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Managing design project flows in design office.

PHD Director : Eric Blanco   -   MCF HDR - GSCOP - Grenoble INP Industrial Engineering

Co-director : Jean Philippe Gayon professor - LIMOS / ISIMA Université Clermont Auvergne

Co-advisor : Pierre Chévrier   Associate professor from industry

PhD School : IMEP 2

Start date : Sept 2018


Keys words  :

1 -   Product Development                                      2 - Queuing  theory     

3 -  Behavioral operations                                       4 -  operations management

5 -  Project management                                          6 - lean engineering

 

Thesis  overview :

Performance of design processes and engineering project is a stake and challenge in many industries.  Design office Managers have to warranty project to be on time while resources are limited, uncertainty is very high.

Added value on project had been shown to be limited to 10 to 15% of time project delivery (Oehmen & Rebentisch 2010). These figures highlight that major productivity improvements are possible. New organization as lean development practices had been implemented to tackle these challenges (Khan et al. 2013; Morgan & Liker 2006; Reinertsen 2009). Among possible actions, multi skilled designers, short feedback, limited project portfolio, rapid prototyping are recommended by literature (Reinertsen 2009; Mascitelli 2011). But design office manager have no tools to simulate or evaluate expected performance and to support them in decision making which can fit with their specific context.

Within academic literature, constraint theory had been used in project management to improve project performance (Leach 1999; Newbold 1998) but has not lead to decision support tools. Recently new approaches had shown the potential of manufacturing simulation models like queuing theory to simulate and describe impact of organizations in projects (Beauregard et al. 2016; Bai et al. 2015). But these models don’t take into account the designer’s behavior which is critical in the case of engineering projects. Bendoly et al (2010) highlight that operations management simulations poorly integrate human behavior in the models whereas knowledge from cognitive or social sciences are available. In design project management for example impact of multitasking and interruptions (Mark et al 2008) , or Parkinson law (newbold1998) had been proven to be of importance. Such models can be integrated in behavioral operations. The objective of this Phd is to propose decision support tools and models integrating designer’s behavior for managers to optimize projects organizations

This Phd Project will benefit from an interdisciplinary research team of advisors with simulation expertise and design organization and activity back ground. It will contribute to this emergent field of research with a high potential.

 

Bibliography

Anderson, N. et al., 2001. Handbook of Industrial, Work and Organizational Psychology. Personnel Psychology. Volume 1, SAGE Publications.

Bai, J., So, K.C. & Tang, C., 2015. A queueing model for managing small projects under uncertainties. European Journal of Operational Research, 253(3), pp.777–790. Available at: http://dx.doi.org/10.1016/j.ejor.2016.02.052.

Bakker, A.B. & Leiter, M.P., 2010. Work engagement A handbook of essential Theory and Research, Psychology Press.

Beauregard, Y. et al., 2016. Optimal utilisation level for lean product development in a multitasking context. International Journal of Production Research, 7543(March), pp.1–24.

Bendoly, E. et al., 2010. Bodies of knowledge for research in behavioral operations. Production and Operations Management, 19(4), pp.434–452.

Khan, M.S. et al., 2013. Towards lean product and process development. International Journal of Computer Integrated Manufacturing, 26(12), pp.1105–1116.

Leach, L.P., 1999. Critical chain project management improves project performance. Project Management Journal, 30(2), pp.39–51.

Mark, G., Gudith, D. & Klocke, U., 2008. The Cost of Interrupted Work : More Speed and Stress. In CHI 2008: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. pp. 107–110.

Mascitelli Ronald, 2011. Mastering Lean Product Development. A practical Event-Driven Process for Maximizing SPeed Profits, and Quality., Technology Perspectives.

Morgan, J.M. & Liker, J.K., 2006. The Toyota Product Developement System: Integrating People Process and Technology, New York: Productivity press.

Newbold, R.C., 1998. Management in the Fast Lane Applying the Theory of Constraints, CRC press Taylor & Francis Group.

Oehmen, J. and Rebentisch, E., 2010a. Waste in Lean Product Development [online]. Cambridge, MA, The Lean Aerospace Initiative.

Reinertsen, D.G., 2009. The principles of Product Development Flow. Second Generation Lean Product Development., Celeritas Publishing.

 

Candidate Profile :

Degree in Industrial Engineering and Management, operations management with engineering background or equivalent.

Experiences in engineering projects within  industry will be a must (internship or others)

Programming skills, modeling and Simulation skills, queuing theory

Interest and/or experiences in interdisciplinary works with social sciences or cognitive sciences or psychology or cognitive ergonomics.

Dynamic

French speaker  : B2

English speaking  :   C1

 

Contacts :

Eric Blanco   -   MCF HC HDR

 Jean Philippe Gayon Prof LISMOS/ ISIMA Université Clermont Auvergne

 Pierre Chévrier   PAST GSCOP Génie industriel

Date of update March 19, 2018

Univ. Grenoble Alpes