Line feeding optimization for Just in Time assembly lines: An application to the automotive industry

• Published in: International journal of production economics 2016-04, Vol.174, p.54-67
• Main Authors: Sali, Mustapha, Sahin, Evren
• Format: Article
• Language: English
• Subjects: Assembly; Assembly lines; Automobile industry; Automobiles; Automotive components; Automotive engineering; Automotive industry; Business administration; Costs; Engineering Sciences; Feeding; Humanities and Social Sciences; In-plant logistics; Integer programming; Just in time; Kitting; Line feeding; Line stocking; Material handling; Mathematics; Optimization techniques; Sequencing; Studies
• ISSN: 0925-5273; 1873-7579
• DOI: 10.1016/j.ijpe.2016.01.009

The performance of mixed-model assembly lines used in sectors such as the automotive industry depends on the availability of a large number of components that have to be supplied to the line on time and at minimum cost. In such settings, components may have different features such as volume, weight, bill of material coefficient, etc. Additionally, a given component may have several alternative variants among which a single one is used in the assembly of end products. Each variant is thus characterized by a varying degree of usage rate. Hence, the diversity of parts requires the selection of the best assembly line feeding mode that aims at minimizing the average total operating cost which mainly consists of labor costs associated with parts preparation before assembly, transportation to the line, picking operations during assembly, as well as parts storage cost. This paper proposes an optimization model that assigns each individual component to the most efficient line feeding mode among three alternatives which are line stocking, kitting and sequencing modes. The developed mixed integer program is applied to a first tier supplier plant in the automotive sector. Based on this model, insight is gained on the trade-off to be considered when deciding the more appropriate line feeding mode for each individual component and how system parameters impact this trade-off.