Authors:
Davide Giglio
and
Massimo Paolucci
Affiliation:
University of Genova, Italy
Keyword(s):
Remanufacturing, Production Planning, Mixed-Integer Programming Modelling.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Formal Methods
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Manufacturing Systems Engineering
;
Optimization Algorithms
;
Planning and Scheduling
;
Production Planning, Scheduling and Control
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
This paper considers a hybrid remanufacturing and manufacturing system on a closed-loop supply chain. The system manufactures a set of new products characterized by a multi-level structure through multi-stage assembly operations. The required raw or basic parts can be acquired new from suppliers or provided as new by a de-manufacturing facility which performs a remanufacturing process from acquired old products returned by customers. The quality of returned products has impact on the quantity of recovered basic parts which can be assumed as good as new, and on the duration of the remanufacturing process. The considered problem is to determine the production lots for the system machines as well as the quantity of new basic parts and retuned products to be acquired in order to satisfy a deterministic demand in the time buckets of the planning period. The performance criterion to be minimized includes the acquisition costs for the new and returned items, inventory and production costs,
recovering and disposal costs, and tardiness costs. A mixed-integer programming model is proposed and its effectiveness is demonstrated by experiments on a case study.
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