Data in production and logistics

The recording, processing, and transmission of data is an essential part of all processes in production and logistic in addition to the actual material flow. Companies often collect large amounts of data, of which only small parts are used for defined functions. A deeper analysis of this data and a combination of different databases offers the possibility to gain new insights about the design and control of production and logistic systems.

Methods of Data Mining, Cluster Analysis and Machine Learning offer the possibility to systematically analyze the data, either for a one-time process optimization (e.g. in line with restructuring of a production system), or for permanent use in processes (e.g. by using various internal data from production and logistics for the forecast of disturbances in the processes).

                           Figure: Material flow clusters in a production network


The focus of the research of the work group are the following questions: 

  • Based on what kind of data already available in the company can disturbances in the processes be forecasted and what methods achieve this?
  • What methods can divide orders, production processes, suppliers, etc. into risk groups in order to align the corresponding processes in accordance with the risks?
  • How can clusters be identified in a production or logistic network?

Selected Publications

  • Till Becker and Daniel Weimer (2014). Identification of Autonomous Structures in Dynamic Manufacturing Networks using Clustering Approaches. The Annual Cambridge International Manufacturing Symposium -- Capturing value from global networks: implications for manufacturing, supply chains and industrial policy ISBN 978-1-902546-45-2: [www] [BibTex]