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2023 | Book

Digital Transformation and Industry 4.0 for Sustainable Supply Chain Performance


About this book

This book provides the interplay between digital transformation, industry 4.0 technologies, and sustainable supply chain performance. The book mainly focuses on presenting case studies and empirical studies demonstrating how the industry 4.0 technologies interact with the conventional manufacturing practices such as lean manufacturing, circular economy practices, total quality management, and maintenance management, while achieving enhanced sustainable supply chain performance. The book guides the practitioners to consider the status of conventional supply chains in their organisations while designing industry 4.0 systems. This book is a useful resource for researchers and academicians to understand the interplay between existing technologies, industry 4.0 technologies, and sustainable performance in the digital transformation journey.

Table of Contents

Big Data Analytics for Supply Chain Transformation: A Systematic Literature Review Using SCOR Framework
Recent developments in information technology generating massive amount of data are referred to as big data. Such data with variety and velocity pose a challenge to supply chain management (SCM) practitioners on how to deal with them to draw valued insights for enhanced decision-making. The analysis of big data can offer unique intuitions into supply and market dynamics like understanding the customer preferences, developing new products, demand forecasting, supplier selection and evaluation, process improvements, quality control, capacity planning, managing delivery schedules, order management, etc., to reduce the supply chain costs and improve product availability. Thus, this chapter reviews and classifies the literature on big data analytics (BDA) application in SCM. We extracted and reviewed about 200 academic journal and conference articles from 2010 to 2017 from various research databases to know the extent of BDA applications in different supply chain domains (plan, source, make, deliver and return). The papers were also classified based on analytics (descriptive, predictive and prescriptive) and the supply chain resources utilized (financial, human, technological, organizational and intangibles). Based on the review results, we propose a supply chain (SC) visibility framework that identifies SC visibility as a key driving force for SC transformation, achieved through strong BDA capability. The findings of this review and future research directions will help the academics, researchers and practitioners to focus on the BDA opportunities and challenges.
Sachin S. Kamble, Rahul S. Mor, Amine Belhadi
Unveiling the Role of Evolutionary Technologies for Building Circular Economy-Based Sustainable Manufacturing Supply Chain
The fourth industrial revolution (Industry 4.0) is influencing and transforming the manufacturing industries’ business activities. To meet rising customer demand and changing behaviour with limited resources, the manufacturing industries must adopt a circular economy idea from traditional linear economies with the use of Industry 4.0 techniques. This study investigates the applications of Industry 4.0 techniques in creating a more promising circular economy concept (CEC) in manufacturing industries by identifying how Industry 4.0 techniques support CEC and how effective manufacturing industries are adopting CEC with the application of Industry 4.0 techniques to fulfil consumer demand and change consumer behaviour for the sustainability of services to people in communities and business survival. Qualitative research methodologies were employed in the study to collect high-quality material from previous research and conduct interviews with corporate executives. Forty research articles were reviewed, and ten company executives from the Papua New Guinea (PNG) manufacturing industry were interviewed. According to the survey, the adoption of Industry 4.0 approaches by manufacturers in each country to establish a promising CEC varies. Rich countries are ahead of the curve in terms of leveraging Industry 4.0 technology to create a promising CEC, whereas poor countries are following the trend, albeit at a slower pace. According to the study, Industry 4.0 is the true facilitator of CEC. Finally, opportunities and threats are revealed and reported, which might encourage manufacturing companies to use Industry 4.0 technology to build a promising CEC.
Rashmi Prava Das, Kamalakanta Muduli, Sonia Singh, Bikash Chandra Behera, Adimuthu Ramasamy
Smart Technologies Interventions for Sustainable Agri-Food Supply Chain
Global demand for safe food products is increasing, thus making an increased pressure on the supply chain system of organizations to meet the demand. Smart technologies form the crucial competitive advantage for an organization ensuring that their supply chain is effective for value creation and sustainability. New advanced digital technologies such as blockchain, artificial intelligence, the Internet of Things, smart wearable, 3D food printing and robotics have a great impact on the upliftment of the performance of the supply chain as per the organizational need and operational requirements. This study uses factor analysis tool to derive factors that are perceived as challenges towards the adoption of smart technologies. Security threat, technology upgradation, high investment and partner’s rejection are the major challenges perceived. This study also highlights the derived perceived benefits from smart technologies like removal of the drudgery of labour, reducing wastage, quality product, enhancing transparency, cost efficiency, etc. in the agri-food supply chain. The authors discuss these factors in detail with various inputs from industry professionals and current literature on the subject.
Suyash Manoram, Anupama Panghal
Wireless Sensors’ Location for Smart Transportation in the Context of Industry 4.0
