis is a valuable methodology to find out the optimum level of parameters. The optimum parameters are cutting speed 105 m/min, feed 0.04 mm/rev, depth of cut 0.4 mm and rake angle 1°. Regression-based models are also developed for predicting the cutting force and surface roughness values using the RSM approach.

Vaibhav Chandra, Andriya Narasimhulu, Sudarsan Ghosh, P. Venkateswara Rao
Metadata
Title
Advances in Industrial and Production Engineering
Editors
Dr. Rakesh Kumar Phanden
Dr. K. Mathiyazhagan
Dr. Ravinder Kumar
Prof. J. Paulo Davim
Copyright Year
2021
Publisher
Springer Singapore
Electronic ISBN
978-981-334-320-7
Print ISBN
978-981-334-319-1
DOI
https://doi.org/10.1007/978-981-33-4320-7

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