Sensor-Based Analysis of Manual Processes in Production and Logistics: Motion-Mining versus Lean Tools

Manual work is a significant cost driver in manufacturing and logistics. However, research on the methods for analyzing manual processes utilizing sensor technologies, apart from technical feasibility, is scarce. Motion-Mining® is a technology that uses motion sensors, Bluetooth, and pattern recognition to enable highly automated process mapping and analysis of manual work. The aim of this paper is to evaluate the benefits and limitations of applying this technology in manual production and logistics processes. To this end, Motion-Mining® is compared with traditional and low-tech Lean management tools for capturing and analyzing manual activities. Ten semi-structured expert interviews as well as case studies in four companies were conducted. The results indicate that Motion-Mining® differs from Lean tools for process analysis mainly in terms of the effort required for data collection, the amount of data obtained, the representativeness of the data, the level of detail, and the insights gained.