Skip to main content

About this book

This book gathers the proceedings of the 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing (AMP 2020), held in Belgrade, Serbia, on 1–4 June 2020. The event marks the latest in a series of high-level conferences that bring together experts from academia and industry to exchange knowledge, ideas, experiences, research findings, and information in the field of manufacturing. The book addresses a wide range of topics, including: design of smart and intelligent products, developments in CAD/CAM technologies, rapid prototyping and reverse engineering, multistage manufacturing processes, manufacturing automation in the Industry 4.0 model, cloud-based products, and cyber-physical and reconfigurable manufacturing systems. By providing updates on key issues and highlighting recent advances in manufacturing engineering and technologies, the book supports the transfer of vital knowledge to the next generation of academics and practitioners. Further, it will appeal to anyone working or conducting research in this rapidly evolving field.

Table of Contents


An Adaptive Scheduling Method Based on Cloud Technology: A Structural Steelwork Industry Case Study

Decision making at the shop floor level has become more complex than ever before due to the massive growth in available data. The increasing market demands, concerning product quality and delivery times, make critical judgement and decision-making crucial requirements of the modern manufacturing problems. Human decision making has become insufficient and struggles to achieve manufacturing goals. Cutting edge technologies like the Internet of Things (IoT) and Cyber Physical Systems (CPS), that are the cornerstones of the Industry 4.0 smart factories, can contribute to efficient decision making. Therefore, more accurate and improved critical decisions can be achieved for the current as well as for the future status of a manufacturing system. Furthermore, production scheduling is one of the main issues that engineers have to address. The decision support tools of the Industry 4.0 era contribute to effective production scheduling, while considering a larger amount of data and constraints than ever before. This research work proposes a production scheduling method, that uses past and near real-time data to check resource and task status, providing insight to production engineers and enabling enhanced decision making. The results are validated in a structural steelwork industry shop case study.
Dimitris Mourtzis, Antonis Gargallis, John Angelopoulos, Nikos Panopoulos

Overview of Human-Robot Collaboration in Manufacturing

Human-robot collaboration (HRC) in the manufacturing context aims to realise a shared workspace where humans can work side by side with robots in close proximity. In human-robot collaborative manufacturing, robots are required to adapt to human behaviours by dynamically changing their pre-planned tasks. However, the robots used today controlled by rigid native codes can no longer support effective human-robot collaboration. To address such challenges, programming-free and multimodal communication and control methods have been actively explored to facilitate the robust human-robot collaborative manufacturing. They can be applied as the solutions to the needs of the increased flexibility and adaptability, as well as higher effort on the conventional (re)programing of robots. These high-level multimodal commands include gesture and posture recognition, voice processing and sensorless haptic interaction for intuitive HRC in local and remote collaboration. Within the context, this paper presents an overview of HRC in manufacturing. Future research directions are also highlighted.
Lihui Wang, Sichao Liu, Hongyi Liu, Xi Vincent Wang

A Bending Test of the Additively Produced Porous Sample

With Industry 4.0, additive-manufacturing methods will be widely used to produce small batches of customized products that offer construction advantages, such as complex, lightweight designs. One type of products that belong to the sophisticated components, producible by 3D printing technology, is a lattice structure. The article deals with the three points bending test of the cylindrical samples. FDM (Fused Deposition modelling) technique and ABS (Acrylonitrile Butadiene Styrene) material were selected for the samples production. Two types of samples (with a simple lattice structure and fully filled by material) were analyzed experimentally and numerically. The results showed that in spite of the material saving at the porous structure production, the lattice structure with body-centred cube cell is not very suitable for the components loaded by bending, because a unit of material at this type of sample is able to carry down less stress compared to the sample fully filled by the material.
Katarina Monkova, Peter Pavol Monka, Jozef Tkac, Jan Vanca

Assessing Industry 4.0 Readiness in Manufacturing Companies from Serbia

Industry 4.0 has become a global programme of scientific and technological development, which covers all economic activities of today. The most developed countries have adopted their own programmes and they implement them for Industry 4.0. Our country is also intensively working on this Programme. This paper presents a model for assessing maturity and readiness of manufacturing organizations (industry branches) to operate and implement the Project I4.0 in their environment.
Vidosav D. Majstorović, Radivoje M. Mitrović, Žarko Z. Mišković

