Optimization of workcell layout for hybrid medical device fabrication. (January 2019)

• Record Type: Journal Article
• Authors: Ho, Nicholas; Ngooi, Syn-Dee; Chui, Chee-Kong
• Is Part Of: Journal of manufacturing systems. Volume 50(2019)
• Page Start: 163
• Page End: 179
• Publication Date: 2019-01
• Subjects: Multi-objective combinatorial optimization -- Workcell layout -- Virtual manufacturing technology -- Medical devices; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2018.12.010
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Manufacturers often overlook the importance of optimizing manufacturing workcell layout. An accurate, practical and implementable methodology was proposed to optimize workcell layout. Multi-objective combinatorial optimization (MOCO) concepts were utilized. Evaluation results from simulated virtual manufacturing workcells proved the feasibility and effectiveness of the proposed model. The potential of the proposed model in improving manufacturing efficiency was highlighted. Abstract: Manufacturers often overlook the importance of optimizing workcell layout. Optimizing manufacturing workcell layouts can help increase production efficiency by reducing unnecessary actions and movements. However, the application of conventional optimization methods to modern production lines is not only becoming too complex, but also becoming inaccurate and unreliable. In this paper, we proposed an accurate and practical methodology that is readily implementable. The methodology uses multi-objective combinatorial optimization (MOCO) concepts to optimize manufacturing workcell layouts, specifically for the production of hybrid medical devices. The proposed model, also known as the Two-Step MOCO model, considers objectives and constraints that are selected by the manufacturer. The first step determines the optimal number of equipment and operators required given a fixed budget, while the second step determines the optimal positions for every equipment, given a fixed space and the required safety distance among each equipment, after considering the results of the first step. We illustrated the implementation of the proposed model on the fabrication of a hybrid medical device. Virtual manufacturing workcells were developed and utilized to evaluate the proposed methodology. The evaluation results proved the feasibility and effectiveness of the proposed model, and its ability to provide flexibility to manufacturers. This paper highlights the potential of our proposed optimization model in improving production efficiency in medical device and other manufacturing industries.