Reviewed
Queueing Models for manual order picking systems with blocking
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Prof. Dr.-Ing.
Kai Furmans
Institute for Conveying Technology and Logistics, Department of Mechanical Engineering, Karlsruhe Institute of Technology
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Dipl. Wi.-Ing.
Christian Huber
Institute for Conveying Technology and Logistics, Department of Mechanical Engineering, Karlsruhe Institute of Technology
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Dr.-Ing.
Jens Wisser
Institute for Conveying Technology and Logistics, Department of Mechanical Engineering, Karlsruhe Institute of Technology
Abstract
In many picker-to-part order picking systems with high space utilization, blocking situations occur and lead to productivity losses. On the one hand order pickers cannot pass each other within aisles and cross-aisles, on the other hand they want to access a certain resource of the system, for example a base station, at the same time. Very few papers and articles dealing with this problem are available in the literature and the few approaches only offer limited possibilities of modeling and quantifying. For this reason the Deutsche Forschungsgemeinschaft (DFG) is funding a research project which aims at developing theoretical foundations to understand blocking in manual order picking systems and quantify its effects by means of an analytical model. In this paper we identify queueing theory as a potential modeling method. We show how to transfer a manual order picking system into a queueing model and present applicable solution algorithms. The analysis of an exemplary system shows that blocking situations reduce the productivity of an order picker and that throughput losses can be as high as 10% in typical implementations. For these scenarios we were able to show that the relative error between the queueing model and simulation is below 4%. Therefore queueing theory is suited as a modeling method because compared to simulation, results can be derived fairly easy and in short time.
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Recommended citation
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Furmans K, Huber C, Wisser J (2009). Queueing Models for manual order picking systems with blocking. Logistics Journal, Vol. 01. (urn:nbn:de:0009-14-20926)
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