The Importance of CT in Industry 4.0 by Supplying Quality and GPS Standards for Several Production Methods Such as Additive Manufacturing

Today Industry 4.0 is spreading from developed countries into other developing economies even to small and medium sized enterprises. With a strong infrastructure and fast connection between components of the whole factory, Industry 4.0 will introduce innovations and a more robust, reliable and sustainable production. While Industry 4.0 is having several fundamental technology additive manufacturing has been playing an important role and takes part in today’s Industry 4.0 technology, prominently for automotive vehicle producers. Additive manufacturing has many advantages and tasks such as in reverse engineering, by defect prediction or producing complex shaped parts. Its vitality becomes more important when its implementation is combined with the most recent measurement technology ‘Computer Tomography’. CT can detect complex surfaces or inner structure with X-Ray usage which helps to additive manufacturing parts by inspection which can not be provided by a CMM in similar manner. That study presents a simple sample for the combination of these two technologies. Followingly, voids and GPS analyses after CT measurements of several parts will be introduced. Also, those CT inspections will give an example for a definite stage of Industry 4.0. In conclusion, a brief investigation of those innovative most recent technologies, which are developing in a continuous manner, will be made in the context of Industry 4.0 according to inspection results.
Cem Yurci, Numan M. Durakbasa

Challenges for Uncertainty Determination in Dimensional Metrology Put by Industry 4.0 Revolution

The paper presents the most important challenges for uncertainty determination in dimensional metrology caused by the recent changes in manufacturing and production engineering related to fourth industrial revolution. Current trends in dimensional metrology are described and gaps in the state of art in measurement uncertainty determination are identified. Some propositions on how to fill this gaps are also given. The main finding of the paper is that simulation methods for uncertainty determination based on usage of numerical models of measurement and/or manufacturing processes seem to be the most promising in uncertainty determination for in-process and in-line/in-situ measurement systems and for modern measuring devices like industrial computed tomography systems.
Adam Gąska, Jerzy Sładek, Piotr Gąska

Cognitive Twins for Supporting Decision-Makings of Internet of Things Systems

Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stake holders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoT-based systems development than DT.
Jinzhi Lu, Xiaochen Zheng, Ali Gharaei, Kostas Kalaboukas, Dimitris Kiritsis

Similarity Based Methodology for Industrial Signal Recovery

The tremendous amount of data generated in the industry provides a massive opportunity to mine that data for decisions, such as prediction of outgoing product quality, process monitoring, etc. In addition, unlike computer and social networks, in the industrial data, the information is not directly observable and is embedded in the signals emitted during the corresponding processes, etc. However, in many cases and for many reasons these sensor signatures are not properly received at the very source causing missing segments in the signal sets. On the other hand, in many manufacturing facilities, large amounts of historical records of past sensor readings are available and can be used to enhance and reinforce the signal recovery process. In this paper, we propose the so-called match matrix methodology which uses signal similarity metrics to regenerate the missing segments in a signal from historical signal records. Three different incomplete signal set situations are simulated using a large dataset from a modern semiconductor manufacturing fab. The proposed method is validated utilizing the dataset and the results demonstrated a high fidelity in signal recovery in the all three cases.
Ramin Sabbagh, Alec Stothert, Dragan Djurdjanovic

Closed-Loop Control by Laser Power Modulation in Direct Energy Deposition Additive Manufacturing

