Performance analysis of a palletizing system

Rapport

Amstel, van, M.F., Plassche, van de, E., Hamberg, R., Brand, van den, M.G.J. & Rooda, J.E. (2007). Performance analysis of a palletizing system. (SE report, No. 2007-09). Eindhoven: Technische Universiteit Eindhoven, 60 pp. Lees meer: Medialink/Full text

Abstract

 

When designing the layout of the material handling system for a warehouse there is a need for the analysis of overall system performance. Since warehouses are typically very large and complex systems it is infeasible to build a simulation model for the entire system. Our approach is to divide the system into subsystems that are small enough to be captured in simulation models. These models can then later be assembled to acquire a simulation model of the entire system. In this case study we assess the feasibility of this approach by creating a simulation model of a part of a warehouse and verify whether it can be used to embed it in a larger simulation model. The subsystem we use for our case study is a container unloading and automatic palletizing system. This system is chosen because it has already been studied extensively using another simulation tool. We also do a performance analysis of this system in order to come to an optimal layout for this subsystem as well as to reproduce the results of the earlier study for validation. For our performance analysis we created a chi model of the unloading and palletizing area. The process algebra chi has been extensively used for modeling and simulation of real-time manufacturing systems. Our case study is also used as a means to assess the suitability of chi for modeling and simulation in a logistics environment. Our experiments resulted in roughly the same outcomes as the earlier study. It turns out that for the required throughput the layout chosen in that study is optimal. We also concluded that chi is perfectly suitable for modeling logistic systems. Considering the extensive time it takes to run simulations of a rather small part of a warehouse using chi, we conclude that it is infeasible to perform simulations of entire warehousing systems by integrating the simulation models of all subsystems into one simulation model. To overcome this problem, aggregate modeling can be used.