Editors

Dominik T. Matt, Vladimír Modrák and Helmut Zsifkovits

Industry 4.0 for SMEs

Challenges, Opportunities and Requirements

Editors

Dominik T. Matt

Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy

Vladimír Modrák

Department of Manufacturing Management, Technical University of Košice, Prešov, Slovakia

Helmut Zsifkovits

Chair of Industrial Logistics, Montanuniversität Leoben, Leoben, Austria

ISBN 978-3-030-25424-7e-ISBN 978-3-030-25425-4

https://doi.org/10.1007/978-3-030-25425-4

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Preface

The term Industry 4.0 describes the ongoing revolution of manufacturing industry around the world. Large companies in particular have rapidly embraced the challenges of Industry 4.0 and are currently working intensively on the introduction of the corresponding enabling technologies. Small- and medium-sized enterprises (SMEs) face the hurdle of possessing neither human nor financial resources to systematically investigate the potential and risks for introducing Industry 4.0. However, in most of the countries SMEs form the backbone of the economy, they account for the largest share of the gross domestic product and are also important employers. In this respect, the challenges, opportunities, and requirements of Industry 4.0 have to be examined specifically for SMEs, thus paving the way for the digital transformation of traditional SMEs into smart factories.

The central question in this book is therefore: Which opportunities arise from Industry 4.0, which challenges do SMEs face when introducing Industry 4.0, and which requirements are necessary for a successful and sustainable digital transformation of their company?

With this book the research consortium of the H2020 MSCA RISE project “SME 4.0—Industry 4.0 for SMEs” (grant agreement No. 734713) encourages other researchers to conduct research in the field of Industry 4.0 specifically for SMEs and thus expanding the community in SME research. Practical methods, instruments, and best practice case studies are needed to support practitioners from SMEs in the introduction of Industry 4.0.

This book summarizes the research results of the first phase of the project “SME 4.0—Industry 4.0 for SMEs: Smart Manufacturing and Logistics for SMEs in an X-to-order and Mass Customization Environment,” which was conducted from 2017 to 2018. The project, started in January 2017 with a duration of four years and is funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 734713.

In this initial book, that is being published within the framework of the above-mentioned research project, the editors and contributors focus their research results on possible challenges, opportunities, and requirements that arise from the introduction of Industry 4.0. A further book publication is planned for the final phase with the focus on research of methods for the introduction of Industry 4.0 to SMEs in addition to practical applications in SMEs.

A great opportunity for the future lies in the transfer of Industry 4.0 expertise and technologies in Small- and Medium-sized Enterprises (SMEs). This research project aims to close and overcome the gap in this transfer through the establishment of an international and interdisciplinary research network for this topic. This network has the objectives of identifying the requirements, the challenges, and the opportunities for a smart and intelligent SME factory, creating adapted concepts, instruments, and technical solutions for production and logistics systems in SMEs and developing suitable organisation and management models. The practical applicability of the results is guaranteed through a close collaboration of the network with small- and medium-sized enterprises from Europe, USA, Thailand, and India.

The book is structured into five parts with a total of 13 chapters:

Part I—Introduction to Industry 4.0 for SMEs

In the first part readers are introduced to the topic by reviewing the current state of the art of the transfer of Industry 4.0 in SMEs and the role of SMEs in the digital transformation.

Part II—Industry 4.0 Concepts for Smart Manufacturing in SMEs

In the second part the focus lies on manufacturing in SMEs. The first chapter in this part describes the main requirements, constraints, and guidelines for the design of smart and highly adaptable manufacturing systems. The second chapter reports how SMEs can implement an industrial internet of things and cyber-physical systems for achieving distributed and service-oriented control of their manufacturing system. The third chapter provides insights about potentials and challenges of automation through safe and ergonomic human–robot collaboration.

Part III—Industry 4.0 Concepts for Smart Logistics in SMEs

The third part concentrates on the introduction of Industry 4.0 in SME logistics. In the first chapter, requirements for the design of smart logistics in SMEs are summarized, while the second chapter shows how SMEs can implement identification and traceability of objects to enable automation. The third chapter gives an overview of the state of the art of the application and the potential of automation in logistics.

Part IV—Industry 4.0 Managerial, Organizational and Implementation Issues

The fourth part deals with organization and management models for smart SMEs. In the first chapter in this part, the contributors develop and test organizational models for smart SMEs in terms of mass customization. In the second chapter, a focus group study shows the main barriers that SMEs are facing when implementing Industry 4.0. As SMEs need to be guided and supported in the process of implementation of Industry 4.0, the third chapter provides an SME 4.0 implementation tool kit.

Part V—Case Studies and Methodical Tools for Implementing Industry 4.0 in SMEs

In this part, topics previously covered theoretically are described by means of practical case studies. The case studies describe both the underlying theoretical concepts as well as the practical implementation and validation in the laboratory environment. In the first chapter, the contributors report about a case study of automatic product identification and inspection by using tools of Industry 4.0. In the second chapter, readers can expect a laboratory case study for intuitive collaboration between man and machine in SME assembly.