Direct Energy Deposition is a metal additive manufacturing technique that has raised great interest in industry thanks to its potential to realize complex parts or repairing damaged ones, but the complexity of this process still requires much effort from practitioners to achieve functionally sound parts. One of the recurring flaws of such parts is the phenomenon of over-deposition, which may occur due to unpredicted local increases of energy density.
The deposition of uniform metal tracks is critical in many practical cases, when parts are composed by a significant number of layers and/or when complex tool paths induce heat build-up, for example in thin structures. Therefore, detecting anomalies such as over-growth in real-time and dynamically correcting them is of paramount importance for achieving repeatable, first-time-right parts.
This work studies the use of a closed-loop control system for Direct Energy Deposition, proposing to adjust on-line the power of the laser beam according to the feedback provided by the analysis of melt pool images. The images are acquired by a camera, mounted coaxially into the optical chain of the deposition head, which records images at 100 fps while the process is running. The proposed approach is explored experimentally by comparing the over-deposition measured on sample test geometries obtained with a traditional feed-forward approach with the over-deposition obtained through the developed closed-loop control laser deposition system.
Stefano Baraldo, Ambra Vandone, Anna Valente, Emanuele Carpanzano

Manufacturing Process Monitoring and Control in Industry 4.0

The use of advanced process planning methodologies has enabled manufacturers to predict and optimize manufacturing processes in the planning stage. However, process faults and non-optimal conditions are always inherent to the manufacturing environment. The advent of Industry 4.0 has given rise to cyber-physical systems wherein online process monitoring and control can be performed autonomously. This paper discusses process monitoring and control in the context of Industry 4.0. With the focus on digital connectivity driving Industry 4.0, the advantages of cloud-based computing and knowledge inferred from a plethora of manufacturing processes can be leveraged for process monitoring and control to improve production speed, quality, and reliability. This paper presents a holistic framework for process monitoring and control in the context of Industry 4.0, where macro-level process control is conducted in the cloud and device-level process control occurs at the edge. A case study of tool life enhancement using such a framework is presented. Limitations of process monitoring and control in the context of Industry 4.0 are discussed along with proposals for new avenues of research.
Vinh Nguyen, Shreyes N. Melkote

On Standardization Efforts for Additive Manufacturing

Additive manufacturing is a set of technologies potentially covering the needs of many industrial sectors, some of which require the certification of the final product. This is the main motivation explaining why the International Organization for Standardization (ISO) and the American Society for Testing and Materials (ASTM) are putting significant efforts into defining standards covering different topics in this area. Efforts that very soon have become joint efforts to rapidly realize common standards under the name of ISO/ASTM standards. In this paper, the state of the art of these efforts is presented and discussed.
Giovanni Moroni, Stefano Petrò, Huan Shao

Artefacts Used for Testing 3D Optical-Based Scanners

Performance verification of 3D optical based scanners is currently a topic of great discussion, since they are ever more used in the industrial manufacturing field for the dimensional verification of components. Among their advantages, there is the capability of acquire large amounts of points in a very short time, regardless the geometrical complexity of the object under measurement. Although, traceability is still critical and the uncertainty assessment conducted using artefacts calibrated through the more traceable Coordinate Measuring Machines (CMMs), is still the most implemented method. In this paper, some of the most interesting geometries used for the performance verification of optical based scanners have been reported, considering the most widespread measuring tasks which require the use of these instruments, both prismatic geometries and freeform shapes.
Maria Grazia Guerra, Fulvio Lavecchia, Luigi Maria Galantucci

An Approach of Development Smart Manufacturing Metrology Model as Support Industry 4.0

The framework for smart manufacturing metrology model (S3M), are based on integration of digital product metrology information through metrological identification, application artificial intelligence techniques and generation of global/local inspection plan for coordinate measuring machine (CMM). S3M has an extremely expressed requirement for better control, monitoring and data mining. Limitations still exist in data storages, networks and computers, as well as in the tools for complex data analysis, detection of its structure and retrieval of useful information. This paper will present recent results of our research on building of S3M as support Industry 4.0. Presented approach to S3M development includes four levels: (i) mathematical model of the measuring sensor path, which establishes a connection between the coordinate systems; (ii) generating the needed set of information to integrate the given tolerances and geometry of the parts by applying an ontological knowledge base; (iii) the application of AI techniques such as ACO and GA to optimize the measurement path, numbers of measuring part setup and configuration of the measuring probes; (iv) simulation of measurement path for a collision check. After simulation of the measurement path and visual checks of collisions, the path sequences are generated in the control data list for appropriate CMM. The experiment was successfully carried out on the examples of prismatic part and two turbine blades or its free-form measuring surfaces.
Slavenko M. Stojadinović, Vidosav D. Majstorović, Dragan Djurdjanović, Srdjan Živković

