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Steering developments in Industry 4.0 through risk management (F-MECA), information systems and knowledge management (C-K)

Steering developments in Industry 4.0 through risk management (F-MECA), information systems and knowledge management (C-K)



PhD supervisor : Prof. Michel TOLLENAERE

Doctoral school : IMEP 2

Starting date : 1st October 2018

Fundings : Grant from IMEP2

 Project development : 

Key words : Industrial Information Systems, Project Risk Management, FMEA, C-K theory, lean manufacturing. 

In the world of Industry 4.0 and the Internet of Things - Multi-applications, Multi-products, Multi-technologies & Multi-expertise - where the dynamics of innovation are intensive and the evolution of products, technologies, areas of expertise and processes of industrialization very quick, designers and performers face a new challenge in terms of industrial engineering: the design of digital tools adapted to a dynamic transmission of knowledge and knowledge -make.

Numerous studies have recently been conducted within the SIREP team to make risk analyzes dynamic [Mili 09], to control product non-conformities [Fiegenwald 13], to define overall acceptable levels of risk with the concept of M@R [Bettayab 12] and steer control plans, assist in the diagnosis of failures using Bayesian networks in multi-product, multi-equipment environments [BenSaid 15].

Industry 4.0 presents us today with the challenge of putting in place a global approach allowing a consistent policy merging Industrial Information Systems (UML), risk management (FMEA) and Knowledge Management - skills (CK theory) in a very dynamic way. As examples, today at ST, six Master's trainees are engaged in ways of continuous improvement : this thesis will use these studies as examples in order to release methodologies to pilot this nature of study by measuring performance in terms of impact on skills. LECTRA is facing the migration of its software offer towards the "cloud" while minimizing the risks for its customers.

The research issue associated with this thesis could be formulated as follows :

       How to design industrial engineering tools in an innovative industrial environment by bridging "knowledge - skills" and individual/collective risks (FMEA)?

The expected contributions of this type of tool to address current and future operational challenges and objectives in a 4.0 context are:

       Participate in the design and implementation of new forms of collective action to support an industrial environment in permanent "crisis".

       Participate in the dynamic spread of a culture of risk and prevention, both of which are constantly evolving.

 

Two industrial partners who are very involved with their customers in Industry 4.0 pledge to support this research action: LECTRA (www.lectra.com), leader in its market of suppliers of solutions for textile and leather cutting, ST Microelectronics leader global market for electronic components (chips). ST provides smart products and solutions that consume little energy and are at the heart of the electronics that everyone uses today. ST's products are everywhere, and with our customers, we help make driving, factories, cities and homes smarter and develop new generations of mobile devices and the Internet of Things. ST is at the forefront of technological innovation, with around 7,500 people working in R & D, both in terms of its products and its 4.0 production processes.

 Short bibliography

o   Hamidreza Pourzarei, Michel Tollenaere, Samuel Bassetto &al (2018) An optimization method of project control plan for considering uncertainty, soumis au Journal of Project Management.

o   Cabanes, B. (2017). Modéliser l’émergence de l’expertise et sa gouvernance dans les entreprises innovantes : des communautés aux sociétés proto-épistémiques d’experts Doctoral dissertation, MINES ParisTech – PSL Research University. https://hal.archives-ouvertes.fr/tel-01565628/document

o   Anis Ben Said, Muhammad Kashif Shahzad, Éric Zamaï, S. Hubac, Michel Tollenaere. Experts' Knowledge Renewal and Maintenance Actions Effectiveness in High-Mix Low-Volume Industries, Using Bayesian Approach, Cognition, Technology and Work, Springer Verlag, 2015, pp.20

o   Aleddine Zouari, Michel Tollenaere, Ben Habib, Y Aref. Domain knowlege versioning and aggregation mechanisms in product design processes, Concurrent Engineering: Research and Applications, SAGE Publications, 2015, pp.1 ; 12

o   M'Hammed Sahnoun, Belgacem Bettayeb, Samuel Bassetto, Michel Tollenaere. Simulation-based optimization of sampling plans to reduce inspections while mastering the risk exposure in semiconductor manufacturing, Journal of Intelligent Manufacturing, Springer Verlag (Germany), 2014

o   Valérie Fiegenwald, Samuel Bassetto, Michel Tollenaere Controlling non-conformities propagation in manufacturing. International Journal of Production Research, Taylor & Francis, 2013

o   Aymen Mili, Samuel Bassetto, Ali Siadat, Michel Tollenaere. Risks management unveil productivity improvements Journal of Loss Prevention in the Process Industries, Elsevier, 2009, 22 (1), pp.25-34

o   PMBok chapter 11, Risks management in projects, www.pmi.org

Contact(s) : Michel.Tollenaere@grenoble-inp.fr

 

Date of update March 16, 2018

  • Tutelle CNRS
  • Tutelle Grenoble INP
  • Université Joseph Fourier
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Univ. Grenoble Alpes