Prof. Dr. Gudrun Kiesmüller

Center of
Digital Transformation

Prof. Dr. Gudrun Kiesmüller

Prof. Kiesmüller and her team conduct research in the field of Operations Management. Due to the current trend in digitization, many processes are changing and can be designed more efficiently. We develop methods to analyze and optimize processes and we especially investigate the implications of digitisation in the context of Industry 4.0 on after sales services. We further study the application of AI methods for Supply Chain Optimization and Inventory Planning.

Curriculum Vitae
Since July 2019Full Professor, Chair for Operations Management TUM School of Management, TUM Campus Heilbronn Technical University of Munich
October 2013 – June 2019Full Professor, Chair for Operations Management Faculty of Economics and Management Otto-von-Guericke-University Magdeburg
April 2010An offered chair for Logistics and Quantitative Methods at the Bayerische Julius-Maximilians-University Würzburg declined
January 2010 – September 2013Full Professor, Chair for Supply Chain Management Institute of Business Administration Christian-Albrechts-University zu Kiel
January 2002 – December 2009Assistent Professor (universitair docent) Faculty of Industrial Engineering & Innovation Science Technical University Eindhoven, The Netherlands
October 1998 – December 2001Post-doc in the realm of the EU-Project REVLOG: Reverse Logistics and its Effects on Industries Subdepartment of Operations, Planning, and Control Technical University Eindhoven, The Netherlands
October 1993 – September 1998Research Assistant at the Chair for Statistics Bayerische Julius-Maximilians-University, Würzburg

Awards

  • 2017 Outstanding reviewer award of the journal OR spectrum
  • 2017 Education award (third place) for lectures in the Master’s program of the Faculty of Economics and Management at the Otto-von-Guericke-University, Magdeburg
  • 2015 Nomination by the students for the teaching award for outstanding engagement of the Otto-von-Guericke-University, Magdeburg
  • 2014 EURO best paper award for the best EJOR Review Paper Inventory models with lateral transshipments: A review , joint work with C. Paterson, R. Teunter und K. Glazenbrook
  • 2008 Education award (first place) for the best Master’s course Supply Chain Operations Planning in the program Operations Management and Logistics together with A.G. de Kok and J.C. Fransoo
  • 2007 Education award (first place) for the best Master’s course Supply Chain Operations Planning in the program Operations Management and Logistics together with A.G. de Kok
  • 2007 Education award (second place) for the best Bachelor’s course Quantitative Modelling and Analysis of Business Processes together with S.D.P Flapper

Research Areas

Design and Analysis of stochastic manufacturing systems

The design of a manufacturing system is essential for its performance. Even a few design improvements can increase production output or maintain throughput at a lower cost, consequently increasing the revenue of a company. In a discrete part production line throughput is influenced by variable processing times or unexpected machine failures, amongst other reasons. One possible way of mitigating the effects of these uncertainties is by installing buffers between the machines such that the machines are decoupled, meaning they are less affected by each other and can continue producing while another machine is under repair or when processing is slow. In this research project it is investigated how the throughput of a manufacturing system can be increased by smart spare parts planning

Selected publications:

G.P. Kiesmüller, F. Sachs Spare Parts or Buffer? How to design a Transfer Line with unreliable machines, (to be published in European Journal of Operational Research)

G.P. Kiesmüller, J. Zimmermann.  The influence of spare parts provisioning on buffer size in a tandem system. IISE Transactions (2018), 50 (5), 367-380

 Optimal Safety Stocks in Supply Chains

Despite careful planning, it may be useful due to unforeseen events, to keep safety stocks in a supply chain. Then the question raises, at which place the safety stocks need to be hold and which quantity is required. Especially in complex networks and under uncertain customer demand, planning safety stocks is an important component in the design of efficient processes. In one of the current research projects uncertain demand and supply are considered simultaneously. Especially the influence of random production yield on safety stocks is investigated.

Selected publications:

D. Sonntag, G.P. Kiesmüller.  The influence of quality inspections on the optimal safety stock level.  Production and Operations Management (2017), 26 (7), 1284-1298.

