Assembly optimisation activities occur across development and production stages of manufacturing goods. Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) problems are among the assembly optimisation. Both of these activities are classified as NP-hard. Several soft computing approaches using different techniques have been developed to solve ASP and ALB. Although these approaches do not guarantee the optimum solution, they have been successfully applied in many ASP and ALB optimisation works. This paper reported the survey on research in ASP and ALB that use soft computing approaches for the past 10 years. To be more specific, only Simple Assembly Line Balancing Problem (SALBP) is considered for ALB. The survey shows that three soft computing algorithms that frequently used to solve ASP and ALB are Genetic Algorithm, Ant Colony Optimisation and Particle Swarm Optimisation. Meanwhile, the research in ASP and ALB is also progressing to the next level by integration of assembly optimisation activities across product development stages.
Then many algorithms were employed in assembly sequence planning, e.g. genetic algorithm (GA), ant colony optimisation (ACO), particle swarm optimisation (PSO), and many others REF .
A Review on Assembly Sequence Planning and Assembly Line Balancing Optimisation using Soft Computing Approaches
The International Journal of Advanced Manufacturing Technology
Engineering