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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/22144

Title: Linear constraint programming for cost-optimized configuration of modular assembly systems
Authors: Anandan, Paul Danny
Hiwarkar, Vikrant
Sayed, Mohamed S.
Ferreira, Pedro
Lohse, Niels
Keywords: Configuration
Modular Equipment
Assembly Systems
Issue Date: 2016
Publisher: © The Authors. Published by Elsevier
Citation: ANANDAN, P.D. ...et al., Linear constraint programming for cost-optimized configuration of modular assembly systems. Procedia Cirp, In Press.
Abstract: In this paper, we develop an optimization model for providing a logical layout for reconfigurable assembly systems from a library of available equipment modules. The design problem addresses the challenges in equipment selection to build workstations and subsequently the entire assembly system. All the available equipment modules are assumed to be modular and each of them retains a subset of skills (capabilities). The set of all available equipment modules, their skills, mode of physical connectivity (ports) and costs are known. The objective is to minimize the overall equipment cost without violating their physical connectivity (ports) constraints and the precedence constraints of the assembly process requirements. The analysis of the problem and the state-of-art review steered us to the following: (1) the design problem is very closely related to the assembly line balancing problems; (2) a few Genetic Algorithm (GA) based approaches are already available for the capital cost optimization of multi-part flow-line (MPFL) configurations that includes the operational precedence constraints; (3) to our knowledge, this is the first work to combine the equipment physical connectivity constraints with task precedence in order to provide a valid and optimal configuration solution. A formalized mathematical model is developed to select suitable subsets of equipment modules and group them into workstations to construct an optimal logical layout. A number of scenarios based on an industrial case study are simulated and the results are analysed to evaluate the performance of the proposed models.
Description: This paper is in closed access until it is published. It was presented at the 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016), Stuttgart, Germany, May 25-27th.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/22144
Publisher Link: http://www.sciencedirect.com/science/journal/22128271
ISSN: 2212-8271
Appears in Collections:Closed Access (Mechanical, Electrical and Manufacturing Engineering)

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