The impact of product variety on automobile assembly operations: Empiricalevidence and simulation analysis

Citation
Ml. Fisher et Cd. Ittner, The impact of product variety on automobile assembly operations: Empiricalevidence and simulation analysis, MANAG SCI, 45(6), 1999, pp. 771-786
Citations number
26
Categorie Soggetti
Management
Journal title
MANAGEMENT SCIENCE
ISSN journal
00251909 → ACNP
Volume
45
Issue
6
Year of publication
1999
Pages
771 - 786
Database
ISI
SICI code
0025-1909(199906)45:6<771:TIOPVO>2.0.ZU;2-F
Abstract
This study examines the impact of product variety on automobile assembly pl ant performance using data from GM's Wilmington, Delaware plant, together w ith simulation analyses of a more general auto assembly line. We extend pri or product variety studies by providing evidence on the magnitude of variet y-related production losses, the mechanisms through which variety impacts p erformance, and the effects of option bundling and labor staffing policies on the costs of product variety. The empirical analyses indicate that great er day-to-day variability in option content (but not mean option content pe r car) has a significant adverse impact on total labor hours per car produc ed, overhead hours per car produced, assembly line downtime, minor repair a nd major rework, and inventory levels, but does not have a significant shor t-run impact on total direct labor hours. However, workstations with higher variability in option content have greater slack direct labor resources to buffer against process time variation, introducing an additional cost of p roduct variety. The simulation results support these findings in that once each;workstation is optimally buffered against process time variation, prod uct variety has an insignificant impact on direct assembly labor. The simul ations also show that bundling options can reduce the amount of buffer capa city required, and that random variation is more pernicious to productivity than product variety, supporting the efforts of some auto makers to aggres sively attack the causes of random variation.