In the third chapter we give an overview on Axiomatic Design as a design methodology pertinent to the introduction of Industry 4.0 to SMEs as this method can be found within some chapters of this book. This chapter explains the basic rules of Axiomatic Design: the different domains and levels used in Axiomatic Design, the independence axiom and the information axiom. Further, this chapter introduces how Axiomatic Design can be used for the design of complex systems including both products and manufacturing systems.

We would like to thank the authors for their refreshing ideas and interesting contributions to this topic.

Dominik T. Matt

Vladimír Modrák

Helmut Zsifkovits

Bolzano, ItalyKošice, SlovakiaLeoben, Austria

May 2019

This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 734713 (Project title: SME 4.0—Industry 4.0 for SMEs).

Contents

Part I Introduction to Industry 4.0 for SMEs

1 SME 4.​0:​ The Role of Small- and Medium-Sized Enterprises in the Digital Transformation 3

Dominik T. Matt and Erwin Rauch

Part II Industry 4.0 Concepts for Smart Manufacturing in SMEs

2 SME Requirements and Guidelines for the Design of Smart and Highly Adaptable Manufacturing Systems 39

Erwin Rauch, Andrew R. Vickery, Christopher A. Brown and Dominik T. Matt

3 Implementation of Industrial Internet of Things and Cyber-Physical Systems in SMEs for Distributed and Service-Oriented Control 73

Rafael A. Rojas and Manuel A. Ruiz Garcia

4 The Opportunities and Challenges of SME Manufacturing Automation:​ Safety and Ergonomics in Human–Robot Collaboration 105

Luca Gualtieri, Ilaria Palomba, Erich J. Wehrle and Renato Vidoni

Part III Industry 4.0 Concepts for Smart Logistics in SMEs

5 Requirement Analysis for the Design of Smart Logistics in SMEs 147

Patrick Dallasega, Manuel Woschank, Helmut Zsifkovits, Korrakot Tippayawong and Christopher A. Brown

6 Consistent Identification and Traceability of Objects as an Enabler for Automation in the Steel Processing Industry 163

Helmut Zsifkovits, Johannes Kapeller, Hermann Reiter, Christian Weichbold and Manuel Woschank

7 State-of-the-Art Analysis of the Usage and Potential of Automation in Logistics 193

Helmut Zsifkovits, Manuel Woschank, Sakgasem Ramingwong and Warisa Wisittipanich

Part IV Industry 4.0 Managerial, Organizational and Implementation Issues

8 Development of an Organizational Maturity Model in Terms of Mass Customization 215

Vladimír Modrák and Zuzana Šoltysová

9 Implementing Industry 4.​0 in SMEs:​ A Focus Group Study on Organizational Requirements 251

Guido Orzes, Robert Poklemba and Walter T. Towner

10 Smart SME 4.​0 Implementation Toolkit 279

Apichat Sopadang, Nilubon Chonsawat and Sakgasem Ramingwong

Part V Case Studies and Methodical Tools for Implementing Industry 4.0 in SMEs

11 The Digitization of Quality Control Operations with Cloud Platform Computing Technologies 305

Kamil Židek, Vladimír Modrák, Ján Pitel and Zuzana Šoltysová

12 Implementation of a Laboratory Case Study for Intuitive Collaboration Between Man and Machine in SME Assembly 335

Luca Gualtieri, Rafael A. Rojas, Manuel A. Ruiz Garcia, Erwin Rauch and Renato Vidoni

13 Axiomatic Design for Products, Processes, and Systems 383

Christopher A. Brown

Index 403

List of Figures

Fig. 1.1 The four industrial revolutions (Adapted from Kagermann et al. 2013)7

 

Fig. 1.2 European beneficiaries and international partner organizations in the project (Source of the map www.​d-maps.​com ) 21

 

Fig. 1.3 Research fields and topics in the SME 4.0 project23

 

Fig. 1.4 Work packages, tasks, and project phases24

 

Fig. 2.1 Explorative field study through SME workshops (Map reproduced from D-maps.com: https://​d-maps.​com/​carte.​php?​num_​car=​3267&​lang=​en ) 48

 

Fig. 2.2 Axiomatic Design based methodology for the analysis of SME requirements and design guidelines for smart manufacturing49

 

Fig. 2.3 AD approach to deduce design parameters for smart manufacturing in SMEs62

 

Fig. 3.1 The OSI model75

 

Fig. 3.2 Relation between the layered architecture of CPS and the OSI model77

 

Fig. 3.3 The drivers of the integration87

 

Fig. 3.4 The three-tier architecture92

 

Fig. 3.5 Sketch of the mini-factory network (Reproduced with permission from Smart Mini Factory Lab, unibz)94

 

Fig. 4.1 Relationship between hazard, risk, and potential consequence108

 

Fig. 4.2 Main standards hierarchy related to industrial collaborative robotics (*Mandatory for European Union nations)115

 

Fig. 4.3 Common human–robot contact variables and condition (Source Adapted from Vicentini 2017) 118

 

Fig. 4.4 Human–robot contact classification (Source Adapted from Vicentini 2017) 120

 

Fig. 4.5 Potential and challenges in safety and ergonomics (S&E) in HRC: research areas129

 

Fig. 4.6 SLR workflow130

 

Fig. 4.7 Comparison between contact avoidance and contact detection and mitigation categories132

 

Fig. 4.8 Comparison of leading technological research areas of interest according to a preliminary SLR133

