Assembly sequence planning using soft computing methods: A review

被引：47
作者：
Deepak, B. B. V. L. [1 ]
Murali, G. Bala [1 ]
Bahubalendruni, M. V. A. Raju [2 ]
Biswal, B. B. [1 ]
机构：
[1] Natl Inst Technol, Dept Ind Design, Rourkela, India
[2] GMR Inst Technol, Dept Mech Engn, Rajam, India
来源：
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING | 2019年 / 233卷 / 03期
关键词：
Artificial intelligence techniques; assembly sequence planning; assembly sequence generation and assembly predicate criteria; ANT COLONY OPTIMIZATION; GENETIC-ALGORITHM; NEURAL-NETWORK; LOCAL SEARCH; GENERATION; DESIGN; STEP; MANUFACTURE; INTEGRATION; PARTS;
D O I：
10.1177/0954408918764459
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
The implementation of artificial intelligence techniques is increasing rapidly in recent years to solve numerous engineering problems. Assembly sequence planning is one of the prominent complex combinatorial problem draw attention of industrial engineers to economize the overall manufacturing cost by minimizing the assembly time and energy. Due to large search space and multiple assembly predicate criteria, researchers are motivated towards efficient utilization of AI techniques to address the problem. Literature review on various artificial intelligence techniques for obtaining the optimal assembly sequence planning are analyzed and the limitations of the existed methodologies are discussed in detail. This review provides an outlook for the researchers on various artificial intell1igent techniques which will be useful to carry out research for obtaining the optimum assembly sequence planning while qualifying various assembly predicate criteria.
引用
收藏
页码：653 / 683
页数：31
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