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.
Highlights
The role of automation in modern manufacturing companies has increased significantly over the past decades
Motivated by recent developments to deploy collaborative robots in industrial production systems, we investigate the assembly line balancing problem with collaborative robots
For the given example problem, the optimal solution of the manual assembly line is calculated according to the formulation of simple assembly line balancing problem (SALBP)-2 proposed by Scholl (1999, Chapter 2.2.3.3, Formulation 1), while the collaborative line is calculated utilizing our model introduced in Sect
Summary
The role of automation in modern manufacturing companies has increased significantly over the past decades. Despite its increasing distribution in real-world industry applications, the trend of human–robot collaboration has not yet been considered in the balancing of assembly lines, and many companies state the necessity of additional support for the planning process (Fraunhofer IAO 2016). The assembly line balancing problem with equipment selection is enriched by a collection of scheduling problems In scheduling these stations, logical relations between the resources have to be considered. By conducting an extensive computational experiment, the performance of the mathematical optimization model and the genetic algorithm is analyzed, and general recommendations for decision makers wavering with collaborative robots’ implementation are derived The remainder of this contribution is structured as follows: we introduce the problem of balancing assembly lines with collaborative robots based on the classification of the problem setting and an illustrative example.
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