1. Possibilities for Applying Data Mining for Early Warning in Food Supply Networks Adrie J.M. Beulens,Yuan Li, Mark R. Kramer, Jack G.A.J. van der Vorst

2. Agenda Framework Requirements in relation to data mining Case study

3. Food supply networks inputs Output s Complexity, variability, uncertainty… Quantification of performance indicators

4. Information Systems in FSN Transparency, traceability, tractability E-commerce Scanning Total quality management HACCP …

5. Framework for Early Warning

6. Requirements on Data mining About processes Problem detection Finding determinant factors Prediction About presentation Complex structure representation Different representation forms New knowledge incorporation

7. Contribution of Data mining - I Requirements imposed by early warning system Function of data mining 1.Predict2.Detect problem 3.Find determinant factors 4.Describe complex structure Deviation detectionValid Factor selection *Helpful ClassificationValidHelpful RegressionValidHelpful Dependence modelValidHelpfulValid Causal modelValid * Factor selection methods are usually regarded as a pre-processing step for data mining rather than a separate data mining function.

8. Contribution of Data mining - II DM methods DM Function Decision trees Neural networks Bayesian networks Association rules Nearest neighbor Deviation detection Valid ClassificationValid RegressionValid Dependence model Valid Causal modelValid

9. Contribution of Data mining - III Data mining methodRepresentation formNovel knowledge incorporation Decision trees Easy Association rulesRulesEasy Neural networksLinear or Nonlinear model Difficult Nearest neighborsExample-base methodsDifficult Bayesian networksProbabilistic graphical dependency model Easy

10. Other remarks on technique selection Data format Quantitative Qualitative How well the model class is able to represent patterns in data sets Heuristic expert rules Meta-learning landmarking

11. Case study Stages of the chicken supply chain: One of the Performance Indicators: percentage of dead chicken upon arrival Deviation: chicken’s Death-On-Arrival (DOA) HatcheryBroiler Farm Transport Slaughter house

12. Case study – Result with Decision trees

13. Questions? © Wageningen UR