Back to Search
Start Over
Green Product Module Partition Method Based on Improved Multi-objective Artificial Bee Colony Algorithm
- Source :
- MATEC Web of Conferences, Vol 301, p 00021 (2019)
- Publication Year :
- 2019
- Publisher :
- EDP Sciences, 2019.
-
Abstract
- Modular design is an important design method in the mass customization for manufacturing industry. The purpose of this paper is to meet diverse market demands while reducing the impact of products on the ecological environment. Firstly, aiming at the product life cycle process, this paper summarizes the problems encountered in each stage of the product, and introduces five green product module partition principles. Then, through the component correlation matrix, the resource greenness objective function based on the whole life cycle and the polymerization degree objective function based on the component correlation matrix are established respectively by the axiomatic design theory which makes the product mapping from functional domain to structural domain. Next, an improved artificial bee colony algorithm is proposed. Based on the artificial bee colony algorithm, the algorithm applies congestion strategy and fast nondominated sorting strategy to solve the module partition problem of product platform with multi-objective optimization, and a uniformly distributed pare to solution set is generated. Through above steps, the optimization results of module partition are obtained. Finally, an application example of aircraft tail horizontal stabilizer parts is given, and the advantages of the algorithm are proved by comparing with other algorithms.
- Subjects :
- Engineering (General). Civil engineering (General)
TA1-2040
Subjects
Details
- Language :
- English, French
- ISSN :
- 2261236X
- Volume :
- 301
- Database :
- Directory of Open Access Journals
- Journal :
- MATEC Web of Conferences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.b21dfb451e4443fd9f3553cfe15d7d5c
- Document Type :
- article
- Full Text :
- https://doi.org/10.1051/matecconf/201930100021