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.
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