Modelling and optimization of assembly line balancing with multi-resource constraints

• Main Authors: Ab Rashid, Mohd Fadzil Faisae, Razman, Mat Tahar, Nik Mohamed, Nik Mohd Zuki, Rose, Ahmad Nasser Mohd, Baharom, Mohamad Zairi
• Format: Research Report
• Language: English
• Published: 2017
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/36426/1/Modelling%20and%20optimization%20of%20assembly%20line%20balancing%20with%20multi-resource%20constraints.wm.pdf; http://umpir.ump.edu.my/id/eprint/36426/
• Institution: Universiti Malaysia Pahang

Assembly Line Balancing (ALB) is an attempt to assign tasks to various workstations along a line so that the precedence relations are satisfied and performance measures are optimised. Assumption by previous researches that any assembly task can be performed in any workstation encourages the author to focus on the resource usage in ALB. Limited number of resources in the industry also becomes a vital influencer to consider this constraint in ALB. This research aim to model and optimize the ALB with resource constraints. In different with existing work that assume all workstations have similar capability, this research consider the tool, worker and equipment constraints in the assembly process. The early study reveal that the current trend in production line is becoming more complex due to growth in the product development and also market force to minimize the set up cost. Therefore, beside only consider the simple assembly line problem (SALB), this research also consider two-sided assembly line problem (2S-ALB) and mixed-model assembly line problem (MMALB) that match with current trend in assembly layout. All three version of ALB problems have been modelled to include the general resource constraints. This make all three versions of ALB model is unique compared with existing model in literature. In all three ALB version, the resource constraints have been set as one of objective function to be minimized. The optimization was conducted by using different optimization algorithms. In SALB, we found that the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) have better performance. Meanwhile, for 2S-ALB and MMALB, the Particle Swarm Optimization and Ant colony Optimization have superior performance respectively. The validation for the problem ALB with resource constraints have been conducted in electronic and automotive assembly plant. The final result indicated that the proposed model is capable to improve the assembly efficiency and also capable to reduce the number of the resources required in assembly plant.