Life Cycle Engineering 4.0: A Proposal to Conceive Manufacturing Systems for Industry 4.0 Centred on the Human Factor (DfHFinI4.0)

Engineering 4.0 environments are characterised by the digitisation, virtualisation, and connectivity of products, processes, and facilities composed of reconfigurable and adaptive socio-technical cyber-physical manufacturing systems (SCMS), in which Operator 4.0 works in real time in VUCA (volatile, uncertain, complex and ambiguous) contexts and markets. This situation gives rise to the interest in developing a framework for the conception of SCMS that allows the integration of the human factor, management, training, and development of the competencies of Operator 4.0 as fundamental aspects of the aforementioned system. The present paper is focused on answering how to conceive the adaptive manufacturing systems of Industry 4.0 through the operation, growth, and development of human talent in VUCA contexts. With this objective, exploratory research is carried, out whose contribution is specified in a framework called Design for the Human Factor in Industry 4.0 (DfHFinI4.0). From among the conceptual frameworks employed therein, the connectivist paradigm, Ashby’s law of requisite variety and Vigotsky’s activity theory are taken into consideration, in order to enable the affective-cognitive and timeless integration of the human factor within the SCMS. DfHFinI4.0 can be integrated into the life cycle engineering of the enterprise reference architectures, thereby obtaining manufacturing systems for Industry 4.0 focused on the human factor. The suggested framework is illustrated as a case study for the Purdue Enterprise Reference Architecture (PERA) methodology, which transforms it into PERA 4.0.

[1]  Botond Kádár,et al.  Simulation model study for manufacturing effectiveness evaluation in crowdsourced manufacturing , 2017 .

[2]  T. D. Wilson,et al.  Activity theory and information seeking , 2009, Annu. Rev. Inf. Sci. Technol..

[3]  Chengliang Liu,et al.  An Integrated Industrial Ethernet Solution for the Implementation of Smart Factory , 2017, IEEE Access.

[4]  Y. Engeström,et al.  Expansive Learning at Work: Toward an activity theoretical reconceptualization , 2001 .

[5]  Bernhard Kölmel,et al.  Integrated Engineering - A SME-Suitable Model for Business and Information Systems Engineering (BISE) towards the Smart Factory , 2012, PRO-VE.

[6]  Betsy Duke,et al.  Connectivism as a Learning Theory for the Digital Age , 2012 .

[7]  Hannah Ji,et al.  Development of Propositions on Human Cognitive Abilities Matching Impacts on Accounting Job Performance , 2019 .

[8]  Ole Madsen,et al.  A Virtual Commissioning Learning Platform , 2018 .

[9]  Jaroslav Vrchota,et al.  Readiness of Enterprises in Czech Republic to Implement Industry 4.0: Index of Industry 4.0 , 2019, Applied Sciences.

[10]  M. E. Peralta,et al.  The challenge of integrating Industry 4.0 in the degree of Mechanical Engineering , 2017 .

[11]  Roberto Pinto,et al.  The business transformation towards smart manufacturing: a literature overview about reference models and research agenda , 2017 .

[12]  Miguel A. Martínez,et al.  Integrating VSM and Network Analysis for Tourism Strategies – Case: Mexico and the Chinese Outbound Market , 2019, Systemic Practice and Action Research.

[13]  Ivan Rizzo Guilherme,et al.  A Multi-agent System Approach for Management of Industrial IoT Devices in Manufacturing Processes , 2018, 2018 IEEE 16th International Conference on Industrial Informatics (INDIN).

[14]  Rajen K. Gupta,et al.  Disruptive innovation and dynamic capabilities in emerging economies: Evidence from the Indian automotive sector , 2017 .

[15]  Pál Varga,et al.  Advanced Security Considerations in the Arrowhead Framework , 2016, SAFECOMP Workshops.

[16]  Laura Porcu,et al.  Cloud manufacturing as a sustainable process manufacturing route , 2018 .

[17]  Syed Imran Shafiq,et al.  Manufacturing collective intelligence by the means of Decisional DNA and virtual engineering objects, process and factory , 2017, J. Intell. Fuzzy Syst..

[18]  Paola Fantini,et al.  Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems , 2018, Comput. Ind. Eng..

[19]  Andrew Whitworth,et al.  Rules, roles and tools: Activity theory and the comparative study of e-learning , 2008, Br. J. Educ. Technol..

[20]  S. Barab,et al.  Using Activity Theory to Conceptualize Online Community and Using Online Community to Conceptualize Activity Theory , 2004 .

[21]  Åsa Fast-Berglund,et al.  The Operator 4.0: Human Cyber-Physical Systems & Adaptive Automation Towards Human-Automation Symbiosis Work Systems , 2016, APMS.