Intelligent Process Planning for Smart Factory and Smart Manufacturing

The goal of the Industry 4.0 is the Smart factory which provides flexible and adaptive production processes in complex production conditions. Smart factory is a solution for manufacturing conditions that have hyper-dynamic character and are rapidly changing. The automation and constant optimization of production are inevitable and enable maximal utilization of workforce and production resources. The main task of technologies and services within the Smart factory is the implementation of artificial intelligence in all aspects of production. In this way, the smart manufacturing is achieved where the tasks are focused on finding optimal solutions in the preparation of production as well as the prediction of errors before they occur in production stages. Smart manufacturing relies on the concept of Cloud manufacturing in which different services are based on artificial intelligence. Smart services utilize various intelligent tools such as nature-inspired metaheuristics, search algorithms whose implementation in manufacturing has grown in the recent period. In this paper, three modern nature-inspired metaheuristic algorithms will be briefly introduced as an efficient tool in intelligent process planning optimization and their performance will be presented on three experimental studies.
Mijodrag Milošević, Mića Đurđev, Dejan Lukić, Aco Antić, Nicolae Ungureanu

Model-Based Manufacturing System Supported by Virtual Technologies in an Industry 4.0 Context

Industry 4.0 concept of the new industrial revolution is based on the application of front-end and base technologies for producing digital solutions. Converging Smart Manufacturing and Smart Products with Big Data and Analytics plays a central role in implementing the I4.0 concept in today’s industry. This paper presents the virtual components of the proposed Model-based Manufacturing System and their role in the I4.0 context. Two different industrial cases demonstrate the application and benefits of the MBM approach, which integrates virtual and rapid technologies for the design, analysis and validation of a product and its fabrication processes of sheet metal forming and forging.
Vesna Mandic

New Trends in Machine Design Within Industry 4.0 Framework

The basic framework of the Industry 4.0 as an approach and philosophy implies the introduction of new procedures and principles, as well as the development and improvement of machine systems towards the introduction of a high level of manufacturing digitalization. In order to meet the achievements of Industry 4.0, very significant changes are also required in the design, monitoring and maintenance phases of machinery. Therefore, all the research and advancements in the field of calculation and design of machine elements and assemblies have to be observed within the paradigm of Industry 4.0. This paper outlines the main research tasks and aims within the determination of basic principles and methods for suiting and improving machine elements and systems in the context of the requirements of the Industry 4.0. Also, the part of the paper gives the description of the new improved methodology and systems for monitoring the parameters of rolling bearings during their operation, which would significantly contribute to the prediction of the possible failure of the rolling bearings and lead to important savings. The developed methodology is a sample for new trends in the context of the vision of Industry 4.0 machinery and respects the requirements for safety, energy efficiency and reliability.
Radivoje M. Mitrović, Ivana Atanasovska, Natasa Soldat, Zarko Miskovic

A Cloud Computing Model for Achieving Competitiveness of Domestic Enterprises

Amidst the globalization of markets and within the framework of the fourth industrial revolution - Industry 4.0, domestic enterprises face challenges when it comes to business and market performance. Domestic enterprises lack necessary productivity and product quality in order to compete on the global market. In this paper cloud computing solutions in various industries are analyzed. The goal is to develop a cloud computing model for improving the competitive ability of domestic enterprises. The model integrates several cloud-based solutions and takes into consideration the business metrics of domestic enterprises. Furthermore, future trends in cloud computing advances and its application are discussed. The paper also presents suggestions and guidelines for improving competitiveness of domestic enterprises through the application of cloud computing solutions. The results of this study significantly contribute to the existing body of literature and provide a solid basis for future research in the domain of cloud computing application in industries in developing countries.
Dejan Đorđević, Dragan Ćoćkalo, Mihalj Bakator, Srđan Bogetić, Miloš Vorkapić, Cariša Bešić

