Prof. Dr. Katja Klingebiel

Klingebiel, K., & Fleißner, F. (2024). Absatz-und Allokationsplanung. In K. Furmans, M. Henke, H. Tempelmeier, M. ten Hompel, & T. Schmidt, Handbuch Logistik (4. Auflage). Berlin: Springer Vieweg.

Klingebiel, K., Wagenitz, A., Toth, M., Motta, M., & Weibels, D. (2020). Integrierte Simulation von Auftragsabwicklungs-und Supply Chain-Prozessen. In G. Mayer, C. Pöge, S. Spieckermann, & S. Wenzel, Ablaufsimulation in der Automobilindustrie (pp. 231–245). Berlin: Springer Vieweg.

Fruhner, D., Pawlikowski, K., Klingebiel, K., & Toth, M. (2017). Efficient product representations for automotive logistics. In CAL-TEK SRL, 29th European Modeling and Simulation Symposium (EMSS 2017) : Barcelona, Spain, 18-20 September 2017 : held at the International Multidisciplinary Modeling and Simulation Multiconference (I3M 2017) (pp. 100–109). Red Hook, NY: Curran Associates, Inc.

Pawlikowski, K., Fruhner, D., & Klingebiel, K. (2016). Benefits of an integrated hierarchical data structure for automotive demand and capacity management. In C. M. Westphall, ICCGI 2016 : the Eleventh International Multi-Conference on Computing in the Global Information Technology : November 13-17, 2016, Barcelona, Spain (pp. 20–25). Wilmington, DE: IARIA XPS Press.

Fruhner, D., Pawlikowski, K., & Klingebiel, K. (2016). Complexity reduction via hierarchical product structures in the field of automotive demand and capacity management. In P. Reusch & C. Wolff, International research conference 2016 (p. ohne Seitenangabe-ohne Seitenangabe). Dortmund: Fachhochschule Dortmund.

Klingebiel, K., Hackstein, L., & Cirullies, J. (2014). Ressourceneffiziente Logistik. In R. Neugebauer, Handbuch ressourcenorientierte Produktion (pp. 719–748). München: Hanser.

Parlings, M., & Klingebiel, K. (2014). Supply chain adaptation through phases of product innovation life cycles. In J. S. Srai & P. Christodoulou, Capturing value from global networks : implications for manufacturing, supply chains and industrial policy ; 18th Cambridge International Manufacturing Symposium 11-12 September, 2014, Cambridge ; conference proceedings (p. ohne Seitenangabe-ohne Seitenangabe). Cambridge: Institute for Manufacturing.

Filla, P., & Klingebiel, K. (2014). A risk management approach für the pre-series logistics in production ramp-up. In W. Kersten, T. Blecker, & C. M. Ringle, Next generation supply chains : trends and opportunities (pp. 407–422). Berlin: Epubli.

Filla, P., & Klingebiel, K. (2014). Risk profiles for the pre-series logistics in automotive ramp-up processes. In R. Schmitt, 2nd ICRM 2014, international conference on ramp-up management : Aachen, Germany, 12-13 June 2014 (pp. 44–49). Red Hook, NY: Curran.

Cirullies, J., Klingebiel, K., & Scavarda, L. F. (2013). Integration of environmental criteria into simulation-based postponement decisions. In E. Pinheiro de Lima, Challenges for sustainable operations : planning, implementing and managing reverse networks ; 22nd International Conference on Production Research, ICPR 22 ; July 28 - August 1, 2013 in Inguassu Falls, Brazil proceedings (pp. 336–342). Foz do Iguaçu: International Foundation for Production Research.

Klingebiel, K., & Wagenitz, A. (2013). An introduction to logistics as a service. In U. Clausen, M. Ten Hompel, & M. Klumpp, Efficiency and logistics (pp. 209–216). Berlin: Springer.

Parlings, M., Cirullies, J., & Klingebiel, K. (2013). A literature-based state of the art review on the identification and classification of supply chain design tasks. In E. Barrington-Light, J. Griffiths, & L. King, Disruptive supply network models in future industrial systems. Configuring for resilience and sustainability : 17th Cambridge International Manufacturing Symposium 19 and 20 September 2013, Cambridge; Symposium proceedings (pp. 407–422). Cambridge: Institute for Manufacturing, Department of Engineering.