 

Fig. 6.1 Bar code structure (Source Adapted from Zsifkovits 2013) 168

 

Fig. 6.2 Upstream and downstream traceability (Source Adapted from Yuan et al. 2011) 173

 

Fig. 6.3 Traceability before and within the production process (Lichtenberger 2016)175

 

Fig. 6.4 Compressed view on traceability database (Reiter 2017)176

 

Fig. 6.5 Data flow in the supply chain181

 

Fig. 6.6 Adaptive quality control182

 

Fig. 6.7 Concept I—bar code and laser marker184

 

Fig. 6.8 Concept II—color marking185

 

Fig. 6.9 Concept III—modification of the cooling bed186

 

Fig. 6.10 Concept IV—Schematic illustration188

 

Fig. 7.1 Picking processes by using augmented reality devices (Reproduced with permission from University of Leoben, Chair of Industrial Logistics)202

 

Fig. 7.2 Example of delivered goods (DG) (Reproduced with permission from University of Chiang Mai, Department of Industrial Engineering)203

 

Fig. 7.3 Cross-docking operation204

 

Fig. 7.4 Truck Loading/unloading conveyor systems (Reproduced with permission from University of Chiang Mai, Department of Industrial Engineering)205

 

Fig. 7.5 Cross belt sorter (Reproduced with permission from University of Chiang Mai, Department of Industrial Engineering)206

 

Fig. 7.6 Improved cross-docking operation207

 

Fig. 8.1 Frequency distribution of the progress levels used in the reviewed MMs224

 

Fig. 8.2 Categorization of subjects of interest based on their appearance in the I4.0 MMs225

 

Fig. 8.3 Research methodological framework228

 

Fig. 8.4 Results from mapping of individual requirements229

 

Fig. 8.5 Spider graph of differences between current states and future targets231

 

Fig. 8.6 I4.0 RMM of organizational capabilities for mass customized manufacturing234

 

Fig. 8.7 Model of the relations between orders and manufacturing operations239

 

Fig. 10.1 Organization management scope281

 

Fig. 10.2 Information technology factors282

 

Fig. 10.3 Production and operations factors284

 

Fig. 10.4 Automation factors286

 

Fig. 10.5 Information technology factors288

 

Fig. 10.6 SMEs 4.0 toolkit framework290

 

Fig. 10.7 Smart SMEs 4.0 implementation toolkit methodology291

 

Fig. 10.8 Phases of smart SMEs 4.0 implementation toolkit292

 

Fig. 10.9 Developed mobile application for coffee shop (Reproduced with permission from Chiang Mai University, Department of Industrial Engineering)297

 

Fig. 11.1 The scheme of quality control digitization312

 

Fig. 11.2 The block diagram data of digitization with Cloud Platform and digital twin312

 

Fig. 11.3 Pictures of subassembly products (top left), 3D digital twin of the product (top right), 3D digital model in exploded view (bottom left), the list of the subassembly product components (bottom right)314

 

Fig. 11.4 The pictures of the fixture and quality control objects (left), along with their 3D model (right)315

 

Fig. 11.5 Vision system Omron (left), calibration of the recognition area (middle), detection of surface errors (right)316

 

Fig. 11.6 Dimension control of assembly elements (top), measured data interpretation from the Cognex vision system 2 (bottom)317

 

Fig. 11.7 Calibration of the recognition area (left), parts presence control in the fixture along with graphical indication of missing part (right)317

 

Fig. 11.8 Verification of the end item completeness by Sick Inspector I10318

 

Fig. 11.9 RFID gate (left), RFID tag implementation into the assembling parts and the fixture (right)320

 

Fig. 11.10 The fixture and parts position detection by laser sensor and incremental encoder for the parts position identification [x, y, z  ] (left), the fixture position detection by RFID and optical sensor (right) 321

 

Fig. 11.11 RFID antenna for the fixture with the end item (left) and RFID antenna for fixture with the parts (right)322

 

Fig. 11.12 Modified RFID tag data structure with EPC Gen2 (96 bit)322

 

Fig. 11.13 An example of RFID tag read value323

 

Fig. 11.14 OPC Server data from vision system (top left), MindSphere value list (top right), measurements timeline with alarm message example (bottom)325

 

Fig. 11.15 3D digital twin (left) and experimental inspection and identification system (right)326

 

Fig. 11.16 The scheme of bidirectional data synchronization between quality control system and digital twin326

 

Fig. 11.17 An example of 2D and 3D simulation in Tecnomatix plant simulator with OPC communication326

 

Fig. 11.18 Remote monitoring of inspection device by mobile phone (left) and by PC (right)327

 

Fig. 11.19 HTC Vive Pro (left), 3D model in plant simulator (middle), digital twin inspection in VR (right)327

 

Fig. 12.1 A collaborative robot (UR3 model) in a shared workspace (Source Smart Mini Factory, unibz [Reproduced with permission from Smart Mini Factory Lab, unibz]) 337

 

Fig. 12.2 Internal and external effects of the introduction of collaborative robots into existing production systems339

 

Fig. 12.3 General evaluation workflow and related priorities for the workstation transformation341

 

Fig. 12.4 Workflow for the evaluation of the technical possibility to use a collaborative robot for assembly activities345

 

