A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations

Mönch, Lars; Fowler, John W.; Dauzère‐Pérès, Stéphane; Mason, Scott J.; Rose, Oliver

doi:10.1007/s10951-010-0222-9

Cited by 320 publications

(101 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A major area of OR for manufacturing applications is production scheduling [72]. Solutions to scheduling problems can lead to improved performance through optimal use of resources.…”

Section: Operations Research Methodsmentioning

confidence: 99%

Methods and Tools for Performance Assurance of Smart Manufacturing Systems

Kibira

Morris

Kumaraguru

2016

J. RES. NATL. INST. STAN.

View full text Add to dashboard Cite

The emerging concept of smart manufacturing systems is defined in part by the introduction of new technologies that are promoting rapid and widespread information flow within the manufacturing system and surrounding its control. These systems can deliver unprecedented awareness, agility, productivity, and resilience within the production process by exploiting the ever-increasing availability of real-time manufacturing data. Optimized collection and analysis of this voluminous data to guide decision-making is, however, a complex and dynamic process. To establish and maintain confidence that smart manufacturing systems function as intended, performance assurance measures will be vital. The activities for performance assurance span manufacturing system design, operation, performance assessment, evaluation, analysis, decision making, and control. Changes may be needed for traditional approaches in these activities to address smart manufacturing systems. This paper reviews the current methods and tools used for establishing and maintaining required system performance. It then identifies trends in data and information systems, integration, performance measurement, analysis, and performance improvement that will be vital for assured performance of smart manufacturing systems. Finally, we analyze how those trends apply to the methods studied and propose future research for assessing and improving manufacturing performance in the uncertain, multi-objective operating environment.

show abstract

“…A major area of OR for manufacturing applications is production scheduling [72]. Solutions to scheduling problems can lead to improved performance through optimal use of resources.…”

Section: Operations Research Methodsmentioning

confidence: 99%

Methods and Tools for Performance Assurance of Smart Manufacturing Systems

Kibira

Morris

Kumaraguru

2016

J. RES. NATL. INST. STAN.

View full text Add to dashboard Cite

show abstract

“…Potts and Kovalyov (2000) review the research related with different machine environments and several types of objectives. Sivakumar (2003, 2006) and Mönch, Fowler, Dauzere-Peres, Mason and Rose (2011) especially focus on BPM scheduling problems which arise in semiconductor manufacturing. Xiao and Shao (2013) review BPM scheduling problem by emphasizing both job sizes and processing time.…”

Section: Related Workmentioning

confidence: 99%

Mathematical models for a batch scheduling problem to minimize earliness and tardiness

Ogun¹,

Alabaş-Uslu²

2018

JIEM

View full text Add to dashboard Cite

Abstract:Purpose: Today's manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem has been addressed to enable on-time completion of customer orders in a lean manufacturing environment. The problem is optimizing the partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components.Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid excess final product inventory. The first model is a non-linear integer programming model whereas the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings:Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times compared to the other two models. It has also been showed that the alternative model is able to solve moderate sized real-world problems. Originality/value:The problem under study differentiates from existing batch scheduling problems in the literature owing to the inclusion of new circumstances that are present in real-world applications. Those are: customer orders consisting of multi-products made of multi-parts, processing of all parts of the same product from different orders in the same batch, and delivering the orders only when all related products are completed. This research also contributes to the literature of batch scheduling problem by presenting new optimization models.

show abstract

“…According to miniaturization, speed acceleration and mass storage in semiconductor, not only manufacturing process to form chip on wafer but also packaging process to install the completed chip on circuit is continuously being developed (Mönch et al, 2011;Nakamura et al, 2013;Joyce et al, 2015). There is not a single part unimportant in packaging process, but interconnecting technology connecting chip and package which enables to interact electrically and structurally is considered as most the important.…”

Section: Introductionmentioning

confidence: 99%

Influence of Fluoride Ions Contamination in Front Opening Unified Pod (FOUP) Generating Defective Bonding Pad

Kwon

Hwang

Kim

et al. 2017

Aerosol Air Qual. Res.

View full text Add to dashboard Cite

We analyzed defective bonding pad in various ways and determined the causes of defects that boosts oxidation of aluminium by fluoride residue on surface of pad with moisture. Additionally, we compared and evaluated methods to minimize pad defects in aspects such as etching and wafer storage environment. In case of wafers after pad open etching process using common CF 4 stored in FOUP, the concentration of fluoride ions in FOUP was 230 ng L -1 and it decreased down to 170 ng L -1 when Ar sputtering step was added after using CF 4 . Also under the same condition, fluoride ion concentration in FOUP decreased down to 20 ng L -1 when nitrogen purge was introduced for 10 minutes to the FOUP where wafers were stored and the moisture also decreased from 40% before purge to 10% after purge. As a result of observation on pad surface after storing wafers in FOUP for 120 hours under each condition, negligible amount of defects were found when nitrogen was purged. Therefore, we conclude that defects on pad were generated by existing fluoride ions after etching process and moisture in the air.

show abstract

A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations

Cited by 320 publications

References 84 publications

Methods and Tools for Performance Assurance of Smart Manufacturing Systems

Methods and Tools for Performance Assurance of Smart Manufacturing Systems

Mathematical models for a batch scheduling problem to minimize earliness and tardiness

Influence of Fluoride Ions Contamination in Front Opening Unified Pod (FOUP) Generating Defective Bonding Pad

Contact Info

Product

Resources

About