The evolution and growing use of Information and Communication Technologies (ICT) in the manufacturing industry has enabled to produce in a more intelligent and sustainable way. Technological innovations have opened a wide range of opportunities to use Internet of Things (IoT) in logistics sector. The increasing adoption of ICT in logistics activities induced a global organizational efficiency as well as a good level of competitivity for companies. As a keystone in logistics operations, transportation is intended to play a significant role in the future digital revolution. Indeed, the challenge is to build a safer, sufficiently flexible, and more efficient transport system. Such smart transportation system is based on a set of different wireless sensors. The located network of sensors would help in the route optimization, accident prevention, parking, road anomaly detection, etc. In this paper, we propose different linear formulations for the “Wireless Sensors Location Problems” in the context of Industry 4.0. The presented programs are validated by solving small and medium data set instances using CPLEX solver. Several extensions are presented and discussed. To model the uncertainty in some decisions, fuzzy linear programs are presented and solved to optimality using a parametric approach. We also describe a modeling traffic flow using a nonlinear transport equation. Then, we study the observability of traffic conditions on highway segments.
Mustapha Oudani, Sarah El Hamdi, Abderaouf Benghalia, Imad El Harraki, Hanane El Raoui, Karim Zkik
Barriers in Smart Green Resilient Lean Manufacturing: An ISM Approach
Smart, green, resilience and lean are considered to be a suitable solution to not only improve the green performance but also improve the operational performance. Nevertheless, smart, green, resilience and lean still face several challenges that hinder their implementation. By reviewing the literature, this paper intends to highlight these barriers and analyse the links existing between them. Using ISM-based modelling approach and using the insights of experts, we developed a hierarchical model of barriers in implementing the smart, green, resilient and lean manufacturing (SGRLM). After the application of the ISM technique, a seven-level structural model has been deduced. The lack of regulations and government support was found to be the topmost important barrier in SGRLM. Further, we used MICMAC analysis to categorize the set of barriers for a better comprehension and visibility; seven barriers are identified as driver barriers, two as dependent, two barriers as linkage and one autonomous barrier.
Imane Benkhati, Fatima Ezahra Touriki, Said El Fezazi
Secure Model for Records Traceability in Airline Supply Chain Based on Blockchain and Machine Learning
With the enormous amount of sensitive data generated by supply chains and with the accession of Industry 4.0, the development of airline supply chain management (SCM) strategies and the preservation of privacy have become a necessity. The implementation of robust privacy strategies allows supply chains to protect their personal data from being lost, used, or accessed in an unauthorized way. Blockchain technologies (BT) allow data to be traded transparently and to automate transactions through smart contracts. Indeed, blockchain technology is attracting more and more attention as it ensures integrity and non-repudiation. However, secure supply chain existing models neglect the complexity of the airline supply chain management (ASCM), data confidentiality, and advanced and persistent attacks (APT) which make them exposed to many vulnerabilities. In this article, we propose a blockchain-based framework suitable for the ASCM context. Thus, we will develop an efficient model based on blockchain and machine learning to authenticate, validate, and secure transactions between suppliers and legitimate users on ASCM environments. The proposed solution reduces transaction costs, enhances security level by detecting and preserving anomalies, and fosters transparency and validity of transactions.
Karim Zkik, Anass Sebbar, Narjisse Nejjari, Sara Lahlou, Oumaima Fadi, Mustapha Oudani
The Role of IoT and IIoT in Supplier and Customer Continuous Improvement Interface
For firms devoted to growth and survival, the total quality management (TQM) strategy is both a practical working procedure and a quality mindset. TQM begins with the belief that concentrated management action may increase the quality of the organization’s service and goods at a very low cost, hence satisfying customer needs and growing market share. The PDCA (plan do check act) cycle with IoT (Internet of Things) and IIoT (Industrial Internet of Things) approach refers to a continuous movement in a certain direction between producers/suppliers and process of the system, including people, plant and machinery, and material methods environment to manage the voice of a producer and the voice of the customer. The PDCA cycle in the system generates actions with measurable outcomes and is a process, and the ultimate goal is to make it perfect the process. IoT and IIoT have received a massive amount of attention worldwide in the past few years as IoT aims to make customers’ lives easier and more convenient, while IIoT aims to improve the safety and efficiency of manufacturing facilities. Further, this chapter also looks at their responsibilities as a supplier and a customer, taking into account the PDCA cycle in the existing manufacturing system, where IoT is used to track B2C (business-to-consumer) transactions.
Vimal Kumar, Nagendra Kumar Sharma, Ankesh Mittal, Pratima Verma
Customer Relationship Management in the Digital Era of Artificial Intelligence