Fig. 12.5 Overall combination of various evaluation analysis for human–robot task allocation348

 

Fig. 12.6 Manual assembly workstation for assembly of pneumatic cylinders (Figs. 12.​6 – 12.​11 reproduced with permission from Smart Mini Factory Lab, Unibz) 350

 

Fig. 12.7 Pneumatic cylinder (As for Figs. 12.​6 – 12.​11 the Fig. 12.7 is reproduced with permission from Smart Mini Factory Lab, Unibz) 351

 

Fig. 12.8 Robotiq collaborative gripper352

 

Fig. 12.9 Universal robot UR3 model353

 

Fig. 12.10 Pneumatic cylinder components354

 

Fig. 12.11 Pneumatic cylinder subassemblies355

 

Fig. 12.12 Pneumatic cylinder—manual assembly cycle357

 

Fig. 12.13 CV value of tasks which could potentially be performed by the robot from a technical point of view369

 

Fig. 13.1 Design domains, customer, functional, physical, and process, and the constraints, with their components. Zigzagging decomposition is indicated between the functional and physical domains. Upper level DPs constrain lower level FRs. The process domain and its connection to the physical domain is not elaborated here387

 

Fig. 13.2 Zigzagging decomposition symbolic example. The arrows show the direction of the flow and the order is indicated by the numbers on the arrows. There must be at least two children at each level of the decomposition in each branch391

 

List of Tables

Table 1.1 Search results in SCOPUS16

 

Table 2.1 Structure of SME workshops51

 

Table 2.2 Categories used in the workshop brainstorming sessions52

 

Table 2.3 Thematic clustering of workshop inputs53

 

Table 2.4 Breakdown of categorization of workshop outputs54

 

Table 2.5 Excerpt from the list of the reverse engineering approach55

 

Table 2.6 Final list of SME functional requirements for smart manufacturing57

 

Table 2.7 Constraints (limitations and barriers) of SMEs introducing smart manufacturing61

 

Table 4.1 Main significant mechanical hazards consequences in traditional and collaborative industrial robotics according to ISO 10218-2 and to UR3 robot original instructions (ISO 2011a; Universal Robot 2018)113

 

Table 4.2 Main passive and active risk reduction measures for the management of quasi-static or transient contacts according to ISO TS 15066 (ISO 2016)121

 

Table 4.3 Classification data of the identified technological leading research areas of interest: percentage of relevant papers which contain a specific topic131

 

Table 4.4 Relationships between main OHS standards and other deliverables related to industrial HRC134

 

Table 5.1 Facts and figures of SME workshops151

 

Table 6.1 Comparison of 2D codes (based on Knuchel et al. 2011)169

 

Table 6.2 Comparison of the proposed concepts187

 

Table 8.1 Comparison of literature sources dedicated to MMs, roadmaps, and conceptual frameworks219

 

Table 8.2 Input data for calculations of Cronbach’s alpha coefficients232

 

Table 9.1 Organizational obstacles and barriers to Industry 4.0 implementation (Adapted from Orzes et al. 2018)255

 

Table 9.2 Organizational barriers to innovation258

 

Table 9.3 Organizational barriers and problems for Industry 4.0 implementation263

 

Table 9.4 Confirmed organizational barriers and problems for Industry 4.0 implementation270

 

Table 9.5 Proposed organizational barriers and problems (not highlighted by previous Industry 4.0 literature)271

 

Table 10.1 Main factors of industry 4.0289

 

Table 10.2 SMEs 4.0 assessment of the case study: make-to-order snack factory294

 

Table 10.3 SMEs 4.0 assessment of the case study: service industry296

 

Table 10.4 SMEs 4.0 assessment of the case study: small fabrication company298

 

Table 10.5 SMEs 4.0 assessment of the case study: multinational SMEs299

 

Table 11.1 Data encoding from vision systems to one packet319

 

Table 12.1 Main guidelines for the preliminary evaluation of human–robot task allocation starting from existing manufacturing activities340

 

Table 12.2 Summary of main feeding, handling and assembly critical issues according to the guidelines developed by Boothroyd and Crowson for the design of robotic and automatic assembly (Boothroyd et al. 2010; Boothroyd 2005; Crowson 2006)343

 

Table 12.3 Components and subassemblies list356

 

Table 12.4 Manual assembly cycle main data358

 

Table 12.5 Examples of technical evaluation of feeding and handling tasks360

 

Table 12.6 Technical evaluation of tasks O5, O8, and O27 according to main critical issues analysis and technical evaluation workflow360

 

Table 12.7 Examples of technical evaluation of assembly tasks361

 

Table 12.8 Technical evaluation of task O9 and O10 according to main critical issues analysis and technical evaluation workflow362

 

Table 12.9 RULA action levels and relative task allocation363

 

Table 12.10 List of tasks which present a RULA index value equal to or higher than three and which could potentially be performed by the robot from a technical point of view363

 

Table 12.11 VA/NVA classification of tasks which could potentially be performed by the robot from a technical point of view366

 

Table 12.12 Overall and final evaluation results367

 

Table 12.13 Final task allocation logic according to the proposed framework and related examples369

 

Table 12.14 Examples of task unification according to the use of resources370

 

Table 13.1 Parts and elements of design385

 

