Ainizar, Mustapa and Zulkifli, Md. Yusof and Asrul, Adam and Badaruddin, Muhammad and Zuwairie, Ibrahim (2018) Solving assembly sequence planning using angle modulated simulated kalman filter. In: 4th Asia Pacific Conference on Manufacturing Systems and the 3rd International Manufacturing Engineering Conference, APCOMS-iMEC 2017 , 7-8 December 2017 , Yogyakarta, Indonesia. pp. 1-6., 319 (1). ISSN 1757-8981 (Print); 1757-899X (Online)
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Abstract
This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. The SKF search strategy contains three simple steps; predict-measure-estimate. The main objective of the ASP is to determine the sequence of component installation to shorten assembly time or save assembly costs. Initially, permutation sequence is generated to represent each agent. Each agent is then subjected to a precedence matrix constraint to produce feasible assembly sequence. Next, the Angle Modulated SKF (AMSKF) is proposed for solving ASP problem. The main idea of the angle modulated approach in solving combinatorial optimization problem is to use a function, g(x), to create a continuous signal. The performance of the proposed AMSKF is compared against previous works in solving ASP by applying BGSA, BPSO, and MSPSO. Using a case study of ASP, the results show that AMSKF outperformed all the algorithms in obtaining the best solution.
| Item Type: | Conference or Workshop Item (Lecture) |
|---|---|
| Additional Information: | Indexed by SCOPUS |
| Uncontrolled Keywords: | Bandpass filters; Combinatorial optimization; Manufacture; Problem solving |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures |
| Faculty/Division: | Faculty of Electrical & Electronic Engineering Faculty of Manufacturing Engineering |
| Depositing User: | Mrs. Neng Sury Sulaiman |
| Date Deposited: | 25 Apr 2019 03:42 |
| Last Modified: | 25 Apr 2019 03:42 |
| URI: | http://umpir.ump.edu.my/id/eprint/23320 |
| Download Statistic: | View Download Statistics |
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