A mixed-integer linear programming formulation for assembly line balancing problem with human-robot shared tasks

Abstract

Human-robot collaboration (HRC) has arisen as a promising technology to improve the productivity of assembly processes. This paper discusses an assembly line balancing problem (ALBP) where manual, robotic, or HRC operations may be considered decision alternatives. Each assembly process task may be operated either by a human operator, a robot operator, or an HRC. This possibility of shared functions between humans and robots may result in a hybrid manual-robotic assembly line. This problem’s mathematical model is developed based on the simple ALBP and modifying the idea of two-sided ALBP, with additional aspects related to resource alternatives of human, robot, or HRC, and robot’s tool-type for the operations. The problem is formulated analytically in a mixed-integer linear programming model with a cost-oriented objective function. The exact method can be applied to obtain an optimal solution.

The Development of Human-Robot Collaborative Assembly Line Model by Considering Availability of Robots, Tools, and Setup Time

“…The model provided in this work has 18 constraints, 15 of which are from Weckenborg (2020), one from Nugraha et al (2021), and two constraints from Alghajani ( 2014). The developed model can be explained below.…”

“…As a result, the assembly line must be adaptable to product variations and must be simple to reconfigure once a new model is placed into production. Using Collaborative Robots (Cobot) on the assembly line is one strategy for dealing with the frequency of changes on the assembly line (Olivares-Alarcos et al, 2022).…”

“…As parameters, the model includes the upper bound cycle time and the maximum number of robots. Nugraha (2021) has improved on Weckenborg's model by considering the number of tools accessible to execute various assembly tasks. The Nugraha model's objective function is to decrease ALHRC's operating costs, which is appropriate for reasonably long-run production because the suggested model allows for investment in additional cobots or tools.…”

Multi-Objective Linear Optimization on Immediate Distributing poultry with Time Windows: Modellings and Applications

“…The above scheme is to reduce the scale of computer operation by dividing the model into sub-constraint modules for the layered solutions. This article will collate and analyse the advantages of dynamic programming [14], linear programming [15][16][17] and non-linear programming [18][19][20][21][22]. Referring to this idea, the actual pick-up time of customers is transformed into 0-1 data table in data preprocessing, which is convenient for the construction of time window constraints.…”