1. 10-Feb-16 RFID data ming, KDL, NTNU 1 Application of the RFID Data Mining to an Apparel Field Professor Kesheng Wang Department of Production and Quality Engineering Norwegian University of Science and Technology N-7491 Trondheim, Norway Tel. 47 73 59 7119, Fax 47 73 59 7117 E-mail: kesheng.wang@ipk.ntnu.nokesheng.wang@ipk.ntnu.no

2. 10-Feb-16 RFID data ming, KDL, NTNU 2 Outline n Introduction n Prediction method n Data format n Experiment n Conclusions n A new project proposal

3. 10-Feb-16 RFID data ming, KDL, NTNU 3 Introduction This project proposes a new method that efficiently uses the RFID data collected from apparel shops. This method learns prediction models from the data by using data mining techniques. The models represent relationships between the number of sales in the next term and the actions of customers, such as the number of pick-up, the number of fitting, the number of customers, and so on. It is possible to predict sales volume by applying the present RFID data to the models. This project verifies the efficiency of the method through numerical experiments based on the RFID data collected from two branches of an apparel company.

4. Prediction Method 10-Feb-16 RFID data ming, KDL, NTNU 4 The prediction method is based on the RFID data. The data is composed of independent variables and a dependent variable. The independent variables correspond to the number of customers, stock, sales, and so on in a week. The method applies the models to the RFID data in this week and predicts the number of items sold in the next week. The managers can decide the number of items ordered in this week by referring to the number of stock in this week and the predicted number of sold items.

5. NTNU Prediction Method 10-Feb-16 RFID data ming, KDL, NTNU 5

6. A format of training example Indipendent VariableDepend ent Variabl e No of pick-up Time of pick-up No of fitting Time of fitting No of custome rs No of stock (whole) No of stock (shop) No of stock (backya rd) No of sales in previou s term No of saløes in present term No of sales in the next term 10-Feb-16 RFID data ming, KDL, NTNU 6

7. 10-Feb-16 RFID data ming, KDL, NTNU 7 Conclusions This project proposed a method that predicts the number of sales in the next term based on the RFID data. The experimental results show the possibility of the prediction, even if it is necessary for the prediction models to be revised their performance. In future work, we will tackle on the improvement of the prediction models. We will try to collect new RFID data. These improvements of the data can revise the models. On the other hand, we will aggressively tackle to establish many methods which the RFID data efficiently activates in various fields.

8. A new peoject proposal : Title: Assessing changes in quality of perishable produce in chilled supply chains using RFID logged data Partners: 1. NTNU (Data ming and system integration) 2. Manchester University (RFID Temperature sensors, Logistics) 3. Hrafn (RFID, SCM) 4. …… 10-Feb-16 RFID data ming, KDL, NTNU 8

9. NTNU Motivation and Drivers Temperature-related loss in quality of perishable produce is significant. Not only does this quality represent a cost, but also it generates waste produce that is expensive to dispose of. As a result, there is an economic incentive to estimate the temperature-related loss, which would subsequently enable a quality-control strategy based on temperature monitoring. 10-Feb-16 RFID data ming, KDL, NTNU 9

10. NTNU Objectives To identify and/or develop a technique that can predict changes in quality of in-transit perishable produce using logged temperature. 10-Feb-16 RFID data ming, KDL, NTNU 10

11. Expected End Result n A data mining technique that uses logged temperature to estimate the loss in quality of perishable produce in transit. n Develop a BIP project with NFR 10-Feb-16 RFID data ming, KDL, NTNU 11

12. Framework/plateforem 10-Feb-16 RFID data ming, KDL, NTNU 12

13. Case study: predicting Remaining Shelf Life (RSL) for chilled sea food n 10-Feb-16 RFID data ming, KDL, NTNU 13

14. NTNU Experiment results 10-Feb-16 RFID data ming, KDL, NTNU 14

15. NTNU RFID Setup in Lab. 10-Feb-16 RFID data ming, KDL, NTNU 15 ComponentsCompanyPrice Temperature sensor array RFID Tag RFID Reader RFID Antenna Middelware (software)? Others?