Balancing of assembly lines with collaborative robots

Abstract

Motivated by recent developments to deploy collaborative robots in industrial production systems, we investigate the assembly line balancing problem with collaborative robots. The problem is characterized by the possibility that human and robots can simultaneously execute tasks at the same workpiece either in parallel or in collaboration. For this novel problem type, we present a mixed-integer programming formulation for balancing and scheduling of assembly lines with collaborative robots. The model decides on both the assignment of collaborative robots to stations and the distribution of workload to workers and robotic partners, aiming to minimize the cycle time. Given the high problem complexity, a hybrid genetic algorithm is presented as a solution procedure. Based on extensive computational experiments, the algorithm reveals promising results in both computational time and solution quality. Moreover, the results indicate that substantial productivity gains can be utilized by deploying collaborative robots in manual assembly lines. This holds especially true for a high average number of robots and tasks to be assigned to every station as well as a high portion of tasks that can be executed by the robot and in collaboration.

Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey

“…Since robots are expensive, reconfigurability of the system may decrease the cost, because mobile robots and workers can move among stations instead of adding a new robot. Furthermore, variety of collaborative robots applications like picking and placing, screw driving, inspection, assembly tasks, in addition to their quick and easy set-up, and mobility (Weckenborg et al, 2019), makes their use in reconfigurable manufacturing systems very attractive. Thus, there is a need to develop design methods aiming to enhance the system's reconfigurability.…”

“…Some researchers have only recently begun to study HRC systems in the context of operations management (Darvish et al, 2018;Bogner et al, 2018;Michalos et al, 2018b). The related topics include system's design (Chen et al, 2011;Michalos et al, 2018b), line balancing (Weckenborg et al, 2019), scheduling (Bogner et al, 2018;Casalino et al, 2019), resource allocation (Takata & Hirano, 2011), and task planning and assignment (Chen et al, 2013;Hu & Chen, 2017;Darvish et al, 2018).…”

“…There exist methods for the design of HRC systems in cellular manufacturing systems (Tan et al, 2009(Tan et al, , 2010, flexible assembly lines , 2018, and cellular manufacturing systems (Kato et al, 2010;Hu et al, 2013). The typical methods to tackle operations management problems in HRC systems include linear/non-linear programing (Hu & Chen, 2017;Bogner et al, 2018), (mixed-)integer programing (Weckenborg et al, 2019), heuristics (Bogner et al, 2018) metaheuristics algorithms (Chen et al, 2013;Weckenborg et al, 2019), multi-criteria evaluation approach (Michalos et al, 2018b), and simulation models (Darvish et al, 2018;Bänziger et al, 2018).…”

“…This research aimed to minimize the total cooperation cost between humans and robots. Mainly, the objective functions correspond to the time and cost; such as makespan (Bogner et al, 2018), cycle time (Casalino et al, 2019;Weckenborg et al, 2019), and production cost (Takata & Hirano, 2011;Chen et al, 2013;Hu & Chen, 2017).…”

Genetic Algorithm-based Task Allocation in Multiple Modes of Human-Robot Collaboration Systems with Two Cobots

“…Dalle Mura and Dini [31] aimed to minimize the cost, number of skilled workers, and energy load variance in an assembly line. Weckenborg et al [32] developed a hybrid GA-based cobot allocation and human workload distribution to minimize cycle time. In their study, they assigned tasks to the stations in an assembly line and decide on the stations where the robots will be allocated.…”