Table 13.2 The design domains386

 

Table 13.3 Steps for zigzagging decompositions to develop FRs and select the best DPs391

 

Table 13.4 Uncoupled basic design matrix, diagonal, and therefore fully independent392

 

Table 13.5 Decoupled basic design matrix, triangular, and therefore quasi-independent392

 

Table 13.6 Coupled basic design matrix, full, and therefore not independent392

 

Table 13.7 Example of an FR-DP, top-level decomposition in response to a CN for sustainability in metal cutting394

 

Table 13.8 Some typical problems in a poor design397

 

Notes on Contributors

Christopher A. Brown

earned his Ph.D. at the University of Vermont, and then spent four years in the Materials Department at the Swiss Federal Institute of Technology. Subsequently he was a senior research engineer working on product and process research and design at Atlas Copco’s European research center. Since the fall of 1989, Chris Brown has been on the faculty at WPI. Chris Brown has published over a hundred and fifty papers on AD, manufacturing, surface metrology, and sports engineering. He has patents on characterizing surface roughness, friction testing, and sports equipment. He also developed software for surface texture analysis. He currently teaches graduate courses on Axiomatic Design of manufacturing processes, and on surface metrology, and undergraduate courses on manufacturing and on skiing technology.

 

Nilubon Chonsawat

was born in Rayong, Thailand. She received a Bachelor of Engineering Program in Computer Engineering in 2012, Faculty of Engineering and a Master of Science Program in Technopreneurshipin 2015, Institute of Field Robotics (FIBO), King Mongkut’s University of Technology Thonburi (KMUTT), Thailand. In 2016, she started her Doctor of Philosophy Program in Industrial Engineering, Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University (CMU), Thailand. Her research interests focus on advanced technology, industrial engineering, logistics and supply chain management, Smart SMEs, organizational performance measurement, and the Industry 4.0 principle.

 

Patrick Dallasega

received degrees from the Free University of Bolzano, Bolzano, Italy, the Polytechnic University of Turin, Turin, Italy, and the Ph.D. degree from the University of Stuttgart, Stuttgart, Germany. He is an Assistant Professor of project management and industrial plants design with the Faculty of Science and Technology, the Free University of Bolzano. He was a Visiting Scholar with the Excellence Center in Logistics and Supply Chain Management Chiang Mai University, Chiang Mai, Thailand, and the Worcester Polytechnic Institute in Massachusetts, Worcester, MA, USA. His main research interests are supply chain management, Industry 4.0, lean construction, lean manufacturing and production planning, and control in MTO and ETO enterprises.

 

Luca Gualtieri

is an Industrial Engineer specialized in manufacturing and logistics. He is also a certified Occupational Health and Safety Manager and Trainer, mainly focused on safety of machinery. He is working in the Smart Mini Factory lab as research fellow and doctoral candidate for the Industrial Engineering and Automation (IEA) group of the Faculty of Science and Technology, Free University of Bozen-Bolzano. He is responsible for research in the field of industrial collaborative robotics. In particular, he is focusing on human–machine interaction from the point of view of the operator’s occupational health and safety conditions, ergonomics, and shared workplace organization. He is involved in the EU project “SME 4.0—Industry 4.0 for SMEs” as well as industry projects on collaborative robotics and workplace design.

 

Johannes Kapeller

received the Dipl.-Ing. Degree in Industrial Logistics from the Montanuniversitaet Leoben, Austria. In 2018, he completed his Ph.D. in Industrial Engineering with special focus on the sequential combination of production control strategies within the line production area. Since 2018, he works as a management consultant at the Boston Consulting Group. Prior he has been a Postdoc at the Montanuniversitaet in Leoben and a visiting researcher within the research project “SME 4.0—Industry 4.0 for SMEs” at the University of Chiang Mai, Thailand. Johannes published his work in high-quality peer-reviewed journals.

 

Dominik T. Matt

holds the Chair for Production Systems and Technologies and heads the research department “Industrial Engineering and Automation (IEA)” at the Faculty of Science and Technology at the Free University of Bozen-Bolzano. Moreover, Dominik is the Director of the Research Center Fraunhofer Italia in Bolzano. Dominik coordinates as Principal Investigator the Horizon 2020 research project SME 4.0 as Lead Partner. His research primarily focuses on the areas of Industry 4.0 and Smart Factory, Lean and Agile Production, on the planning and optimization of assembly processes and systems, as well as on organizational and technical aspects of in-house logistics. He has authored more than 200 scientific and technical papers in journals and conference proceedings and is member of numerous national and international scientific organizations and commitees (e.g., AITeM—Associazione Italiana di Tecnologia Meccanica | WGAB—Academic Society for Work and Industrial Organization | EVI—European Virtual Institute on Innovation in Industrial Supply Chains and Logistic Networks).

 

Vladimír Modrák

is Full Professor of Manufacturing Technology at Faculty of Manufacturing Technologies of Technical University of Kosice. He obtained his Ph.D. degree at the same University in 1989. His research interests include cellular manufacturing systems design, mass customized manufacturing and planning/scheduling optimization. Since 2015 he is a Fellow of the European Academy for Industrial Management (AIM). He was the leading editor of three international books,Operations Management Research and Cellular Manufacturing Systems ,Handbook of Research on Design and Management of Lean Production Systems , andMass Customized Manufacturing: Theoretical Concepts and Practical Approaches . He is also active as editorial board member in several scientific journals and committee member of many international conferences. Moreover, Vladimiír is Vice-Rector for International Relations of Technical University of Kosice.

