Identifying Anomaly Work in Intralogistics Using BLE and LPWA.

Due to recent increased competition in the automobile industry, many studies have optimized manufacturing models to reduce costs. However, such studies have produced scant benefits because these models have matured due to the long-term improvements in the automobile industry. Therefore, we propose a way to identify anomaly work in intralogistics. Anomaly work means inefficient work whose efficiency is worse than the normal work in this paper. As a concrete method, workers and forklifts are given BLE beacons, and the radio waves transmitted by them are collected by a sensor network using LPWA. Next the collected BLE beacon data continuously estimate the positions of workers and forklifts and are converted into intralogistics data. Regression analysis is performed on these intralogistics data to identify anomaly work. This proposed method identifies the locations and the times when anomaly work occurs in a factory, and with such data, logistics will be improved and manufacturing costs will be reduced.