A Methodology of Task Allocation to Design a Human-Robot Assembly Line

Abstract

There are successful cases in lean manual assembly lines; however, in some cases, such as the ease of assembly in quicker cycle time, the designs are not satisfactory and must be transformed to semi-automation. This research studies human-robot task allocation when designing for semi-automation considering not only time-cost effectiveness as in the existing research but also assembly difficulty and ergonomic issues. A proposed methodology optimally determines what tasks should be performed by humans or robots, at which station, and in what sequence. A multi-objective linear programming (MOLP) model is proposed to simultaneously minimize total operating cost, cycle time, and ergonomic difficulty. Solving the model has two approaches: with and without optimal weights. The methodology is applied to a Lego-car assembly line. To illustrate the benefits of the proposed MOLP, a comparison between it and three single-objective models is made. Results show that the optimal-weight MOLP yields a better performance (a shorter cycle time, a lower cost, and especially, a significant ergonomic improvement) when compared to the other MOLP and single-objective models.

Multi-Objective Job Rotation in Rice Seed Harvesting With Equitable Injury Risk and Cost Allocation

“…A well-known method within this approach is the weighted sum method, as described by Deb (2014). Examples of illustrative research that utilize the weighted sum method to solve MOPs are the studies of Sandar (2019), Tram andRaweewan (2021), andThippo et. al.…”