 

Guido Orzes

received his M.Sc. in Management Engineering from the University of Udine (Italy) in 2011 with summa cum laude. In 2015, he obtained his Ph.D. degree in Industrial and Information Engineering (topic: operations management) from the University of Udine (Italy). Currently, he is an Assistant Professor in Management Engineering at the Free University of Bozen-Bolzano (Italy). He is also Honorary Research Fellow at the University of Exeter Business School (UK) and Visiting Scholar at the Worcester Polytechnic Institute (USA). His research focuses on international sourcing and manufacturing and their social and environmental implications. He has published over 70 scientific works on these topics in leading operations management and international business journals (e.g.,International Journal of Operations & Production Management ,International Journal of Production Economics ,International Business Review , andJournal of Purchasing and Supply Management ) as well as in conference proceedings and books. He is involved (as work package leader or coinvestigator) in various EU-funded research projects on global operations management and Industry 4.0. He is also Associate Editor of theElectronic Journal of Business Research Methods and member of the board of the European division of the Decision Science Institute.

 

Ilaria Palomba

received the M.Sc. degree in Product Innovation Engineering from the University of Padua, in 2012. In 2016, she obtained the Ph.D. degree in Mechatronics and Product Innovation Engineering from the University of Padua with a dissertation on “State estimation in multibody systems with rigid or flexible links”. Currently, she is an Assistant Professor in Applied Mechanics at the Free University of Bozen-Bolzano. Dr. Palomba’s research activities chiefly concern theoretical and experimental investigations in the fields of mechanics of machines, mechanical vibrations, multibody dynamics, and robotics and automation. In particular, her research interests are focused on the following topics: nonlinear state estimation for multibody systems with rigid and flexible links; model reduction of vibrating systems; robotic grasping systems for soft and fragile bodies; structural modifications and model updating of vibrating systems; design of advanced mechatronic systems.

 

Ján Pitel

is a Full Professor in automation at the Technical University of Košice (Slovakia) and he currently works at the Faculty of Manufacturing Technologies with a seat in Prešov as vice-dean and head of the Institute of Production Control. His research activities include modelling, simulation, automatic control and monitoring of machines and processes. He is author of more than 60 papers registered in databases WoS and Scopus with more than 200 SCI citations. He is inventor and coinventor of more than 50 patents and utility models. He has been leader of many national projects (e.g., EU Structural Funds projects) and currently he participates in 2 EC-funded projects (H2020, Erasmus+). As vice-dean for external relationships he is responsible for mobility programs under the framework of projects ERASMUS and CEEPUS.

 

Robert Poklemba

is Ph.D. student in the department of automotive and manufacturing technologies at the Technical University of Kosice (Slovakia). His dissertation thesis is focused on composite material based on polymer concrete. He worked at the project as an early stage researcher and was part of a team that was focused on organizational and managerial models in a mass customized environment for small and medium enterprises.

 

Sakgasem Ramingwong

is an Associate Professor in Industrial Engineering at the Faculty of Engineering at Chiang Mai University, Thailand. His research interests are in industrial logistics and supply chain management.

 

Erwin Rauch

holds an M.Sc. in Mechanical Engineering from the Technical University Munich (TUM) and an M.Sc. in Business Administration from the TUM Business School and obtained his Ph.D. degree in Mechanical Engineering from the University of Stuttgart with summa cum laude. Currently he is an Assistant Professor for Manufacturing Technology and Systems at the Free University of Bolzano, where he is the Head of the Smart Mini Factory laboratory for Industry 4.0. His current research is on Industry 4.0, Social Sustainability in Production, Smart and Sustainable Production Systems, Smart Shopfloor Management and Engineer/Make to Order. He has 10 years of experience as Consultant and later Associate Partner in an industrial consultancy firm operating in production and logistics. He is project manager of the EU-funded H2020 research project “SME 4.0—Industry 4.0 for SMEs” in an international partner consortium. Further, he is author and coauthor of more than 130 scientific and nonscientific books, chapters of books, articles, and other contributions and received several awards for scientific contributions.

 

Hermann Reiter

received the Dipl.-Ing. Degree in Production and Management from the University of Applied Science Steyr, Austria. In 2009 he completed his Master’s in Supply Chain Management and in 2017 his Executive MBA from the Danube University Krems, Austria. Since 2004, he was working in different positions, e.g., project manager, head of production planning and head of supply chain management in industrial manufacturing companies. He was working in the pharmaceutical area for 7 years. In 2012 he moved to the automotive supplier industry being responsible for the global supply chain and ERP-implementation in Austria and China. Since 2018 he is a member of the directors of global automotive supplier for headlamps.

