[3H5-GS-3] Data mining: Applied data mining (2)

[3H5-GS-3-04] Implementation of detection method for unsteady works in logistics using BLE and LPWA

〇Masahiro Yamaguchi¹, Takanobu Otsuka² (1. Nagoya Institute of Technology, 2. Department of Conputer Science, Nagoya Institute of Technology)

Keywords:Position estimation, Anomaly detection, AI for Industries

Recently, there are various problems at manufacturing site. IoT and digitalization are progressing to respond these problems. On the other hand, logistics problems at manufacturing site are untouched. In particular, it is important to improve the efficiency of inter-process logistics, which is difficult to automate. In this paper, we implemented a system manages informations on the position and movement of workers and forklift(POI: Position Operation Information)and informations on parts inventory, and use it to improve the efficiency of inter-process logistics. In this paper, position estimation is performed using data on POI of inter-process logistics in factory. In addition, by using data of POI which divided by time, we extract time periods that unsteady behavior is often performed and reduce work steps of inter-process logistics.