Sub-assembly detection and line balancing using fuzzy goal programming approach

Rifat G. Ozdemir, Ugur Cinar, Eren Kalem and Onur Ozcelik

International Journal of Data Analysis Techniques and Strategies, 2016, vol. 8, issue 1, 65-86

Abstract: This study suggests a mathematical modelling approach to sub-assembly detection and assembly line balancing problems. The sub-assembly detection problem involves two issues as follows: 1) determine which components of products are assembled in sub-assembly area; 2) determine which components of the products are assembled directly in the line. In assembly line balancing problem tasks are assigned to the workstations. The main motivation of this study is to determine the best compromised assembly line structure by solving the sub-assembly detection and the line balancing problems jointly. A multi-objective mathematical model is developed to formulate the above mentioned problems in which two conflicting costs of sub-assembly generation and assembly line labour cost are involved. Since the applications in real life are imprecise, fuzzy goal programming is adapted to the developed model to determining the vague goal. Then the model is implemented in a real life automotive manufacturers assembly line balancing.

Keywords: sub-assembly detection; assembly line balancing; ALB; fuzzy goal programming; FGP; alpha cut; mathematical modelling; fuzzy logic; automotive manufacturing; automobile industry. (search for similar items in EconPapers)
Date: 2016
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