 

Rafael A. Rojas

received an M.Sc. degree in Mechanical Engineering at the Sapienza University of Rome. In 2016 he concluded his Ph.D. in theoretical and applied mechanics with ad dissertation on optimal control theory for semi-active actuators. Since 2016, he works as postdoc research fellow at the Free University of Bozen-Bolzano in the Smart Mini Factory laboratory, focusing in his research on cyber-physical production systems, smart manufacturing control systems, connectivity and interoperability, and collaborative robotics. As Visiting Scholar, he worked in the research project “SME 4.0—Industry 4.0 for SMEs” with the Faculty of Mechanical Engineering at Worcester Polytechnic Institute (WPI) in Massachusetts. Rafael published his work in high-quality peer-reviewed journals likeRobotics and Automation Letters andMechanical Systems and Signal Processing .

 

Manuel A. Ruiz Garcia

received his Master’s degree in Control Engineering in 2013 and his Ph.D. in Engineering in Computer Science in 2018, both from Sapienza University of Rome, Rome, Italy. He is a postdoc research fellow in the Smart Mini Factory Laboratory of the Free University of Bozen-Bolzano, Bolzano, Italy. His research interests include reactive control of mobile manipulators, robotics perception, collaborative robotics, and human–robot cooperation. He had been involved in the EU Projects “NIFTi—Natural human-robot cooperation in dynamic environments” and “TRADR—Long-term human-robot teaming for disaster response” and is currently involved in the EU Project “SME 4.0—Industry 4.0 for SMEs” as well as in industry projects on collaborative robotics and robotics perception. Dr. Ruiz Garcia published his work in high-quality peer-reviewed journals and conference proceedings likeIEEE Robotics and Automation Letters , Proceedings of the IEEE International Conference on Robotics and Automation and Proceedings of the International Conference on Computer Vision.

 

Zuzana Šoltysová

completed her Bachelor’s and Master’s at the Technical University of Kosice, Faculty of Manufacturing Technologies with a seat in Presov, Department of Manufacturing Management in the field of Manufacturing Management. She completed her Ph.D. Study at Technical University of Kosice, Faculty of Manufacturing Technologies with a seat in Presov, Department of Manufacturing Management in the field of Industrial Technology. Her Ph.D. thesis was focused on the research of product and production complexity in terms of mass customization. Currently, she is an Assistant Professor at Faculty of Manufacturing Technologies with a seat in Presov at Department of Manufacturing Management. Moreover, her research activities include complexity, throughput, axiomatic design, and production line balancing rate.

 

Apichat Sopadang

was born in Chiang Mai, Thailand. He graduated from Chiang Mai University, Thailand in 1987 with a degree in industrial engineer. For several years, he worked as a maintenance planning engineer in Electricity Generator Authority of Thailand (EGAT). He completed his Ph.D. from Clemson University, USA in 2001. Following the completion of his Ph.D., he is working for Chiang Mai University as an Associate Professor and head of Excellence Center in Logistics and Supply Chain Management (E-LSCM). He is a frequent speaker at industry and academic meetings. His current research areas are on Industry 4.0, Sustainability Supply Chain, Aviation Logistics, Lean Manufacturing System and Performance Measurement. Dr. Sopadang also served as a consultant in many private organizations in Thailand and international organizations such as the Asian Development Bank (ADB) and The Japan External Trade Organization (JETRO). He is author and coauthor of more than 100 academic papers that include book chapters and articles.

 

Korrakot Tippayawong

graduated with B.Eng., M.Eng. and Ph.D. in Industrial Engineering from Chiang Mai University, Thailand, Swinburne University of Technology, Australia, and Tokyo Institute of Technology, Japan, respectively. She has over 20 years’ experience in teaching, research, and industrial consultation. Korrakot has worked with more than 300 SMEs as well as a number of large public and private enterprises. She is currently an Assistant Professor at Department of Industrial Engineering, Chiang Mai University. Her research focuses on logistics & supply chain, industrial engineering & management. She has received many major grants, including those from Thai Ministry of Industry, Ministry of Science and Technology, and European Horizon 2020 MSCA-RISE programme.

 

Walter T. Towner

teaches for the Foisie Business School at Worcester Polytechnic Institute, Worcester Massachusetts, USA. Courses include Achieving Effective Operations, Engineering Economics, Operations Management, Lean Process Design, Productivity Management, Design and Analysis of Manufacturing Processes, Six Sigma, and Axiomatic Design Theory. The courses were taught at Raytheon, UTC, Natick Labs, NE Utilities, NSTAR, ECNE, Public Service of NH, Electric Boat, UMass Hospital, and General Dynamics and GE Healthcare. These courses are interdisciplinary and combine elements of engineering, finance, and management. Prof. Towner is the former owner of a metal fabrication and laser cutting manufacturing company serving semiconductor equipment, medical equipment, and nuclear power. Degrees from WPI include BS Mechanical Engineering, MS Operations & Information Technology, MS Manufacturing Engineering, an M.B.A. from Babson College and alumnus of Owner/President Management Program at Harvard Business School. The WPI Alumni Association awarded the John Boynton Award Young Alumni Award and the Herbert F. Taylor Award for service to the university. Awarded Provost’s Undergraduate Capstone Project Award three times. Prof. Towner has completed 1/3 of the 2200-mile Appalachian Trail in the Eastern US.

 

Andrew R. Vickery

is a Ph.D. student of manufacturing engineering in the mechanical engineering department of Worcester Polytechnic Institute (USA). He earned a Master’s in materials science and engineering at WPI. His main research interests are the design of sustainable manufacturing systems for SMEs, systems design through axiomatic design, and the study and optimization of value chains for SMEs.

