Engineering insights from an anthropocentric cyber-physical system: A case study for an assembly station

Abstract To effectively cope with the complexity of manufacturing control problems the cyber-physical systems are engineered to work in the social space. Therefore the research in the field of cyber-physical systems needs to address social aspects when this concept is adopted in factory automation. The paper argues for an anthropocentric cyber-physical reference model as the basic decomposition unit for the design of distributed manufacturing control systems. The model assimilates all the required components (i.e. physical, computational and human) of a synthetic hybrid system in an integrated way. This is due to the real need to design cyber-physical production systems where the technological advances are merging their functionalities in a way more and more difficult to distinctly draw between the physical, computational and human components. If this view is almost obvious for advanced technologies, such as brain computer interfaces, controlled assistive robots and intelligent prostheses, it is equally true even for simple automated systems, like context-aware assistive systems that are built with state-of-the-art technologies. This assertion is demonstrated in the context of the SmartFactory KL production system, where the manual assembly station exhibits all the key features of an anthropocentric cyber-physical system by employing a seamless augmented reality to guide the human operator.

[1]  Paul P. Maglio,et al.  Steps Toward a Science of Service Systems , 2007, Computer.

[2]  Hai Zhuge,et al.  Interactive semantics , 2010, Artif. Intell..

[3]  Damien Trentesaux,et al.  A stigmergic approach for dynamic routing of active products in FMS , 2009, Comput. Ind..

[4]  Enzo Morosini Frazzon,et al.  Towards Socio-Cyber-Physical Systems in Production Networks , 2013 .

[5]  Tonci Grubic,et al.  Supply chain ontology: Review, analysis and synthesis , 2010, Comput. Ind..

[6]  Yong Yin,et al.  Perceptual control architecture for cyber-physical systems in traffic incident management , 2012, J. Syst. Archit..

[7]  Takashi Minato,et al.  Physical Human-Robot Interaction: Mutual Learning and Adaptation , 2012, IEEE Robotics & Automation Magazine.

[8]  Kristinn R. Thórisson,et al.  Attention Capabilities for AI Systems , 2012, ICINCO.

[9]  Alok K. Choudhary,et al.  Semantic web in manufacturing , 2009 .

[10]  Mathias Schmitt,et al.  Mobile Interaction Technologies in the Factory of the Future , 2013, IFAC HMS.

[11]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[12]  Jozef Kelemen,et al.  Beyond Artificial Intelligence: The Disappearing Human-Machine Divide , 2014 .

[13]  Malte Brettel,et al.  How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective , 2014 .

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

[15]  Matthias Loskyll,et al.  Do Not Cancel My Race with Cyber-Physical Systems , 2014 .

[16]  Matthias Loskyll,et al.  Context-Based Orchestration for Control of Resource-Efficient Manufacturing Processes , 2012, Future Internet.

[17]  Fei-Yue Wang,et al.  The Emergence of Intelligent Enterprises: From CPS to CPSS , 2010, IEEE Intelligent Systems.

[18]  Paulo Leitão,et al.  ADACOR: A holonic architecture for agile and adaptive manufacturing control , 2006, Comput. Ind..

[19]  Eric Becker,et al.  An event driven framework for assistive CPS environments , 2009, SIGBED.

[20]  Wenji Mao,et al.  Cyber-Physical-Social Systems for Command and Control , 2011, IEEE Intelligent Systems.

[21]  Anne Beaudry,et al.  Understanding User Responses to Information Technology: A Coping Model of User Adaption , 2005, MIS Q..

[22]  Schahram Dustdar,et al.  The Social Compute Unit , 2011, IEEE Internet Computing.

[23]  Renan Maffei,et al.  Exploring the IEEE ontology for robotics and automation for heterogeneous agent interaction , 2015 .

[24]  Detlef Zühlke,et al.  Preliminary Insides for an Anthropocentric Cyber-physical Reference Architecture of the Smart Factory , 2013 .

[25]  Giulia Biamino A Semantic Model for Socially Aware Objects , 2012, IOT 2012.

[26]  Charles S. Wasson Human–System Integration , 2005 .

[27]  Schahram Dustdar,et al.  Unifying Human and Software Services in Web-Scale Collaborations , 2008, IEEE Internet Computing.

[28]  J. C. R. Licklider,et al.  Man-Computer Symbiosis , 1960 .

[29]  Dale Goodhue,et al.  What Happens After ERP Implementation: Understanding the Impact of Interdependence and Differentiation on Plant-Level Outcomes , 2005, MIS Q..

[30]  Liang Hu,et al.  Review of Cyber-Physical System Architecture , 2012, 2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops.

[31]  Paulo Leitão,et al.  Recent Developments and Future Trends of Industrial Agents , 2011, HoloMAS.

[32]  Deniz Erdogmus,et al.  The Future of Human-in-the-Loop Cyber-Physical Systems , 2013, Computer.

[33]  E. Hutchins Cognition in the wild , 1995 .

[34]  Claudio S. Pinhanez Human aspects of internet services: considering the needs of users and providers , 2011, Journal of Internet Services and Applications.

[35]  Imre Horváth,et al.  What the Design Theory of Social-Cyber-Physical Systems Must Describe, Explain and Predict? , 2014 .

[36]  Tom Ziemke,et al.  Enactive artificial intelligence: Investigating the systemic organization of life and mind , 2009, Artif. Intell..

[37]  Ghassan Beydoun,et al.  Aligning ontology-based development with service oriented systems , 2014, Future Gener. Comput. Syst..

[38]  T. Bangemann,et al.  A system of systems view on collaborative industrial automation , 2013, 2013 IEEE International Conference on Industrial Technology (ICIT).

[39]  Matthias Loskyll,et al.  Enabling virtual assembly training in and beyond the automotive industry , 2012, 2012 18th International Conference on Virtual Systems and Multimedia.

[40]  David M. Dilts,et al.  The evolution of control architectures for automated manufacturing systems , 1991 .

[41]  Rolf Pfeifer,et al.  How the body shapes the way we think - a new view on intelligence , 2006 .

[42]  Luc Bongaerts,et al.  Reference architecture for holonic manufacturing systems: PROSA , 1998 .

[43]  Bogdan-Constantin Pirvu,et al.  Human-centred Assembly: A Case Study for an Anthropocentric Cyber-physical System , 2014 .

[44]  Matthias Loskyll,et al.  Semantic service discovery and orchestration for manufacturing processes , 2011, ETFA2011.

[45]  Wendy E. Mackay,et al.  Diversity in the use of electronic mail: a preliminary inquiry , 1988, TOIS.

[46]  Michael Wooldridge,et al.  Introduction to Multi-Agent Systems , 2016 .

[47]  W. Karwowski International encyclopedia of ergonomics and human factors , 2001 .

[48]  Valentin Robu,et al.  Emergence of consensus and shared vocabularies in collaborative tagging systems , 2009, TWEB.

[49]  W. Orlikowski Using Technology and Constituting Structures: A Practice Lens for Studying Technology in Organizations , 2000 .

[50]  Edward A. Lee Cyber Physical Systems: Design Challenges , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).

[51]  C. Wickens,et al.  Applied Attention Theory , 2007 .