Strategic Approach for Robotics Development in SME by Value Linkage Concept

Small and Medium Enterprises (SME) in Japan has been facing the difficulties of global competition caused by manufacturing commoditization as well as by collapsing affiliation system known as “Keiretsu”. Effective measure for this SME issue would be regarded as potential remedy not only for Japan but also for other countries including Germany and Serbia because of their high percentage of SME ratio in industries.
This study attempts to make positive effects on the said issue by providing the new perspectives for SME to obtain driving force to create a survival path with utilizing digital technologies. This approach also covers robotics industries which has strong possibilities for SME to strengthen the basis for versatile growth and to facilitate SME to implement Industry 4.0.
Hideaki Hohnoki

Big Data Analysis as a Digital Service: Evidence Form Manufacturing Firms

Digital disruption is propelling manufacturers to move on towards digital transformation and deliver digital services based on predictive analytics. The literature agrees that digital technologies (i.e. big data) facilitate the service innovation of manufacturers by creating digital servitization. However, little research has specifically focused on the empirical data that analyze use of digital technologies in manufacturing firms in terms of technological intensity. The present study investigates the interaction between big data analysis, as a digital service, and firm characteristics (i.e. firm size and technological intensity). Our analysis used the Serbian dataset of 240 manufacturing firms from the European Manufacturing Survey conducted in 2018. The empirical results show that, in manufacturing firms, digital service based on predictive analytics is highly utilized in medium size firms. Furthermore, results indicate that high technology manufacturing firms in Serbia are not yet utilizing digital technologies to facilitate the service innovation in comparison to other innovation intensity characteristics.
Bojan Lalic, Ugljesa Marjanovic, Slavko Rakic, Marko Pavlovic, Tanja Todorovic, Nenad Medic

Abrasive Flow Machining of 3D Printed Metal Parts – A Scientific Review with Extension on Industrial Needs

Nowadays, the use of additive technologies is increasing. Despite the exceptional capability to produce complex geometries, additive technologies are unable to produce components or functional surfaces within tight tolerances and integrity demands. With other words, “as build” surface qualities are poorer in comparison to a conventional machined surfaces. Therefore, components have to be post-machined. Lately, abrasive flow machining (AFM) is offering improvements in such cases. However, many process parameters, e.g. abrasive media property, temperature, velocity, etc. influencing the performance of AFM and their understanding is crucial for successful implementation of AFM into the industrial applications. This paper presents critical scientific review of AFM, with an emphasis on post-machining of 3D printed metal parts.
Luka Kastelic, Davorin Kramar, Franci Pušavec

Rejuvenation of Business Management Tools in Industry 4.0

The world of business economics (and management) traditionally has been viewed as relatively linear. In such context, competitive dynamics depends on contingency between structural factors and contextual factors, as well as characteristics of a representative company. But, the context has been changed under the impact of Industry 4.0. By synthesizing the breakthroughs from cyber and physical (and/or biological) worlds, it gave rise to an almost endless stream of combinatorial innovations. There are two major consequences of the previous transition. First, universal connectivity as the new free good enables that the world of engineering reaches the levels of complexity and dynamism typical for non-linear systems. Second, emerging amalgams of cyber and physical breakthroughs trigger in business management transformation of linear value chain into exponential value chain (or platform), actually a non-linear system. Mentioned structural changes lead to convergence of the engineering and business management in conceptual terms. In this paper we explore the ways in which Industry 4.0 can offer a powerful and consistent platform for implementation of conventional business management tools. We have been inspired by two achievements. First, to map out the impact of Industry 4.0 on double paradigm change, both in macro and micro (or business) management. Second, to explore, with key details, the impact of the paradigm change in business management on effectiveness of conventional management tools. By doing this, we wish to promote the broader and systemic thinking, synthesizing micro and macro management perspectives into a single point of view that is actually based on the reversibility principle.
Dragan Đuričin, Iva Vuksanović Herceg

Influence of the Orientation of Steel Parts Produced by DMLS on the Fatigue Behaviour