[22]  Eunbae Lee,et al.  Connectivism as a Framework for Creative Productivity in Instructional Technology , 2011, 2011 IEEE 11th International Conference on Advanced Learning Technologies.

[23]  Hongnian Yu,et al.  Management approaches for Industry 4.0: A human resource management perspective , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

[24]  William R. King,et al.  Knowledge Management and Organizational Learning , 2009, Knowledge Management and Organizational Learning.

[25]  Mustafa Tuncay,et al.  The Emergent Technological and Theoretical Paradigms in Education: The Interrelations of Cloud Computing (CC), Connectivism and Internet of Things (IoT) , 2015 .

[26]  Jiafu Wan,et al.  Industrial Big Data Analytics for Prediction of Remaining Useful Life Based on Deep Learning , 2018, IEEE Access.

[27]  Yanhong Zhou,et al.  Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing , 2019, Engineering.

[28]  Ole Madsen,et al.  The AAU Smart Production Laboratory for Teaching and Research in Emerging Digital Manufacturing Technologies , 2017 .

[29]  Pauline Found,et al.  TQM, games design and the implications of integration in Industry 4.0 systems , 2019, International Journal of Quality and Service Sciences.

[30]  Y. Engeström,et al.  Activity theory and individual and social transformation. , 1999 .

[31]  Ana Cachada,et al.  Maintenance 4.0: Intelligent and Predictive Maintenance System Architecture , 2018, 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA).

[32]  Hajar Mozaffar,et al.  Health Technology Development and Use: From Practice‐bound Imagination to Evolving Impacts , 2011 .

[33]  K. Foot Cultural‐historical activity theory as practice theory: illuminating the development of conflict‐monitoring network , 2001 .

[34]  Venanzio Arquilla,et al.  A Design perspective for IoT products. A case study of the Design of a Smart Product and a Smart Company following a crowdfunding campaign , 2017 .

[35]  Jay Lee,et al.  A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems , 2015 .

[36]  Laine Mears,et al.  Measurement of Operator-machine Interaction on a Chaku-chaku Assembly Line , 2017 .

[37]  Peng Wang,et al.  Ontology-based web service integration for flexible manufacturing systems , 2017, 2017 IEEE 15th International Conference on Industrial Informatics (INDIN).

[38]  Predrag Ćosić,et al.  Process Planning in Industry 4.0 Environment , 2017 .

[39]  M. Mol,et al.  Management Innovation Made in China: Haier’s Rendanheyi , 2018, California Management Review.

[40]  Helen Hasan,et al.  Demonstrations of the Activity Theory Framework for Research in Information Systems , 2007, Australas. J. Inf. Syst..

[41]  Zaleha Abdullah,et al.  Activity Theory as Analytical Tool: A Case Study of Developing Student Teachers’ Creativity in Design★ , 2014 .

[42]  Ishwar Singh,et al.  SEPT Learning Factory Framework , 2018, REV.

[43]  Klaus-Dieter Thoben,et al.  Learning in ports with serious gaming , 2017, 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC).

[44]  Michael C. Pyryt Human cognitive abilities: A survey of factor analytic studies , 1998 .

[45]  Fernando Galindo-Rueda,et al.  OECD Taxonomy of Economic Activities Based on R&D Intensity , 2016 .

[46]  J. Brine,et al.  Students' perceptions of a selected aspect of a computer mediated academic writing program: An activity theory analysis , 2006 .

[47]  Jungtae Mun,et al.  Self-evolution framework of manufacturing systems based on fractal organization , 2009, Comput. Ind. Eng..

[48]  José García Rodríguez,et al.  Machine Learning Improves Human-Robot Interaction in Productive Environments: A Review , 2017, IWANN.

[49]  N. Bennett,et al.  What a Difference a Word Makes: Understanding Threats to Performance in a VUCA World , 2014 .

[50]  Marcello Pellicciari,et al.  Exploring the potential of Operator 4.0 interface and monitoring , 2020, Comput. Ind. Eng..

[51]  Fei Tao,et al.  A Smart Manufacturing Service System Based on Edge Computing, Fog Computing, and Cloud Computing , 2019, IEEE Access.

[52]  Dazhong Wu,et al.  Cybersecurity for digital manufacturing , 2018, Journal of Manufacturing Systems.

[53]  Amy J. C. Trappey,et al.  Immersive Technology for Human-Centric Cyberphysical Systems in Complex Manufacturing Processes: A Comprehensive Overview of the Global Patent Profile Using Collective Intelligence , 2018, Complex..

[54]  Stephen Ekwaro-Osire,et al.  Life-cycle engineering: Issues, tools and research , 2003, Int. J. Comput. Integr. Manuf..

