Jwch Jeremy Visschers

Analysis of assembly systems with service level constraints

In this paper we propose a decomposition method for general assembly systems, that decomposes the assembly network into purely divergent multi-echelon systems. The key idea behind the method is to pre-allocate common components to (sets of) end-products. The decomposition method is inspired by Roslings proof of the equivalence of pure assembly systems and serial multi-echelon systems. For the divergent multi-echelon systems it is possible to calculate near-optimal order-up-to-levels satisfying a fill rate constraint. These order-up-to-levels are then used in the original assembly system. We restrict detailed analysis to assembly systems that decompose into series inventory systems. Using discrete event simulation we compare our pre-allocation policies with several commonly used allocation policies. These allocation policies distribute the common components at the latest possible moment among orders of the subassemblies and end-products that use them. The simulation experiments show that the pre-allocation policies perform quite well compared to the allocation policies, both with respect to costs and service.

The impact of material coordination concepts on planning stability in supply chains

The goods flows in supply chains can be managed based on either the purchase orders of the next company in the chain or on the demand information from the end customer in the total supply chain. Many standard software packages which are meant for controlling goods flows are based on the purchase orders of their immediate customers (in accordance with the MRP logic). In this paper it is investigated how the type of demand information used influences the stability of the planning in the supply chain. For this purpose a simulation experiment was set up, using data from a truck manufacturer in the Netherlands. This company was confronted with the choice to either stick to its own planning logic (based on undistorted demand information from the end of the supply chain) or to change over to a standard package based on the MRP-logic. This experiment reveals how instable the planning in a supply chain may become if the wrong demand information is being used. The experiment also shows which factors in the production environment as well as in the market place have the biggest impact on the instability of the planning. The results were discussed with the development department of a major software company. Based on the results the software company is now considering to adapt the planning logic in their standard software package.