Toepassing van data mining methoden om systemen te bepalen voor early warning en proactive control in voedselvoorzieningsketens en -netwerken
12 / 2004 - 05 / 2010
European consumers are sophisticated and conscious of food quality and safety. This concern has been strengthened by a series of food safety crises. In response, Food supply chains react by implementing systems to improve the product¿s quality and guarantee its safety. The aim of this project is to analyze Food Supply Chains and Networks in order to find the possibilities to detect deviations from specifications of product attributes and processes in FSCN, and to improve the logistical performance of FSCN. Based on knowledge of Supply Chains, logistics, and data mining, this project aims to find appropriate methods to analyze relations between (attributes of) processes and performance in Food Supply Chains and Networks. In particular, this project intends to build models of the object system at hand using a variety of Data mining techniques. Such models will be based on relations present in the actual FSCN. We will use these models to recommend improvements to the information system and control system that will allow for early warning and proactive control in FSCN. This includes that the model should help detecting potential problems and preventing them at an early stage. By means of a repository of types of relations that can be used to build models of similar object systems, the methods can be applied successfully in subsequent problems and opportunity projects. Moreover, the project will give insight into the applicability of various Data mining techniques and tools to analyze this kind of chains.