The goal of this paper is to present studies of the influence of orientation of steel samples during additive manufacturing to their fatigue behaviour. The samples were produced from maraging steel EOS MS1 and stainless steel EOS PH1 using direct laser metal sintering technology. Three sets of samples were manufactured for each of the materials, with slopes of longitudinal axis of the samples being 0° (horizontal), 45° (slanted) and 90° (vertical) with respect to the horizontal building plane. All the samples were post-processed by heat treatment, shot-peening and machining, and tested according to the ISO 1143 standard. The curves for finite life domain were calculated using ISO 12107, and an estimation of the fatigue limit was made by Dixon-Mood method. The obtained results show that the building orientation has no significant influence on fatigue strength of maraging steel samples, while the stainless steel samples with slanted orientation of the axis have fatigue strength of up to 20% higher than the samples with horizontal or vertical orientation of the axis.
Nebojša Bogojević, Snežana Ćirić-Kostić, Aleksandar Vranić, Giorgio Olmi, Dario Croccolo

New ISO Geometrical Product Specification Standards as a Response to Industry 4.0 Needs

The task of international standardization to provide design, manufacturing and quality assurance teams the specification tools based on clear and unambiguous rules is discussed. The current state in implementation of the ISO/TC 213 new approach to develop complete set of rule based standards in the field of geometrical tolerancing is analysed. It is mentioned that fourth edition of the ISO 1101 standard that establish fundamentals for geometrical tolerancing is still case based standard without directly listed rules that make this standard difficult for digital utilization. Proposal of rewriting clause from the ISO 1101 in the rule based way is given. The currently available ISO GPS standards that are rule based are listed and shortly reviewed.
Zbigniew Humienny

Multi-modal Multi-agent Path Finding with Optimal Resource Utilization

The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other. We study a general version of MAPF, called mMAPF, that involves further challenges, such as multi-modal transportation modes, a set of waypoints to visit for each agent, and consumption of different types of resources. We introduce a declarative method to solve mMAPF, using answer set programming that provides a flexible formal framework to address all these challenges while optimizing multiple objectives.
Aysu Bogatarkan, Esra Erdem, Alexander Kleiner, Volkan Patoglu

The Effects of Milling and Drilling Process Parameters and Different Tool Path Strategies on the Quality of the CFRP Composites

Carbon fiber reinforced plastic (CFRP) composites are being used at a greater scale which is increasing the demands on automated production to improve productivity. These types of materials can be stronger than steel, about 40% lighter than aluminium, up to 80% lighter than steel and as stiff as titanium. Composite materials represent a good alternative to engineering materials, providing several important advantages in comparison to conventional materials, such as: light weight, mechanical and chemical resistance, low maintenance costs, high specific strength, higher stiffness and temperature stability, allowance of free forms modelling and specific design. Surface roughness evaluation is very important for many fundamental problems such as friction, contact deformation, heat and electric current conduction, tightness of contact joints and positional accuracy. For this reason, surface roughness, has been the subject of experimental and theoretical investigations for many decades. Also, surface roughness imposes one of the most critical constrains for the selection of machines and cutting parameters in process planning. In order to economically machine these materials with high part qualities, improvements in machining strategies must be made. This chapter presents the researches regarding different milling and drilling strategies in order to determine the best quality of the finished product. Flatness, parallelism, cylindricity, roughness and dimensional tolerances were measured using 3D CMM and the results were analysed using the Design Expert software.
Grigore Marian Pop, Emilia Campean, Liviu Adrian Crisan, Mihai Tripa

Industry 4.0 in Croatia – Perspective and Industrial Familiarity with the (New) Digital Concept

The impact of Industry 4.0, almost ten years after its introduction to industry and science, has encouraged the manufacturers to change their working environment, offer customized products and change the mind-set on the organizational level. In Croatia, so far there are only few examples its partial implementation in the industrial practice. That is why in this paper the overview of the current research about Industry 4.0 in Croatia previously conducted and companies’ readiness is given, as well as the results of the new research regarding the familiarity of the local industry with the new concept. The flaws of the current implementation procedure will be recognized and strategic guidance for the future steps will be given. Also, the importance of the local support from the various institutions, like government or universities, will be considered with the definition of their role during the transformational digitization process.
Maja Trstenjak, Tihomir Opetuk, Danijel Pavković, Davor Zorc


Additional information

Premium Partner

    Image Credits