Modeling, Analysis, and Improvement of Supply Chains with support of Information Technology (diss.)

Researchers:

Jörg Nienhaus

Partners: 

Case Studies at ALSTOM, Komax Systems (partner in the project "Robust Planning"),
and SIG Pack (partner in the project "ProdChain")

Financed by: 

The Professorship’s own resources

Motivation:

Today, improvement potential with respect to time, cost, quality, and flexibility often lies in effectively managing the logistics and production network of which the company is a part – rather than in managing the operations of the single company. This presents operations managers with new
planning tasks, such as selecting supply chain partners, determining how much capacity to provide at each tier of the supply chain, determining where to place the order penetration point, and choos-ing methods of materials management. Due to the complexity of a supply chain, which often com-prises hundreds of production and storage sites, answering such questions requires a clear view of the supply chain, a structured approach, and Information Technology support.
A few modeling approaches for supply chains are available, such as SCOR, Supply Chain Maps, Value Stream Mapping, and others implemented in SCM software. Analysis of state-of-the-art shows that all of them have three drawbacks in common: No approach fully covers the relevant aspects of a sup-ply chain resulting in optimizing one of its aspects at the expense of others, the ratio of input re-quired to output gained from the mapping process reveals a lack of efficiency, and considering the low quality of planning data none of the existing approaches is robust enough against incomplete or even wrong input data.

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Objectives:

The objective of the dissertation project is to provide operations managers with an integrated model-ing approach for supply chains that is tangible, efficient, and robust, so that it facilitates informed decision-making on supply chain strategy and operations.

Activities completed:

Identification of requirements based on a survey and case studies; state-of-the-art analysis of seven supply chain modeling approaches; software prototype to model, analyze, and improve supply chains (see picture at left); validation of the approach with the help of the software prototype in three industrial test-beds; demonstration of its strengths.