Optimization framework for process scheduling of operation-dependent automobile assembly lines
Productivity, cost, and completion time are regarded as performance measures for assembly production management. The traditional decomposition of Assembly Line Balancing (ALB) and Car sequencing (CS) does not work well, especially when operations belonging to different car types are sequence-dependent and time overlap between two successive workstations is allowed. In this paper, we first use a motivating industrial-scale example to demonstrate that the traditional ALB/CS decomposition method could not satisfy modern continuous production demands in a flexible assembly line. Then, we present a new optimization objective to scale the Operation Process Precision (OPP) that relates to the operation assignment sequence. Lastly, we propose a two-stage hierarchical optimization framework to solve the CS, the operation allocation, and the operation sequence problems. This framework consists of (a) a new Mixed Integer Linear Programming (MILP) model for sequencing automobiles and allocating their operations to each station, and (b) a novel MILP model for determining the operation sequence and timing of each car type. The motivating industrial case is revisited with the proposed framework to illustrate its validity and efficiency.
KeywordsOperation Process Precision (OPP) Mixed-model assembly line Operation assignment Car Sequencing (CS) Assembly Line Balancing (ALB) Continuous manufacturing Mixed Integer Linear Programming (MILP)
Unable to display preview. Download preview PDF.
- 2.Larkin J.: The 1,000,000th vehicle produced at BMW manufacturing Co. in spartanburg automotive industries. Automot. Ind. 186, 55 (2006)Google Scholar
- 5.Hazbany, S., Gilad, I., Shpitalni, M.: About the efficiency and cost reduction of parallel mixed-model assembly lines. The 17th CIRP Design Conference, Berlin, Germany, March 27–28 (2007)Google Scholar
- 6.Matanachai S., Yano C.A.: Balancing mixed-model assembly lines to reduce work overload. IIE Trans. 33, 29–42 (2001)Google Scholar
- 39.Li J., Karimi I.A., Srinivasan R.: Recipe determination and scheduling of gasoline blending operations. AIChE J. 56, 441–465 (2010)Google Scholar
- 42.Brooke A., Kendrick D., Meeraus A., Raman R.: GAMS: A User’s Guide. GAMS Development Corporation, South San Francisco (2003)Google Scholar