GKN Aerospace (formerly Volvo Aero) has invested in a complex production cell containing a set of multipurpose machines. The problem of finding optimal schedules for this so-called multitask cell is a complex combinatorial optimization problem which is recognized as a flexible job shop. In the talk, we present the scheduling problem and compare the results from two mathematical optimization models utilizing different variable definitions. For one of the models, an iterative procedure has been developed that solves the time-indexed model for iteratively smaller time steps, i.e., with increasingly better accuracy. The scheduling problem includes a limited availability of fixtures and preventive maintenance planning. Computational results show that with the method developed we are able to produce optimal, or near-optimal, schedules for real data instances within an acceptable time frame. The scheduling principle proposed shortens lead times and minimizes tardiness.

Information about the speaker:
Karin Thörnblad is an industrial PhD student at the department of Mathematical Sciences at Chalmers University of Technology. Karin started as trainee at Volvo Aero in 1996, and has had positions as technical responsible for the afterburner of the Gripen engine, assistant manager in production, and project leader of several logistics projects. Karin started her PhD studies in applied optimization in 2008.