THE THIRD INTERNATIONAL WORKSHOP OF THE IFIP WG 5.7 SPECIAL INTEREST GROUP ON "ADVANCED TECHNIQUES IN PRODUCTION PLANNING & CONTROL"

– The authors propose an analytic-simulation hybrid model (HM) to solve a lot sizing and scheduling problem in a multi-product/dynamic demand/single machine environment. Problem complexity is increased due to sequence dependent and relevant setup times as well as to stochastic variability of both process and setup times. Resource availability is also considered in evaluating capacity at each period of the planning horizon. The analytic model consists of a mixed integer linear programming model obtained by improving a model available in literature; it interacts with a simulation model in order to meet a production plan that allows minimizing an economic objective function. The approach tries to overcome traditional limits of both analytic and simulation models as each of them fails in jointly capturing system complexity and searching for optimal solutions. HM proposed is applied to a case study. It concerns with production of braking systems components for automotive industry. Results obtained are compared with those that could have been obtained if only the analytic model adopted in HM was used. Comparison outlines capabilities of HM in facing problem complexity as it is able to evaluate stochastic dependency among manufacturing variables; such a dependency is neglected by analytic models. Moreover, the iterative procedure adopted in HM reveals an effective tool in searching for a good production planning avoiding expensive and low effective “trial and error” procedures required by simulation to meet the same goal when a relevant number of decision manufacturing variables occurs in a production planning problem in cases of full scale industrial cases.