Robust Planning
Planning Methods to Cope with Uncertainty in Production Networks (CTI 5986.1 KTS)
Researchers:
A. Ziegenbein, J. Nienhaus, Prof. M. Baertschi, Prof. P. Schönsleben
Partners:
Academic:
University of Applied Sciences St. Gallen, Institute of Mechatronics and Information Technology
Industrial:
ESEC SA
Sibos AG
Siemens (Schweiz) AG
Financed by:
CTI 5986.1 KTS
Website:
Motivation:
Production enterprises are vulnerable to many unexpected events: On the buy side, for example, there are supplier delivery difficulties. In the production process itself, machine failures and unplanned waste can occur, while on the sell side companies face uncertainty of sales quantities. In a production network with several stages in the value chain, one company’s uncertainty is propagated throughout the whole network. Due to this uncertainty, supply chains are subject to risks that can lead to inefficiencies, such as large safety stocks and obsolete material. Currently, only few planning methods consider these uncertainties and risks.
Objectives:
The project “Robust Planning” aims to develop strategic and operational methods that make supply chain planning and the production network itself more robust against unexpected events and the related uncertainty and risks.
The following activities have already been completed:
Sources of uncertainty and the related risks have been structured and identified in a supply chain, taking into account occurrence and impact. Moreover, “robust planning” methods have been deve-loped and implemented at the companies of the industrial partners. One method decreases the un-certainty caused by the demand of variants of product families by introducing the scenario tech-nique to demand forecasting. Another method, an IT-supported method for parameterization of ma-terial management methods, helps to reduce the risk caused by unappropriate planning parameters, e.g., safety stock, batch size. Both methods have been implemented at an industrial project partner company. Further, to reduce the risk coming from suppliers, a systematic method for evaluating, se-lecting, and controlling suppliers has been developed and implemented at another industrial project partner company. A survey among the customers of an industrial partner company analyzes the flow of information and the IT infrastructure in the company network. In addition, a prototype of an IT solution to distribute information relevant to planning tasks in a production network has been im-plemented. It includes a connector to SAP R/3. All in all, the project provides companies with a tool-box of methods and best practices to identify, assess, and control uncertainty and risk in the supply chain.