Process Planning, Scheduling, and Layout Optimization for Multi-Unit Mass-Customized Products in Sustainable Reconfigurable Manufacturing System

Sini Gao, Joanna Daaboul and Julien Le Duigou
Additional contact information
Sini Gao: Roberval (Mechanics, Energy and Electricity), Centre de Recherche Royallieu, Université de Technologie de Compiègne, CEDEX, CS 60319, 60203 Compiègne, France
Joanna Daaboul: Roberval (Mechanics, Energy and Electricity), Centre de Recherche Royallieu, Université de Technologie de Compiègne, CEDEX, CS 60319, 60203 Compiègne, France
Julien Le Duigou: Roberval (Mechanics, Energy and Electricity), Centre de Recherche Royallieu, Université de Technologie de Compiègne, CEDEX, CS 60319, 60203 Compiègne, France

Sustainability, 2021, vol. 13, issue 23, 1-24

Abstract: Currently, manufacturers seek to provide customized and sustainable products, requiring flexible manufacturing systems and advanced production management to cope with customization complexity and improve environmental performance. The reconfigurable manufacturing system (RMS) is expected to provide cost-effective customization in high responsiveness. However, reconfiguration optimization to produce sustainable mass-customized products in RMS is a complex problem requiring multi-criteria decision making. It is related to three problems, process planning, scheduling, and layout optimization, which should be integrated to optimize the RMS performance. This paper aims at integrating the above three problems and developing an effective approach to solving them concurrently. It formulates a multi-objective mathematical model simultaneously optimizing process planning, job-shop scheduling, and open-field layout problem to improve RMS sustainability. The penalty for product tardiness, the total manufacturing cost, the hazardous waste, and the greenhouse gases emissions are minimized. Economic and environmental indicators are defined to modify the Pareto efficiency when searching the Pareto-optimal solutions. Exact Pareto-optimal solutions are obtained by brute-force search and compared with those of the non-environmental indicator model. NSGA-III is adopted to obtain the approximate Pareto-optimal solutions in high effectiveness and efficiency. A small numerical example is applied to validate the mathematical model and resolution methods.

Keywords: reconfigurable manufacturing system; mass customization; process planning; scheduling; layout; environmental sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/23/13323/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/23/13323/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:23:p:13323-:d:692964

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().