K. Inderfurth, G.P. Kiesmüller. Exact and heuristic linear-inflation policies for an inventory model with random yield and arbitrary lead times. European Journal of Operational Research (2015), 245, 109-120.

S.C. Kutzner, G.P. Kiesmüller. Optimal control of an inventory-production system with state-dependent random yield. European Journal of Operational Research (2013), 227, 444-452.

Maintenance and Reliability

Advanced technical systems (e.g. power generators, manufacturing systems, computer networks, medical systems, material handling systems, defense systems) serve for primary operations in our society. They must be kept up and running for operational continuity in power plants, factories, banks, hospital, airports, warehouses, etc. Interruptions of these systems lead to significant losses and therefore companies try to avoid downtimes by smart maintenance activities which have to be planned and integrated in production schedules. Another possibility to improve the availability of a system is a reliability improvement program and a redesign of components. In this research project we study joint reliability and spare parts planning and joint production and maintenance planning.

Selected publications:

W. von Hoyningen-Huene, G. P Kiesmüller. Evaluation of the Expected Makespan of a Set of Non-Resumable Jobs on Parallel Machines with Stochastic Failures.  European Journal of Operational Research (2015), 240, 439-446.

K. Öner, G.P. Kiesmüller, G.J. van Houtum. On the Upgrading Policy After the Redesign of a Component for Reliability Improvement. European Journal of Operational Research (2015), 244, 867-880.

K. Öner, G.P. Kiesmüller, G.J. van Houtum. Optimization of component reliability in the design phase of capital goods. European Journal of Operational Research (2010), 205, 615-624.

Areas of interest

  • Inventory Management
  • After Sales Service
  • Design and Analysis of Manufacturing System
  • Operations Research and Business Analytics

Teaching

A wide and attractive range of courses in the bachelor and master degree program in the field of Operations Management is offered to the students. In addition to the scientifically grounded application, practical relevance are the focus of the courses. Especially, the following objectives are considered:

  • Students know the elementary planning and decision problems in a supply chain, have the awareness of the basic problems that can occur in the management of these processes, and know concepts and methods to solve these problems
  • Students will have experience in dealing with software for decision support, particularly with the use of quantitative models in the field of decision support in Operations Management
  • Students are able to solve complex problems in a Supply Chain through a structured approach, by using scientific methods

Bachelor (Winter Term)

A manager in a company has to make many decisions and many planning tasks have to be performed.Management Science can support decision making and planning, because it is a systematic and quantitative approach to problem solving and to maximize efficiency. Mathematical models are used to describe the problems and algorithms are applied to come up with optimal solutions. In this course tools and techniques from Management Science are studied for applications in Logistics, Finance, Marketing and other fields.

Master (Winter Term)

A manager in a company has to make many decisions and many planning tasks have to be performed.Management Science can support decision making and planning, because it is a systematic and quantitative approach to problem solving and to maximize efficiency. Mathematical models are used to describe the problems and algorithms are applied to come up with optimal solutions. In this course tools and techniques from Management Science are studied for applications in Logistics, Finance, Marketing and other fields.

Forecasting is required for many decisions in Business as for example whether a new production facility should be built or how many employees in a call center are needed. Usually, information about future demand is not available and forecasts are needed to apply the well-known planning methods. The focus in this course is on the use of historical data to compute accurate forecasts. Methods are discussed to detect genuine patterns and to difference between random fluctuations. Besides traditional forecasting methods we also discuss how to integrate Data Mining Techniques or Machine learning to forecasting. Students have to work with Data and do small projects with R.

Each semester a seminar is offered with a different generic topic as for example procurement, maintenance, humanitarian logistics. Student have to study a concrete topic in the related field and have to write a research report and give an oral presentation.

Master (Summer Term)

Within the framework of supply chain management, the management of stocks plays a central role. The aim is to keep inventories as low as possible while maintaining a high level of service. Customer demand should always be met, while keeping costs as low as possible.In general, however, the demand is not known with certainty and delivery times cannot always be regarded as constant. In order to ensure that the processes in the supply chain run smoothly, inventories are therefore used. Nowadays, intelligent inventory Management includes the analysis of real time data and the support of modern technologies like RFID. In this course, the basic trade-offs are discussed and the standard inventory models are studied. Students get data in order to identify the potential improvements for inventory management and learn how to optimize inventory levels.

