Application of Artificial Intelligence to Measure the Productivity of an Assembly - Line Worker

Abstract

Artificial Intelligence and its application became part of the manufacturing industry during the Industry 4.0 paradigm to resolve the manufacturing difficulties. Intelligent systems are robust in data monitoring and decision-making. Measurement of assembly worker productivity is important for organization economics. This research provides an intelligent technique to measure the productivity of an assembly-line worker using the computer vision. Furthermore, the productivity measures are used to model the work skill of the assembly worker for corresponding assembly task. Video learning technique is adapted to measure the worktime and productivity of the assembly worker from their work recordings. However, work skill is modeled in terms of the work time, assembly task’s shop norm and the work time variance. A use-case example is given to demonstrate the research scope for a manual assembly line. The developed intelligent algorithm has measured the productivity of the assembly worker successfully. Furthermore, the results are compared with the manual measurement.