Towards human-based industrial cyber-physical systems

The constant advances in sciences and technologies encourage industrialist and researchers in manufacturing, to address new challenges relevant to industrial Cyber-Physical Systems (CPS). Human aspects, among others, are of importance and researchers try to take them into account, but they remain to be efficiently dealt with during the design of industrial CPS. The goal of this paper is to highlight how it is possible to integrate “human-in-the-loop” inside the process control of industrial CPS. For that purpose, studies coming from the domain of industrial engineering are presented in the next part. It is completed by an overview of the main cognitive dimensions industrial designers have to integrate in assistance systems definition in order to benefit from human competencies and capacities while respecting human limits. The main idea is to balance Human and technology involvement, taking advantage of industrial CPS advances and Human capabilities identified and implemented through Human-Machine Cooperation principles. The project HUMANISM, which is presented, aims to specify and experiment such principles.

[1]  Marie-Pierre Pacaux-Lemoine,et al.  Towards Levels of Cooperation , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

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

[3]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[4]  Pascal Berruet,et al.  Using Cognitive Work Analysis to design smart grid interfaces , 2015 .

[5]  Åsa Fast-Berglund,et al.  Towards a Human-Centred Reference Architecture for Next Generation Balanced Automation Systems: Human-Automation Symbiosis , 2015, APMS.

[6]  David A. Abbink,et al.  Shared and cooperative control of ground and air vehicles: Introduction and general overview , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[7]  Mats Winroth,et al.  Aligning manufacturing strategy and levels of automation: A case study , 2010 .

[8]  Marie-Pierre Pacaux-Lemoine,et al.  Human-robot cooperation through brain-computer interaction and emulated haptic supports , 2018, 2018 IEEE International Conference on Industrial Technology (ICIT).

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

[10]  Patrick Millot,et al.  A Common Work Space for a Mutual Enrichment of Human-Machine Cooperation and Team-Situation Awareness , 2013, IFAC HMS.

[11]  Christoph H. Glock,et al.  Human Factors in Order Picking System Design: A Content Analysis , 2015 .

[12]  Paulo Leitão,et al.  Augmented reality experiments with industrial robot in industry 4.0 environment , 2016, 2016 IEEE 14th International Conference on Industrial Informatics (INDIN).

[13]  Damien Trentesaux,et al.  Designing intelligent manufacturing systems through Human-Machine Cooperation principles: A human-centered approach , 2017, Comput. Ind. Eng..

[14]  André Crosnier,et al.  Collaborative manufacturing with physical human–robot interaction , 2016 .

[15]  Marie-Pierre Lemoine.  Coopération hommes-machines dans les procédés complexes : Modèles techniques et cognitifs pour le contrôle de trafic aérien , 1998 .

[16]  Peter Korondi,et al.  Shop-Floor Architecture for Effective Human- Machine and Inter-Machine Interaction , 2012 .

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

[18]  Makoto Itoh,et al.  Towards Vertical and Horizontal Extension of Shared Control Concept , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[19]  Patrick Millot,et al.  Adaptation of the level of automation according to the type of cooperative partner , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[20]  Patrick Millot,et al.  AN APPROACH OF DYNAMICAL ALLOCATION OF SUPERVISION TASKS BETWEEN MAN AND COMPUTER IN CONTROL ROOMS OF AUTOMATIZED PRODUCTION SYSTEMS , 1985 .

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

[22]  Thomas B. Sheridan,et al.  Man-machine systems;: Information, control, and decision models of human performance , 1974 .

[23]  José Barbosa,et al.  Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution , 2015, Comput. Ind..

[24]  Damien Trentesaux,et al.  A Human-Centred Design to Break the Myth of the "Magic Human" in Intelligent Manufacturing Systems , 2015, SOHOMA.

[25]  J M Hoc,et al.  From human – machine interaction to human – machine cooperation , 2000, Ergonomics.

[26]  Carsten Wittenberg,et al.  Human-CPS Interaction - requirements and human-machine interaction methods for the Industry 4.0 , 2016 .

[27]  Mark Mulder,et al.  Haptic shared control: smoothly shifting control authority? , 2012, Cognition, Technology & Work.

[28]  Johan Stahre,et al.  Proactive assembly systems-realising the potential of human collaboration with automation , 2009, Annu. Rev. Control..

[29]  J. Norberto Pires.  Semi-autonomous manufacturing systems: The role of the human–machine interface software and of the manufacturing tracking software , 2005 .

[30]  Johan Stahre,et al.  Levels of automation in manufacturing , 2008 .

[31]  Jean-Michel Hoc.  Planning in Dynamic Situations: Some Findings in Complex Supervisory Control , 2006 .

[32]  Przemysław Oborski,et al.  Man-machine interactions in advanced manufacturing systems , 2004 .

[33]  Fei-yue Wang,et al.  Control 5.0: from Newton to Merton in popper's cyber-social-physical spaces , 2016, IEEE/CAA Journal of Automatica Sinica.

[34]  Marcantonio Catelani,et al.  Context awareness for maintenance decision making: A diagnosis and prognosis approach , 2015 .