Two-level manufacturing system performance analyser

Open queuing network is a commonly used analytical tool for modelling manufacturing systems. Parametric decomposition is a proven solution method for analysing open queuing networks and can estimate key performance measures such as work-in-process inventory, cycle time, and machine utilisation, fairly accurately. This paper presents a two-level hierarchical open queuing network model, which considers numerous features seen in a real manufacturing system including, machine set-up, material handling device setup (for example, loading and unloading operations), process as well as transfer batching, empty travel of the material handling device and machine or material handling device failures. The model first analyses a higher level open queuing network whose nodes are aggregations of a set of machines. The higher level network is solved via the parametric decomposition method and the results are then disaggregated to get lower level, e.g. machine specific, results. The motivation, algorithm and its relationship with the one-level model are discussed. Experimental results are provided to show that the two-level model provides comparable results with the one-level model in addition to its computational and managerial advantages. In addition, both are shown to provide better results than a recent method available in the literature that is based on the well-known queuing network analyser.