A scatter simulated annealing algorithm for the bi-objective scheduling problem for the wet station of semiconductor manufacturing

Pang, Jihong; Zhou, Hongming; Tsai, Yi-Cheng; Chou, Fuh-Der

doi:10.1016/j.cie.2018.06.017

Cited by 73 publications

(28 citation statements)

References 54 publications

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“…Scheduling is another concern in semiconductor manufacturing due to its vast number of steps and jobs [158][159][160], confirmed by the majority of the identified studies in Table 6. Efficient order scheduling structures are required for balancing the production load and capacity throughout all the production stages [161].…”

Section: Data Mining Applications For Production and Production Schedmentioning

confidence: 81%

A Review of Data Mining Applications in Semiconductor Manufacturing

Espadinha-Cruz

Godina

Rodrigues³

2021

Processes

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For decades, industrial companies have been collecting and storing high amounts of data with the aim of better controlling and managing their processes. However, this vast amount of information and hidden knowledge implicit in all of this data could be utilized more efficiently. With the help of data mining techniques unknown relationships can be systematically discovered. The production of semiconductors is a highly complex process, which entails several subprocesses that employ a diverse array of equipment. The size of the semiconductors signifies a high number of units can be produced, which require huge amounts of data in order to be able to control and improve the semiconductor manufacturing process. Therefore, in this paper a structured review is made through a sample of 137 papers of the published articles in the scientific community regarding data mining applications in semiconductor manufacturing. A detailed bibliometric analysis is also made. All data mining applications are classified in function of the application area. The results are then analyzed and conclusions are drawn.

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Section: Data Mining Applications For Production and Production Schedmentioning

confidence: 81%

A Review of Data Mining Applications in Semiconductor Manufacturing

Espadinha-Cruz

Godina

Rodrigues³

2021

Processes

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“…In some cases of steel processing or semiconductor manufacturing, the maintenance start time depends on a specific threshold value such as maximum continuous working time or maximum dirt. is kind of assumption can be found in Qi et al [18], Mosheiov and Sarig [19], Cui and Lu [20], Su and Wang [21], Pang et al [22], Huang et al [23], Chung et al [24], etc. Another deterministic case is when the maintenance period [u, v] is arranged in advance and maintenance operations should be undertaken within the period [u, v], where the maintenance time (w) is not longer than the maintenance period, i.e., w ≤ (v − u).…”

Section: Introductionmentioning

confidence: 99%

Single-Machine Scheduling with Fixed Periodic Preventive Maintenance to Minimise the Total Weighted Completion Times

Zhou

Tsai

Huang

et al. 2021

Mathematical Problems in Engineering

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The single-machine scheduling problem with fixed periodic preventive maintenance, in which preventive maintenance is implemented periodically to maintain good machine operational status and decrease the cost caused by sudden machine failure, is studied in this paper. The adopted objective function is to minimise the total weighted completion time, which is representative of the minimisation of the global holding/inventory cost in the system. This problem is proven to be NP-hard; a position-based mixed integer programming model and an efficient heuristic algorithm with local improvement strategy are developed for the total weighted completion time problem. To evaluate the performances of the proposed heuristic algorithms, two new lower bounds are further developed. Computational experiments show that the proposed heuristic can rapidly achieve optimal results for small-sized problems and obtain near-optimal solutions with tight average relative percentage deviation for large-sized problems.

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“…Li, Liu, Zhang, & Ye, 2016), secure encryption (Y. , image filtering (H. Zhao, Gao, Wang, Pan, & Graphics, 2016;H. Zhao, Jiang, Jin, Du, & Li, 2018), image editing (Xujie Li, Huang, Zhao, Wang, & Hu, 2020;, structural topology optimization (Shaohua Zhang, Li, Zhong, & Xiang, 2014), scheduling problem (Pang, Zhou, Tsai, & Chou, 2018;H. Zhou, Pang, Chen, & Chou, 2018), face recognition and micro-expression recognition (S. J.…”

Section: Introductionmentioning

confidence: 99%

Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts

Yang

Chen

Heidari

et al. 2021

Expert Systems with Applications

822

301

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

show abstract

A scatter simulated annealing algorithm for the bi-objective scheduling problem for the wet station of semiconductor manufacturing

Cited by 73 publications

References 54 publications

A Review of Data Mining Applications in Semiconductor Manufacturing

A Review of Data Mining Applications in Semiconductor Manufacturing

Single-Machine Scheduling with Fixed Periodic Preventive Maintenance to Minimise the Total Weighted Completion Times

Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts

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