A cell formation algorithm for sequential processes with alternative machine selection in the automotive lighting industry

Victor Manuel Loya Garnica, University of Texas at El Paso

Abstract

At the present time, there are more than 12 big companies dedicated to design and produce OEM lighting systems for cars and trucks. The manufacturing processes for headlamps, tail lamps and any other exterior vehicle lighting are very common in the auto industry. Still, every automotive lamp assembly is different from brand to brand and even between the different vehicle models. Indeed, there are car headlamps with less than 30 sub-components and others with up to 300 elements. This implies creating diverse part numbers which share or hold varying manufacturing methods within a specific facility. Management of the plant resources becomes highly challenging when the parts to be created and the machines to be operated are not organized in family groups. A great amount of time and effort has to be invested in production planning related to associating parts to machines. Consequently, the foundation of Group Technology (GT) has to be utilized with the purpose of dividing a relatively large system into smaller and more-manageable manufacturing cells. However, existing GT methods have not shown a practical application in the target scenario. This study pretends to find a better approach to the concept of GT throughout the use of a customized cell formation algorithm for the automotive lighting field or any other area that may be pertained.^

Subject Area

Engineering|Industrial engineering

Recommended Citation

Loya Garnica, Victor Manuel, "A cell formation algorithm for sequential processes with alternative machine selection in the automotive lighting industry" (2015). ETD Collection for University of Texas, El Paso. AAI10000820.
http://digitalcommons.utep.edu/dissertations/AAI10000820

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