Mechanism to minimise the assembly time with feeder assignment for a multi-headed gantry and high-speed SMT machine
- Authors
- Han, Jihee; Seo, Yoonho
- Issue Date
- 2017
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- PCB assembly; assembly planning; pick-and-place; SMT machine; feeder assignment
- Citation
- INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, v.55, no.10, pp.2930 - 2949
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Volume
- 55
- Number
- 10
- Start Page
- 2930
- End Page
- 2949
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/86328
- DOI
- 10.1080/00207543.2016.1229071
- ISSN
- 0020-7543
- Abstract
- This paper proposes the development of a mechanism to minimise the assembly time for a multi-headed gantry and high-speed surface mounting technology machine by determining the component assignment to feeder slots. Since a gantry moves long distances in order to pick components, place them on the board and then return them to the feeder slots, we classified the overall assembly time according to the different movements of a gantry. The overall assembly time is then minimised by presenting a new heuristic for the feeder assignment, consisting of Nearest Component Allocation (NCA) and Globally Updated Assignment (GUA). NCA contains information about how each component type locates closely to others on the board. Using the solution from NCA, the component distance function calculates the most representative distance between component types. Then, GUA is applied to improve the NCA solution. The experiments consist of several printed circuit boards with numbers of component types and points to be placed. Highlights of this paper are that: a classification of the gantry movements is proposed based on the average speed; a heuristic NCA-GUA for feeder assignment is developed by considering the placements on the board; the computational time is greatly reduced by NCA-GUA without degrading the solution quality; and a decision process for nozzle assignment is proposed to minimise the overall assembly time. The results show how NCA and GUA affect the final results, and how this mechanism leads to better performance than a genetic algorithms or 2-opt swap search. This comparison proves that our method provides competitive and effective solutions in terms of minimising the overall assembly time.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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