[55]  W. Ashby,et al.  Requisite Variety and Its Implications for the Control of Complex Systems , 1991 .

[56]  Álvaro Segura,et al.  Visual computing technologies to support the Operator 4.0 , 2020, Comput. Ind. Eng..

[57]  Hwa Jen Yap,et al.  Virtual Planning, Control, and Machining for a Modular-Based Automated Factory Operation in an Augmented Reality Environment , 2016, Scientific Reports.

[58]  Stan Karanasios,et al.  HOW SHOULD TECHNOLOGY-MEDIATED ORGANIZATIONAL CHANGE BE EXPLAINED ? A COMPARISON OF THE CONTRIBUTIONS OF CRITICAL REALISM AND ACTIVITY THEORY 1 , 2013 .

[59]  Y. Engeström,et al.  Learning and Expanding with Activity Theory: The Future of Activity Theory: A Rough Draft , 2009 .

[60]  Iveta Zolotova,et al.  Smart and cognitive solutions for Operator 4.0: Laboratory H-CPPS case studies , 2020, Comput. Ind. Eng..

[61]  Yves-Simon Gloy,et al.  Textile Learning Factory 4.0 – Preparing Germany's Textile Industry for the Digital Future , 2017 .

[62]  Mike P. Papazoglou,et al.  Smart Connected Digital Factories: Unleashing the Power of Industry 4.0 and the Industrial Internet , 2018, CLOSER.

[63]  Joaquín B. Ordieres Meré,et al.  Healthy Operator 4.0: A Human Cyber–Physical System Architecture for Smart Workplaces , 2020, Sensors.

[64]  Pablo Cabanelas,et al.  The impact of modular platforms on automobile manufacturing networks , 2017 .

[65]  Hong Li,et al.  Interface design for the Purdue enterprise reference architecture (PERA) and methodology in e-Work , 2003 .

[66]  Lars Wallin,et al.  Individual determinants of research utilization by nurses: a systematic review update , 2011, Implementation science : IS.

[67]  A. Nayeemulla Khan,et al.  On a Frame Work of Curriculum for Engineering Education 4.0 , 2018, 2018 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC).

[68]  Paula Jarzabkowski,et al.  Strategic Practices: An Activity Theory Perspective on Continuity and Change , 2003 .

[69]  Amit P. Sheth,et al.  From Raw Data to Smart Manufacturing: AI and Semantic Web of Things for Industry 4.0 , 2018, IEEE Intelligent Systems.

[70]  Christoph Herrmann,et al.  Supporting SMEs towards adopting mixed reality : A training concept to bring the reality-virtuality continuum into application , 2018, 2018 IEEE 16th International Conference on Industrial Informatics (INDIN).

[71]  Jie Wang,et al.  Optimized Adaptive Scheduling of a Manufacturing Process System with Multi-skill Workforce and Multiple Machine Types: An Ontology-based, Multi-agent Reinforcement Learning Approach , 2016 .

[72]  Jon Martin Fordal,et al.  Operator 4.0 – Emerging Job Categories in Manufacturing , 2018, Advanced Manufacturing and Automation VIII.

[73]  Apostolos P. Fournaris,et al.  Enabling the human in the loop: Linked data and knowledge in industrial cyber-physical systems , 2019, Annu. Rev. Control..

[74]  Kwangyeol Ryu,et al.  Agent-based fractal architecture and modelling for developing distributed manufacturing systems , 2003 .

[75]  Akos Csiszar,et al.  Digital Twins of Manufacturing Systems as a Base for Machine Learning , 2018, 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP).

[76]  Danping Lin,et al.  Design an intelligent real-time operation planning system in distributed manufacturing network , 2017, Ind. Manag. Data Syst..

[77]  Gunther Reinhart,et al.  Knowledge-Based Decision Making in a Cyber-Physical Production Scenario , 2017 .

[78]  Pingyu Jiang,et al.  The configuration of social manufacturing: a social intelligence way toward service-oriented manufacturing , 2017, Int. J. Manuf. Res..

[79]  Johan Stahre,et al.  TOWARDS AN OPERATOR 4.0 TYPOLOGY: A HUMAN-CENTRIC PERSPECTIVE ON THE FOURTH INDUSTRIAL REVOLUTION TECHNOLOGIES , 2016 .

[80]  Jay Lee,et al.  Cyber physical systems for predictive production systems , 2017, Production Engineering.

[81]  Yrjö Engeström,et al.  Category of Development as the Basis of Psychologicaland Pedagogical Research in Education , 2018 .

[82]  Stephen M. Fiore,et al.  Social Cognitive and Affective Neuroscience in Human–Machine Systems: A Roadmap for Improving Training, Human–Robot Interaction, and Team Performance , 2014, IEEE Transactions on Human-Machine Systems.

