Approach to derive golden paths based on machine sequence patterns in multistage manufacturing process

Chang-Ho Lee (), Dong-Hee Lee (), Young-Mok Bae (), Seung-Hyun Choi (), Ki-Hun Kim () and Kwang-Jae Kim ()
Additional contact information
Chang-Ho Lee: Pohang University of Science and Technology
Dong-Hee Lee: Hanyang University
Young-Mok Bae: SK Hynix
Seung-Hyun Choi: Pohang University of Science and Technology
Ki-Hun Kim: Ulsan National Institute of Science and Technology (UNIST)
Kwang-Jae Kim: Pohang University of Science and Technology

Journal of Intelligent Manufacturing, 2022, vol. 33, issue 1, No 9, 167-183

Abstract: Abstract A multistage manufacturing process (MMP) consists of several consecutive process stages, each of which has multiple machines performing the same functions in parallel. A manufacturing path (simply referred to as path) is defined as an ordered set indicating a record of machines assigned to a product at each process stage of an MMP. An MMP usually produces products through various paths. In practice, multiple machines in a process stage have different operational performances, which accumulate during production and affect the quality of products. This study proposes a heuristic approach to derive the golden paths that produce products whose quality exceeds the desired level. The proposed approach consists of the searching phase and the merging phase. The searching phase extracts two types of machine sequence patterns (MSPs) from a path dataset in an MMP. An MSP is a subset of the path that is defined as an ordered set of assigned machines from several process stages. The two extracted types of MSPs are: (1) superior MSP, which affects the production of superior-quality products, and (2) inferior MSP, which affects the production of inferior-quality products, called inferior MSP. The merging phase derives the golden paths by combining superior MSPs and excluding inferior MSPs. The proposed approach is verified by applying it to a hypothetical path dataset and the semiconductor tool fault isolation (SETFI) dataset. This verification shows that the proposed approach derives the golden paths that exceed the predefined product quality level. This outcome demonstrates the practical viability of the proposed approach in an MMP.

Keywords: Multistage manufacturing process (MMP); Product quality; Golden path; Machine sequence pattern (MSP); Quality engineering (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-020-01654-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:33:y:2022:i:1:d:10.1007_s10845-020-01654-2

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-020-01654-2

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().