A case study of energy efficient assembly sequence planning problem
Energy efficiency has become an important issue in manufacturing industry, since it is one of the biggest energy consumers in the world. Despite the importance of energy efficiency, it is much obvious that the research in assembly sequence that focus on environmental aspect is still lacking. In A...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Conf. Series: Materials Science and Engineering 469 (2019) 012013
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/24068/ http://umpir.ump.edu.my/id/eprint/24068/ http://umpir.ump.edu.my/id/eprint/24068/1/1.%20%282019%29%20M.%20A.%20Abdullah%20et%20al.%20-%20A%20Case%20Study%20of%20Energy%20Efficient%20Assembly%20Sequence%20Planning%20Problem.pdf |
| Summary: | Energy efficiency has become an important issue in manufacturing industry, since it
is one of the biggest energy consumers in the world. Despite the importance of energy efficiency,
it is much obvious that the research in assembly sequence that focus on environmental aspect is
still lacking. In Assembly Sequence Planning (ASP), the research on problem optimization is
mainly demanded for the effective computational approach to determine the best assembly
sequence. This paper presents a case study from an electronic product assembly that considers
the energy utilization during assembly process. In particular, the case study focuses to reduce the
idle energy utilization in assembly process. The case study was optimized using newly proposed
Moth-Flame Optimization (MFO) and then being compared with well-frequent used algorithms
including Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic
Algorithm (GA). The result of the computational experiment test was divided into comparison
of assembly layout between MFO proposed layout and existing layout. Besides, the statistical
test involving Analysis of Variance (ANOVA) and post-hoc test of Fisher’s Least Significant
Difference (LSD) were then conducted. The proposed MFO performed better in terms of the best
minimum fitness (0.401681), average fitness (0.415308), standard deviation of fitness
(0.022601), with appropriate computational time and power consumed. In meantime, the results
also indicated that the case study was suitable in the development of energy efficient model for
ASP |
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