[83]  S. Z. Ismail,et al.  Development of Product Service System Modelling in SMED: The Case of Inventory Control , 2018, Journal of Modern Manufacturing Systems and Technology.

[84]  Hans-Jrgen Warnecke,et al.  The Fractal Company: A Revolution in Corporate Culture , 1997 .

[85]  Fei Tao,et al.  CCIoT-CMfg: Cloud Computing and Internet of Things-Based Cloud Manufacturing Service System , 2014, IEEE Transactions on Industrial Informatics.

[86]  Christoffer Rybski,et al.  Learning Factory for Industry 4.0 to provide future skills beyond technical training , 2018 .

[87]  A V Shukalov,et al.  Implementation of H2M technology and augmented reality for operation of cyber-physical production of the Industry 4.0 , 2019, Journal of Physics: Conference Series.

[88]  Yu-Sheng Lin,et al.  Developing a decision support system (DSS) for a dental manufacturing production line based on data mining , 2018, 2018 IEEE International Conference on Applied System Invention (ICASI).

[89]  Denis A. Coelho A growing concept of ergonomics including pleasure. comfort and cognitive engineering: an engineerin , 2002 .

[90]  María Jesús Ávila-Gutiérrez,et al.  Arquitectura holónica de referencia para empresas de fabricación sostenibles distribuidas , 2017 .

[91]  María Estela Peralta Alvarez,et al.  Reference holonic architecture for sustainable manufacturing enterprises distributed , 2017 .

[92]  Judy M. Vance,et al.  Industry use of virtual reality in product design and manufacturing: a survey , 2017, Virtual Reality.

[93]  John J. J. Chen,et al.  Operator 4.0 or Maker 1.0? Exploring the implications of Industrie 4.0 for innovation, safety and quality of work in small economies and enterprises , 2020, Comput. Ind. Eng..

[94]  Harry Daniels,et al.  Learning and expanding with activity theory , 2009 .

[95]  Lei Shu,et al.  Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges , 2016, Sensors.

[96]  Eileen Scanlon,et al.  Using technology in Higher Education: an Activity Theory perspective , 2002, J. Comput. Assist. Learn..

[97]  Giovanni Carabin,et al.  Advanced Automation for SMEs in the I4.0 Revolution: Engineering Education and Employees Training in the Smart Mini Factory Laboratory , 2018, 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).

[98]  Michael Schrefl,et al.  Modelling Knowledge about Data Analysis Processes in Manufacturing , 2015 .

[99]  Zoltan Rajnai,et al.  Labor market risks of industry 4.0, digitization, robots and AI , 2017, 2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY).

[100]  Rainer Stark,et al.  Innovations in digital modelling for next generation manufacturing system design , 2017 .

[101]  Sami Kara,et al.  Toward integrated product and process life cycle planning—An environmental perspective , 2012 .

[102]  Françoise Blin CALL and the development of learner autonomy: Towards an activity-theoretical perspective , 2004, ReCALL.

[103]  Alvaro Guarin,et al.  Learning Factory: The Path to Industry 4.0 , 2017 .

[104]  W. Ross Ashby,et al.  Variety, Constraint, And The Law Of Requisite Variety , 2011 .

[105]  Vukica Jovanovic,et al.  Smart Manufacturing: State-of-the-Art Review in Context of Conventional and Modern Manufacturing Process Modeling, Monitoring and Control , 2018 .

[106]  MengChu Zhou,et al.  A life cycle engineering approach to development of flexible manufacturing systems , 2003, IEEE Trans. Robotics Autom..

[107]  Yingfeng Zhang,et al.  A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products , 2017 .

[108]  Hong-Seok Park,et al.  Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context , 2019, Applied Sciences.

[109]  Joachim Metternich,et al.  Industrie 4.0 – Competencies for a modern production system , 2018 .

[110]  János Abonyi,et al.  Enabling Technologies for Operator 4.0: A Survey , 2018, Applied Sciences.

[111]  Xifan Yao,et al.  Emerging manufacturing paradigm shifts for the incoming industrial revolution , 2016 .

[112]  K. Kuutti Activity theory as a potential framework for human-computer interaction research , 1995 .

[113]  A. Clark,et al.  The Extended Mind , 1998, Analysis.

[114]  Canio Forliano,et al.  How Can Organisations and Business Models Lead to a More Sustainable Society? A Framework from a Systematic Review of the Industry 4.0 , 2019, Sustainability.

[115]  Torgeir Welo,et al.  Enhancing Integrative Capabilities through Lean Product and Process Development , 2016 .

[116]  P. Jordan Designing Pleasurable Products: An Introduction to the New Human Factors , 2000 .