A three-step approach for decision support in operational production planning of complex manufacturing systems

Abstract

In this paper, a practical relevant operational production planning problem in complex manufacturing systems is addressed. In this problem, lots are planned individually to provide a more detailed plan than approaches that only consider production quantities. A three-step approach, which is currently fully integrated and used in a Decision Support System, is then introduced. This work follows the one of Mhiri et al. [2018. “Heuristic Algorithm for a WIP Projection Problem at Finite Capacity in Semiconductor Manufacturing.” IEEE Transactions on Semiconductor Manufacturing 31 (1): 62–75] who addressed this problem. We push the approach a step further by introducing new optimisation possibilities through new smoothing rules, whose performance is studied according to different indicators. Furthermore, we present the production planning process in which the decision support tool is embedded and how it bridges the gap between the upper and lower planning levels.

Keywords:

• Production planning
• complex manufacturing systems
• semiconductor manufacturing
• heuristic
• optimisation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data used in this article have been anonymised and can be made available on request.

Additional information

Funding

This work has been partially financed by the ANRT (Association Nationale de la Recherche et de la Technologie) through the PhD number 2016/0421 with CIFRE funds and a cooperation contract between STMicroelectronics and Mines Saint-Etienne.

Notes on contributors

Quentin Christ

Quentin Christ is an engineer working at STMicroelectronics. He received in 2020 his Ph.D. degree in Industrial Engineering from the Ecole Nationale Supérieure des Mines de Saint-Étienne. His email address is [email protected].

Stéphane Dauzère-Pérès

Stéphane Dauzère-Pérès is Professor at Mines Saint-Etienne in its site of Gardanne, France, and Adjunct Professor at BI Norwegian Business School, Norway. He received the Ph.D. degree from Paul Sabatier University in Toulouse, France, in 1992 and the H.D.R. from Pierre and Marie Curie University, Paris, France, in 1998. He was a Postdoctoral Fellow at M.I.T., U.S.A., in 1992 and 1993, and Research Scientist at Erasmus University Rotterdam, The Netherlands, in 1994. He has been Associate Professor and Professor from 1994 to 2004 at the Ecole des Mines de Nantes, France. His research interests broadly include modelling and optimization of operations at various decision levels (from real-time to strategic) in manufacturing and logistics, with a special emphasis on production planning (lot sizing) and scheduling, on semiconductor manufacturing and on railway operations. He has published 96 papers in international journals and has contributed to more than 200 communications in national and international conferences. Stéphane Dauzère-Pérès has coordinated numerous academic and industrial research projects, including 4 European projects and 30 industrial (CIFRE) PhD theses, and also eight conferences. He was runner-up in 2006 of the Franz Edelman Award Competition, and won the Best Applied Paper of the Winter Simulation Conference in 2013 and the EURO award for the best theory and methodology EJOR paper in 2021. His email address is [email protected].

Guillaume Lepelletier

Guillaume Lepelletier is an expert in Semiconductor Manufacturing who has worked 2 decades at STMicroelectronics in Crolles (France). in manufacturing science at the frontier between operational management, industrial engineering and data science. He is the co-funder and CTO of Kheoos, a solution for manufacturer seeking to optimise the cost of their stock of maintenance parts while minimising the risk of shortage. His email address is [email protected].