Parlings, M., Klingebiel, K., & Cirullies, J. (2013). Determining phase transitions for aligning the supply chain strategy along early life cycle phases of product innovations. In B. Fynes & P. Coughlan, European Operations Management Association -EurOMA- : 20th EurOMA Conference 2013 - Operations Management at the Heart of the Recovery ; Dublin, Ireland, 7th-12th of June 2013 (p. ohne Seitenangabe-ohne Seitenangabe). Brüssel: EurOMA Secretariat. Retrieved from http://euroma2013.euroma-online.org/

Yi, H., & Klingebiel, K. (2013). Contribution to an automotive variant-driven product variety framework. In T. Schoenherr, Production and Operations Management Society (POMS Annual Conference) : 24, 2013, Denver/Colorado (p. ohne Seitenangabe-ohne Seitenangabe). Miami: Production and Operations Management Society.

Klingebiel, K., & Wagenitz, A. (2010). Prozesse und IT aufgabenorientiert gestalten. In U. Clausen, M. Ten Hompel, & M. Klumpp, Efficiency and logistics (pp. 111–122). Berlin: Springer.

Klingebiel, K., Schulz, B., & Reh, D. (2023). A Systematic Literature Review on the Developments in the Field of Flexible and Fully Automated Assembly Stations Within the Automotive Sector. In E. Alfnes, A. Romsdal, J. O. Strandhagen, G. von Cieminski, & D. Romero, Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures (pp. 441–459). Cham: Springer Nature Switzerland. https://doi.org/https://doi.org/10.1007/978-3-031-43688-8_31

Sardesai, S., & Klingebiel, K. (2023). Maintaining viability by rapid supply chain adaptation using a process capability index. Omega, 115. https://doi.org/https://doi.org/10.1016/j.omega.2022.102778

Parlings, M., & Klingebiel, K. (2017). A framework for aligning the supply chain throughout a radical product innovation life cycle. International Journal of Manufacturing Technology and Management, 31 (2017)(1/2/3), 37–61.

Pawlikowski, K., Fruhner, D., Klingebiel, K., Toth, M., & Wagenitz, A. (2017). A motivation and evaluation of hierarchical data structures for application in automotive demand and capacity management. International Journal on Advances in Software, 10 (2017)(1 & amp;2), 155–166.

Klingebiel, K., & Motta, M. (2017). Logistik benötigt sämtliche Informationen. Orange : das Forschungsmagazin der Fachhochschule Dortmund, 45–49.

Parlings, M., Klingebiel, K., & Oschmann, P. (2016). An integrated innovation life cycle model for supply chain adaption. IFAC-PapersOnLine, 49 (2016)(2), 96–101.

Santos Ceryno, P., Scavarda, L. F., & Klingebiel, K. (2015). Supply chain risk. Journal of Risk Research : Official Journal of the Society for Risk Analysis Europe and the Society for Risk Analysis Japan, 18 (2015)(9), 1145–1164.

Thome, A. M. T., Scavarda, L. F., & Klingebiel, K. (2014). A multi-tier study on supply chain flexibility in the automotive industry. International Journal of Production Economics, 158 (2014), 91–105.

Santos Ceryno, P., Scavarda, L. F., & Klingebiel, K. (2013). Supply chain risk management. International Journal of Industrial Engineering and Management : IJIEM, 4 (2013)(3), 141–150.

Klingebiel, K., Leiras, A., & Másculo, F. (2013). Challenges for Managing Complexity in Industrial and Operations Management – A point of view from ICIEOM 2013. Brazilian Journal of Operations Management, 10(2), 7–10.

Klingebiel, K., Yüzgülec, G., & Wagenitz, A. (2011). Innovative Bauklötze. Logistik heute, (6), 54–57.

Klingebiel, K., Scavarda, L. F., Winkler, H., & Wagenitz, A. (2011). Logistikkompetenz in Brasilien Transfer erprobter logistischer Methoden in einen Entwicklungsmarkt. Industrie Management, 37(2), 33–37.

Klingebiel, K., Hellingrath, B., Pires, S. R. I., & Scavarda, L. F. (2011). Integrated Design and Evaluation of Logistics Network: Oriented Placement of the Order Penetration Point. Brazilian Journal of Operations Management, 8(2), 103–120.

Klingebiel, K., Toth, M., & Wagenitz, A. (2010). Dynamic Supply Chain Planning with Logistic Assistant Systems. THE AUSTRALIAN SOCIETY FOR OPERATION RESEARCH INCORPORATED, 29(2), 3–14.

Klingebiel, K., Gavrylenko, Y., & Wagenitz, A. (Eds.). (2010). Adoption Of Simulation Techniques For Mastering Logistic Complexity Of Major Construction And Engineering Projects. Presented at the 24th European Conference on Modelling and Simulation,  Simulation Meets Global Challenges, Nottingham: ECMS. https://doi.org/10.7148/2010-0160-0168