Optimizing capacity assignment of multiple identical metrology tools

Stéphane Dauzère-Pérès; Michael Hassoun; Alejandro Sendon

doi:10.1109/WSC.2016.7822308

Optimizing capacity assignment of multiple identical metrology tools

Stéphane Dauzère-Pérès
, Michael Hassoun
, Alejandro Sendon

Department of Industrial Engineering and Management

Ariel University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In modern semiconductor manufacturing facilities, metrology capacity is becoming limited because of the high equipment cost. This paper studies the problem of optimally assigning the capacity of multiple identical metrology tools in order to minimize the risk of defective wafers on heterogeneous production machines. We assume that the output of each production machine is assigned to only one metrology tool. The resulting problem is formulated as a Multiple Choice Multiple Knapsack Problem (MCMKP), which combines the Multiple Choice Knapsack Problem and the Multiple Knapsack Problem and does not appear to have been studied in the literature. A greedy heuristic and an improving heuristic are also proposed. Numerical experiments are performed on randomly generated instances to analyze and compare the solutions of the heuristics with solutions obtained with a standard solver.

Original language	American English
Title of host publication	2016 Winter Simulation Conference
Subtitle of host publication	Simulating Complex Service Systems, WSC 2016
Editors	Theresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
Pages	2709-2718
Number of pages	10
ISBN (Electronic)	9781509044863
DOIs	https://doi.org/10.1109/WSC.2016.7822308
State	Published - 2 Jul 2016
Event	2016 Winter Simulation Conference, WSC 2016 - Arlington, United States Duration: 11 Dec 2016 → 14 Dec 2016

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	0

Conference

Conference	2016 Winter Simulation Conference, WSC 2016
Country/Territory	United States
City	Arlington
Period	11/12/16 → 14/12/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

ASJC Scopus subject areas

Software
Modelling and Simulation
Computer Science Applications

Access to Document

10.1109/WSC.2016.7822308

Cite this

Dauzère-Pérès, S., Hassoun, M., & Sendon, A. (2016). Optimizing capacity assignment of multiple identical metrology tools. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (pp. 2709-2718). Article 7822308 (Proceedings - Winter Simulation Conference; Vol. 0). https://doi.org/10.1109/WSC.2016.7822308

@inproceedings{b7896ed498264d1794b0b7d9bf39a1d6,

title = "Optimizing capacity assignment of multiple identical metrology tools",

abstract = "In modern semiconductor manufacturing facilities, metrology capacity is becoming limited because of the high equipment cost. This paper studies the problem of optimally assigning the capacity of multiple identical metrology tools in order to minimize the risk of defective wafers on heterogeneous production machines. We assume that the output of each production machine is assigned to only one metrology tool. The resulting problem is formulated as a Multiple Choice Multiple Knapsack Problem (MCMKP), which combines the Multiple Choice Knapsack Problem and the Multiple Knapsack Problem and does not appear to have been studied in the literature. A greedy heuristic and an improving heuristic are also proposed. Numerical experiments are performed on randomly generated instances to analyze and compare the solutions of the heuristics with solutions obtained with a standard solver.",

author = "St{\'e}phane Dauz{\`e}re-P{\'e}r{\`e}s and Michael Hassoun and Alejandro Sendon",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 Winter Simulation Conference, WSC 2016 ; Conference date: 11-12-2016 Through 14-12-2016",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/WSC.2016.7822308",

language = "American English",

series = "Proceedings - Winter Simulation Conference",

pages = "2709--2718",

editor = "Roeder, \{Theresa M.\} and Frazier, \{Peter I.\} and Robert Szechtman and Enlu Zhou",

booktitle = "2016 Winter Simulation Conference",

}

Dauzère-Pérès, S, Hassoun, M & Sendon, A 2016, Optimizing capacity assignment of multiple identical metrology tools. in TM Roeder, PI Frazier, R Szechtman & E Zhou (eds), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016., 7822308, Proceedings - Winter Simulation Conference, vol. 0, pp. 2709-2718, 2016 Winter Simulation Conference, WSC 2016, Arlington, United States, 11/12/16. https://doi.org/10.1109/WSC.2016.7822308

Optimizing capacity assignment of multiple identical metrology tools. / Dauzère-Pérès, Stéphane; Hassoun, Michael; Sendon, Alejandro.
2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. ed. / Theresa M. Roeder; Peter I. Frazier; Robert Szechtman; Enlu Zhou. 2016. p. 2709-2718 7822308 (Proceedings - Winter Simulation Conference; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Optimizing capacity assignment of multiple identical metrology tools

AU - Dauzère-Pérès, Stéphane

AU - Hassoun, Michael

AU - Sendon, Alejandro

PY - 2016/7/2

Y1 - 2016/7/2

N2 - In modern semiconductor manufacturing facilities, metrology capacity is becoming limited because of the high equipment cost. This paper studies the problem of optimally assigning the capacity of multiple identical metrology tools in order to minimize the risk of defective wafers on heterogeneous production machines. We assume that the output of each production machine is assigned to only one metrology tool. The resulting problem is formulated as a Multiple Choice Multiple Knapsack Problem (MCMKP), which combines the Multiple Choice Knapsack Problem and the Multiple Knapsack Problem and does not appear to have been studied in the literature. A greedy heuristic and an improving heuristic are also proposed. Numerical experiments are performed on randomly generated instances to analyze and compare the solutions of the heuristics with solutions obtained with a standard solver.

AB - In modern semiconductor manufacturing facilities, metrology capacity is becoming limited because of the high equipment cost. This paper studies the problem of optimally assigning the capacity of multiple identical metrology tools in order to minimize the risk of defective wafers on heterogeneous production machines. We assume that the output of each production machine is assigned to only one metrology tool. The resulting problem is formulated as a Multiple Choice Multiple Knapsack Problem (MCMKP), which combines the Multiple Choice Knapsack Problem and the Multiple Knapsack Problem and does not appear to have been studied in the literature. A greedy heuristic and an improving heuristic are also proposed. Numerical experiments are performed on randomly generated instances to analyze and compare the solutions of the heuristics with solutions obtained with a standard solver.

UR - https://www.scopus.com/pages/publications/85014249783

U2 - 10.1109/WSC.2016.7822308

DO - 10.1109/WSC.2016.7822308

M3 - Conference contribution

T3 - Proceedings - Winter Simulation Conference

SP - 2709

EP - 2718

BT - 2016 Winter Simulation Conference

A2 - Roeder, Theresa M.

A2 - Frazier, Peter I.

A2 - Szechtman, Robert

A2 - Zhou, Enlu

T2 - 2016 Winter Simulation Conference, WSC 2016

Y2 - 11 December 2016 through 14 December 2016

ER -

Optimizing capacity assignment of multiple identical metrology tools

Abstract

Publication series

Conference

UN SDGs

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this