Abstract
ABSTRACT In an assembly line system, the production process may suffer a sudden disruption, and this may call for rebalancing. In this paper, the assembly line rebalancing problem is set in a multiperiod context considering stochastic processing times. It is assumed that there are specific moments in time chosen for rebalancing the line (if necessary). Two policies, a periodic rebalancing policy and a data-driven rebalancing policy, are proposed to solve the rebalancing problem. The goal is to minimize the total cost, which include production and rebalancing costs. An empirical study is conducted, and several results are achieved: rebalancing an assembly line is sometimes worse than not rebalancing it; rebalancing an assembly line too often may not be beneficial; and the new data-driven policy introduced is better than the plain multiperiod policy.
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