Each semester a seminar is offered with a different generic topic as for example procurement, maintenance, humanitarian logistics. Student have to study a concrete topic in the related field and have to write a research report and give an oral presentation.

Publications

  • Johansson, Lina;Sonntag, Danja R.;Marklund, Johan;Kiesmüller, Gudrun P.: Controlling distribution inventory systems with shipment consolidation and compound Poisson demand. European Journal of Operational Research 280 (1), 2020, 90-101 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.;Sachs, F.E.: Spare parts or buffer? How to design a transfer line with unreliable machines. European Journal of Operational Research, 2019 [ Full text ( DOI ) ]
  • Kiesmüller, Gudrun P.;Zimmermann, Julia: The influence of spare parts provisioning on buffer size in a production system. IISE Transactions 50 (5), 2018, 367-380 [ Full text ( DOI ) ]
  • Karaarslan, Gönül A.;Atan, Zümbül;de Kok, Ton;Kiesmüller, Gudrun P.: Optimal and heuristic policies for assemble-to-order systems with different review periods. European Journal of Operational Research 271 (1), 2018, 80-96 [ Full text ( DOI ) ]
  • Sonntag, Danja;Kiesmüller, Gudrun P.: Disposal versus rework – Inventory control in a production system with random yield. European Journal of Operational Research 267 (1), 2018, 138-149 [ Full text ( DOI ) ]
  • Sonntag, Danja;Kiesmüller, Gudrun P.: The Influence of Quality Inspections on the Optimal Safety Stock Level. Production and Operations Management 26 (7), 2017, 1284-1298 [ Full text ( DOI ) ]
  • Kiesmüller, G. P.;Inderfurth, K.: Approaches for periodic inventory control under random production yield and fixed setup cost. OR Spectrum, 2017 [ Full text ( DOI ) ]
  • Sonntag, Danja;Kiesmüller, Gudrun P.: The shape of the yield and its impact on inventory decisions. 4OR 14 (4), 2016, 405-415 [ Full text ( DOI ) ]
  • Öner, K.B.;Kiesmüller, G.P.;van Houtum, G.J.: On the upgrading policy after the redesign of a component for reliability improvement. European Journal of Operational Research 244 (3), 2015, 867-880 [ Full text ( DOI ) ]
  • Inderfurth, K.;Kiesmüller, G.P.: Exact and heuristic linear-inflation policies for an inventory model with random yield and arbitrary lead times. European Journal of Operational Research 245 (1), 2015, 109-120 [ Full text ( DOI ) ]
  • von Hoyningen-Huene, W.;Kiesmüller, G.P.: Evaluation of the expected makespan of a set of non-resumable jobs on parallel machines with stochastic failures. European Journal of Operational Research 240 (2), 2015, 439-446 [ Full text ( DOI ) ]
  • Kleintje-Ell, F.;Kiesmüller, G. P.: Cost minimising order schedules for a capacitated inventory system. Annals of Operations Research 229 (1), 2015, 501-520 [ Full text ( DOI ) ]
  • Kutzner, S.C.;Kiesmüller, G.P.: The value of joint decision-making in an inventory–production system with random yield and imperfect information. International Journal of Systems Science: Operations & Logistics 1 (2), 2014, 118-129 [ Full text ( DOI ) ]
  • Karaarslan, A. G.;Kiesmüller, G. P.;de Kok, A. G.: Effect of modeling fixed cost in a serial inventory system with periodic review. OR Spectrum 36 (2), 2013, 481-502 [ Full text ( DOI ) ]
  • Karaarslan, A.G.;Kiesmüller, G.P.;de Kok, A.G.: Analysis of an assemble-to-order system with different review periods. International Journal of Production Economics 143 (2), 2013, 335-341 [ Full text ( DOI ) ]
  • Paterson, Colin;Kiesmüller, Gudrun;Teunter, Ruud;Glazebrook, Kevin: Inventory models with lateral transshipments: A review. European Journal of Operational Research 210 (2), 2011, 125-136 [ Full text ( DOI ) ]
  • Arts, Joachim;van Vuuren, Marcel;Kiesmüller, Gudrun: Efficient optimization of the dual-index policy using Markov chains. IIE Transactions 43 (8), 2011, 604-620 [ Full text ( DOI ) ]
