Activity Monitoring Using Wearable Sensorsin Manual Production Processes - An Application of CPS for Automated Ergonomic Assessments

Abstract

The automated identification and analysis of human activities in a manufacturing context represent an interesting challenge to support the workers, providing novel solutions for managing and optimizing existing manufacturing processes. If on one hand real-time coupling of events and activities is a relativelyeasy task for activities which are executed by means of information systems, on the other hand,the coupling of events and human physical activities remains an unsolved problem. In this paper we present a novel paradigm based on the integration of a light-weight, low-cost body sensor network and a software solution based on machine learning for tracking working operations. This enables the fast identification of inconvenient ergonomic behaviors and process aspects, which are objective of workflow analysis, process improvement and optimization activities. To assess the usability and functionality of the system a study under real conditions was conducted in the logistic plant of a big automobile manufacturer.