Multi-Objective Optimization of a Cost-Effective Modular Reconfigurable Manufacturing System: An Integration of Product Quality and Vehicle Routing Problem

Abstract

A reconfigurable manufacturing system offers several manufacturing routes to produce the same product. Each manufacturing route considers different production, reconfiguration, and module changing time which can potentially impact the delivery time of a product to the customer location. This study considers the impact of different reconfigurable manufacturing routes and quality concerns on the efficiency of a vehicle routing problem. The reconfigurable manufacturing system produces different products while the vehicle routing problem distributes the products to different customer locations. The analysis is conducted by using two important reconfigurable manufacturing system characteristics i.e., modularity and scalability, to assess their impact on manufacturing and supply chain systems. A multi-objective model containing the objectives of the total cost, the total time, the scalability, and the modularity is proposed to analyze the problem. The model is subsequently implemented by using a two-phased meta-heuristic approach using automatic calibration. In the first phase, production analysis is examined by using different reconfigurable machines through the application of a non-sorting genetic algorithm embedded with an absorption policy and multiple crossover operators based on simulated annealing. The second phase considers the delivery of products to different customer locations through the application of a variable neighborhood search approach.

Keywords

• Modularity
• non-sorting genetic algorithm
• optimization
• quality variation
• reconfigurable manufacturing system
• scalability