Comparison of two optimization based order release models with fixed and variable lead times

Manufacturing planning and control systems ideally seek to simultaneously achieve short and predictable flow times as well as high output and due-date performance. One approach to address this problem is the workload control concept. It is based on the idea to control lead times by controlling order releases and thus the level of work-in-process and output. The focus of this paper is on multi-period optimization models for order release planning. We use a simulation study of a make to order manufacturer in a rolling horizon setting and compare the performance of an order release model that assumes fixed lead times and a model that allows for variable lead times: An input output control and a clearing function model, respectively. We analyze two different approaches to cope with the varying and tight due date slack and find that including more foreknowledge of demand is preferable. Finally, we show that the clearing function model outperforms the input output control model in all scenarios by yielding lower inventory levels with shorter shop floor throughput times. This advantage seems not to be affected by the predictability of the demand, but the IOC model narrows the gap when using near optimal parameters especially for a scenario with deterministic demand.