Innovative robotization of manual manufacturing processes

Abstract

Manufacturing industries are continually challenged to adapt to a competitive environment. Consequently, there is an urgency to opt for automation technologies to upgrade their manufacturing facilities and make them more flexible. Especially this relates to automating manual manufacturing processes, which is often challenging to structure to ensure repetitiveness and generalization to other processes within the facility. Consequently, innovating systematic approaches to identify robotization opportunities is an interesting proposition for manufacturing set-ups that would like to integrate collaborative robots on the shop floor and struggle with the decision steps to follow.In this paper, a framework for supporting robotization effort for manufacturing set-ups is proposed. The methodology consisting of five phases, culminating in the identification of robotization opportunities. A case for manual milling manufacturing processes is demonstrated as a ‘proof-of-concept’. The first step of the proposed approach focuses on task decomposition, in which manual manufacturing tasks are characterized. This is followed by task allocation to a robot and human agent based on intrinsic characteristics of the task to capabilities of the agent. Next, alternative layout configurations for candidate cell layouts are generated. In the final step, a candidate layout is selected and modeled in an agent-based simulation platform, considering factors such as realism, interaction safety between the robot and human agent, and interesting manufacturing metrics such as resource utilization and throughput rate. A final configuration is optimized, which visualizes a collaborative robot performs loading and unloading tasks alongside an operator performing highly cognitive tasks. For safety, zoning of the manufacturing cell is visualized, considering a working area separated by a safety fence.