Customer relationship management (CRM) is an effective tool to understand the customers of an organizations in systematic manner. CRM helps by identifying the best customers of an organization. It helps to maximize the value of the customer by satisfying and retaining them for an organization. Artificial intelligence (AI) integrated with CRM known as AI-CRM helps in many ways like automating the routine tasks, quick and accurate analysis of huge volume of customers’ data, decision-making process, recommendations to the salespeople, and so on. The aim of this chapter is to examine the role of AI-CRM system in the organizations and how it can help the organizations’ growth by improving its sales performance and decision-making process. The chapter also highlights different AI-CRM related tools available in the marketplace and their features and functionalities. This chapter also shows few of the technologies used by AI-CRM system to improve the process efficiency, sustainability and digital transformation of the sales, marketing, and operations departments of the organizations. Finally, the chapter also discusses few of the upcoming technologies and their benefits which would essentially improve the bottom line of the organizations and improve their sustainability.
Sheshadri Chatterjee, Ranjan Chaudhuri
Efficient Supplier Selection in the Era of Industry 4.0
With the advent of fast computers, availability of data, and development of sophisticated algorithms, every sector is undergoing a process of rapid advancement. Industries utilize advanced technologies to digitize various phases of the supply chain (SC) for better production and enhanced customer experience. Supplier selection is a fundamental part of supply chain management (SCM) and has an immense scope of exploiting emerging technologies like IoT (Internet of Things), big data analytics, cloud computing (CC), etc. The present study provides brief research and a comparison of the conventional methods or models accessible in literature and the role of Industry 4.0.
Deepanshu Nayak, Meenu Singh, Millie Pant, Sunil Kumar Jauhar
A Comparative Approach for Sustainable Supply Chain Finance to Implement Industry 4.0 in Micro-, Small-, and Medium-Sized Enterprises
In the present competitive business environment, the adoption and implementation of Industry 4.0 technologies have a significant issue for micro-, small-, and medium-sized enterprises (MSMEs) due to lack of leadership, visibility, skills, resource, and unawareness of government aid/schemes. Therefore, the negligence of liabilities, sustainability, and financing issues force the MSMEs to steadily ceding ground to larger firms. Whereas, recent studies reveal that sustainable supply chain financing strategies can overcome these issues by incorporating the resource optimization approach. This chapter optimizes the available financial resources (government aid, internal, and external resources) with a data envelopment analysis method and incorporates ratio data with zero inputs. To find the relevant literature, first, we performed a systematic literature analysis that confirmed a lack of literature on sustainable supply chain financing strategies to implement Industry 4.0 technologies in MSMEs, and we found DEA is a suitable method to address ratio data with zero inputs. Our finding suggests flexible strategies for efficient financial decision-making units (DMUs) for MSMEs to implement Industry 4.0. Besides, the Pareto chart represents that a higher rank of DMUs will always have a higher coefficient of performance. The analysis shows that lending from higher profit-sharing stakeholders with higher interest rates should be avoided in Industry 4.0 implementation. The proposed model provides a better evaluation of the carrying value of loan amount, which can enhance the visibility and flexibility of MSMEs to maintain the recurring payment. The computation work is performed on the R-version 4.1.0 platform with modified additive DEA, benchmarking, multiplier DEA packages, and Microsoft Excel tool.
Pratik Maheshwari, Suchet Kamble
Artificial Intelligence and Data Science in Food Processing Industry
Digital transformations and industrial automation help improve productivity and operational efficiency at a mass scale without compromising quality and consistency in the food processing industry. This chapter discusses how artificial intelligence (AI) can effectively enhance food hygiene, safety and quality, efficient production and supply chain by efficient decision-making, food waste management, and smart sorting and packaging solution through economic resource utilization by reducing errors and saving capital investments. The convergence of data science and AI can further improve the delivery of items at food outlets, boosting on-demand production and predicting sales performance through algorithms. It can drastically improve shelf life, packaging, food safety with a more translucent supply chain, and quality control by identifying customer needs. Automation in the food industry will monitor each processing stage and thus improve its scale-up, inventory predictions, and supply chain stream. This helps in cost reduction, improved accuracy, and time-saving in a large-scale operation.
Mohit Malik, Vijay Kumar Gahlawat, Rahul S. Mor, Shekhar Agnihotri, Anupama Panghal, Kumar Rahul, Neela Emanuel
Industry 4.0-Based Agritech Adoption in Farmer Producer Organization: Case Study Approach
The advent of the Fourth Industrial Revolution has transformed several sectors. Several technologies related to information technology have helped in increasing productivity. Agriculture has also been impacted by agritech. However, agritech has its individual and organizational applications. FPO as an organizational form has changed the nature of business of agriculture. The objective of this study was to find if agritech and FPO are synergistic. Specifically, through a case research methodology, this research was focused on whether FPOs facilitated agritech adoption. Using a dairy tech firm and interviews with dairy FPO, it was found that nature of diffusion depends on several innovation adoption characteristics and the factors that facilitate it. The study suggested working on these eight dimensions to achieve greater synergy between FPOs and agritech.
C. Ganeshkumar, A. Sivakumar, B. Venugopal
Digital Transformation and Industry 4.0 for Sustainable Supply Chain Performance
Sachin S. Kamble
Rahul S. Mor
Amine Belhadi
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