 

Renato Vidoni

received his M.Sc. in Electronic Engineering—focus: industrial automation—from the University of Udine, Italy, in 2005. In 2009, he obtained his Ph.D. degree in Industrial and Information Engineering from the University of Udine, Italy. Currently, he is Associate Professor in Applied Mechanics at the Free University of Bozen-Bolzano (Italy) where he is responsible of the activities in robotics and mechatronics inner the Smart Mini Factory laboratory for industry 4.0 and he is the Head of the Field Robotics laboratory. He is course director of the M.Sc. in Industrial Mechanical Engineering and Rector’s delegate at the CRUI (Conference of the Rectors of Italian Universities) Foundation’s for the University-Business Observatory. His research activity is documented by more than 100 scientific contributions that deal with topics of the Applied Mechanics sector both in “classical” fields as well in new and emerging domains (e.g., industry and Agri 4.0). The recent research activity can be grouped in three different research areas that fall into the “Industrial Engineering and Automation” macro-area of the Faculty of Science and Technology: High-performance automatic machines and robots, Mechatronic applications for Energy Efficiency, Mechatronics and Robotics for field activities.

 

Erich J. Wehrle

is an Assistant Professor for Applied Mechanics at the Free University of Bozen-Bolzano. He holds a Bachelor of Science in Mechanical Engineering from the State University of New York at Buffalo (USA) and a Master of Science in Mechanical Engineering from the Technical University of Munich. He carried out research in structural design optimization with crash loading under uncertainty at Institute of Lightweight Structures leading to the Doktor-Ingenieur (doctor of engineering) degree. At his current appointment at the Free University of Bozen-Bolzano, he is deputy director of the Mechanical Lab. His current research includes applied mechanics, design optimization, multibody dynamics, topology optimization for compliant mechanisms, nonlinear mechanics, Industry 4.0, and engineering education. He is author and coauthor of more than 60 book chapters, conference papers, articles, and other contributions.

 

Christian Weichbold

received the Dipl.-Ing. Degree in Industrial Logistics from the Montanuniversitaet Leoben, Austria. Since 2016, he works as a researcher at the Voestalpine Stahl Donawitz GmbH in the blast furnace area for reduction metallurgy with special focus on his Ph.D.-project material tracking of bulk material (iron ore sinter) and its properties.

 

Warisa Wisittipanich

received a Master of Science in Systems Engineering from George Mason University, Virginia, USA in 2006 and obtained a Doctor of Engineering from Asian Institute of Technology, Thailand in 2012. Currently, she is working as an Assistant Professor at the Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand. Her areas of interests and research include operations research, production scheduling and sequencing, inbound and outbound truck scheduling, vehicle routing problem, supply chain and logistics management, and metaheuristic applications for real-world optimization problems.

 

Manuel Woschank

is a Postdoc Senior Lecturer and Researcher at the Department of Economic and Business Management, Chair of Industrial Logistics at the University of Leoben. Manuel holds a Diploma in Industrial Management and a Master’s Degree in International Supply Management from the University of Applied Sciences FH JOANNEUM, Austria and a Ph.D. in Management Sciences from the University of Latvia, Latvia. He has published a multitude of international, peer-reviewed papers and has conducted research projects with voestalpine AG, Stahl Judenburg—GMH Gruppe, Knapp AG, SSI Schaefer, MAGNA International Europe GmbH, Hoerbiger Kompressortechnik Holding GmbH, voestalpine Boehler Aerospace GmbH & Co KG, etc. His research interests include Logistics Systems Engineering, Logistics Process Optimization, Production Planning and Control Systems, and Behavioral Decision Making Theory. He is a member of BVL, WING, Logistikclub Leoben, ILA, and GfeW.

 

Kamil Židek

is focused on the research in the area of image processing for manufacturing applications and knowledge extraction by algorithms of artificial intelligence. He completed his habitation thesis named “Identification and classification surface errors of mechanical engineering products by vision systems” at Faculty of Manufacturing Technologies of Technical University of Kosice. Currently, he is Associate Professor at this faculty. He published his research titled “Embedded vision equipment of industrial robot for in-line detection of product errors by clustering-classification algorithms” in the mentioned area in Current Contents (IF 2016 = 0.987). He is the lead author of one Current Contents article and coauthor of 3 other CC articles. He is inventor and coinventor of 6 published patents 4 and 8 utility models. He is also coauthor of 1 monograph, 2 university textbooks, and 3 scripts.

 

Helmut Zsifkovits

holds the Chair of Industrial Logistics at the Department of Economics and Business Management at Montanuniversitaet Leoben, Austria. He graduated from the University of Graz, Austria and has professional experience in automotive industry, logistics consultancy, and IT. His research interests include logistics systems engineering, supply chain strategy, and operations management. He is a Board Member of the European Certification Board for Logistics (ECBL), Vice-President of Bundesvereinigung Logistik Austria (BVL), and President of Logistics Club Leoben. In 2018, he was appointed as an Adjunct Professor at the University of the Sunshine Coast, Australia. He has teaching assignments at various universities in Austria, Latvia, Colombia, and Germany, and is the author of numerous scientific publications and several books.