An Error Prevention Using Deep learning to Solve Disassembly Line Balancing Problem

Abstract

The disassembly line has issues with balancing the disassembly, including worker errors and the influence of these errors on worker productivity, disassembly idle time, loss of smooth work, accumulation and blockage of some work stations, and the lack of effectiveness of other work stations. In this paper, a new novel technique for balancing the waste products disassembly line is proposed, and this method depends on the machine's vision to assist workers in performing essential tasks. The findings of comparing the performance of workers with and without assistance with the proposed method were as follows:  Worker productivity increased by 50 percent, idle time was reduced by 77.8 percent, the number of workstations was reduced by 33.3 percent, and the error rate was reduced by 81.5 percent.