….How to design a flow line with unreliable machines
Prof Gudrun Kiesmuller presented her research at the LCL on Wed. 9 May 2018 as a visiting professor.
Prof Gudrun Kiesmuller is a professor for operations management at the Faculty of Economics and Management at the Otto-von-Guericke University in Magdeburg.
Here is the abstract of her paper “The influence of spare parts provisioning on buffer size in a production system”, published in IISE Transactions.
Manufacturing systems consist of several machines often connected with material flow systems. If machines are subject to failures and breakdowns, then often buffers are installed to decouple the machines and to avoid a production stop of the whole system.
In this paper, Prof Gudrun Kiesmuller and her coauthor Julia Zimmermann, additionally allow stock keeping of spare parts in order to enable fast repairs. As a consequence, machine availability as well as the isolated production rate is increased, which results in a larger throughput.
They model the system as a Markov Chain to enable the computation of the steady state probabilities and all relevant performance measures. Further, they also present an approximation to compute optimal system designs fast.
They investigate the interrelation between spare parts provisioning and buffer size and show how the optimal system design depends on the cost for spare parts and the cost for buffer places. If the same parts are responsible for the failures in all machines, then spare part provisioning is getting more attractive due to the pooling effect.
Gudrun P. Kiesmüller holds the chair of operations management at the Otto-von-Guericke University in Magdeburg (Germany). She obtained her Ph.D. in mathematics from the Julius-Maximilans University in Würzburg (Germany) and was working as a postdoc and an assistant professor at the Technical University Eindhoven (The Netherlands) before she was affiliated as a professor for supply chain management at the Christian Albrechts Universität zu Kiel (Germany). Her main research interests are related to stochastic modeling in after-sales service, inventory control, and supply chain management.