  • Klosterhalfen, Steffen;Kiesmüller, Gudrun;Minner, Stefan: A comparison of the constant-order and dual-index policy for dual sourcing. International Journal of Production Economics 133 (1), 2011, 302-311 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.;de Kok, A.G.;Dabia, S.: Single item inventory control under periodic review and a minimum order quantity. International Journal of Production Economics 133 (1), 2011, 280-285 [ Full text ( DOI ) ]
  • Öner, K.B.;Kiesmüller, G.P.;van Houtum, G.J.: Optimization of component reliability in the design phase of capital goods. European Journal of Operational Research 205 (3), 2010, 615-624 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.: Multi-item inventory control with full truckloads: A comparison of aggregate and individual order triggering. European Journal of Operational Research 200 (1), 2010, 54-62 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.;Broekmeulen, R.A.C.M.: The benefit of VMI strategies in a stochastic multi-product serial two echelon system. Computers & Operations Research 37 (2), 2010, 406-416 [ Full text ( DOI ) ]
  • Öner, K.B.;Kiesmüller, G.P.;van Houtum, G.J.: Monotonicity and supermodularity results for the Erlang loss system. Operations Research Letters 37 (4), 2009, 265-268 [ Full text ( DOI ) ]
  • G. P. Kiesmüller, S. Minner: Inventory redistribution for fashion products under demand parameter update. , 2009
  • Kiesmüller, G.P.: A multi-item periodic replenishment policy with full truckloads. International Journal of Production Economics 118 (1), 2009, 275-281 [ Full text ( DOI ) ]
  • Larsen, Christian;Kiesmüller, G.P.: Developing a closed-form cost expression for an policy where the demand process is compound generalized Erlang. Operations Research Letters 35 (5), 2007, 567-572 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.;de Kok, A.G.: The customer waiting time in an (R,s,Q) inventory system. International Journal of Production Economics 104 (2), 2006, 354-364 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.;de Kok, A.G.;Fransoo, J.C.: Transportation mode selection with positive manufacturing lead time. Transportation Research Part E: Logistics and Transportation Review 41 (6), 2005, 511-530 [ Full text ( DOI ) ]
  • G. P. Kiesmüller, A.G. de Kok: A multi-item multi-echelon inventory system with quantity-based order consolidation. , 2005
  • Kiesmüller, Gudrun P.;de Kok, Ton G.;Smits, Sanne R.;van Laarhoven, Peter J. M.: Evaluation of divergent N-echelon (s,nQ)-policies under compound renewal demand. OR Spectrum 26 (4), 2004, 547-577 [ Full text ( DOI ) ]
  • Kiesmüller, Gudrun P.;Scherer, Carsten W.: Computational issues in a stochastic finite horizon one product recovery inventory model. European Journal of Operational Research 146 (3), 2003, 553-579 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.: A new approach for controlling a hybrid stochastic manufacturing/remanufacturing system with inventories and different leadtimes. European Journal of Operational Research 147 (1), 2003, 62-71 [ Full text ( DOI ) ]
  • Kiesmüller, G.P.: Optimal control of a one product recovery system with leadtimes. International Journal of Production Economics 81-82, 2003, 333-340 [ Full text ( DOI ) ]
  • Kiesmüller, G P;Minner, S: Simple expressions for finding recovery system inventory control parameter values. Journal of the Operational Research Society 54 (1), 2003, 83-88 [ Full text ( DOI ) ]
  • Kleber, Rainer;Minner, Stefan;Kiesmüller, Gudrun: A continuous time inventory model for a product recovery system with multiple options. International Journal of Production Economics 79 (2), 2002, 121-141 [ Full text ( DOI ) ]
  • Kiesmüller, Gudrun P.;van der Laan, Erwin A.: An inventory model with dependent product demands and returns. International Journal of Production Economics 72 (1), 2001, 73-87 [ Full text ( DOI ) ]