Predictive maintenance via integrated automatic and statistical process control

Irad Ben-Gal; Jingshan Li; Evgeni Khmelnitsky

Predictive maintenance via integrated automatic and statistical process control

Irad Ben-Gal
, Jingshan Li
, Evgeni Khmelnitsky

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

This paper proposes a methodology for predictive maintenance of a production system by integrating automatic process control (APC) and statistical process control (SPC). In particular, the integrated methodology is based on three main components: A) a Markov chain model that describes the production systems undergoing maintenance activities; b) stochastic optimal control methods that formulate the dynamics of the system, and a state-costate analysis based on the maximum principle that characterizes the properties of the optimal feedback rule; c) a Markov-based SPC (MSPC) method that monitors the resultant state-dependent process.

Original language	English
Title of host publication	IIE Annual Conference and Expo 2010 Proceedings
Publisher	Institute of Industrial Engineers
Publication status	Published - 2010
Externally published	Yes
Event	IIE Annual Conference and Expo 2010 - Cancun, Mexico Duration: 5 Jun 2010 → 9 Jun 2010

Publication series

Name	IIE Annual Conference and Expo 2010 Proceedings

Conference

Conference	IIE Annual Conference and Expo 2010
Place	Mexico
City	Cancun
Period	5/06/10 → 9/06/10

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

APC
Markov chain
Predictive maintenance
SPC
State-costate analysis
Stochastic optimal control

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Cite this

@inproceedings{eccaccfe364c44cfa34eed3076a01101,

title = "Predictive maintenance via integrated automatic and statistical process control",

abstract = "This paper proposes a methodology for predictive maintenance of a production system by integrating automatic process control (APC) and statistical process control (SPC). In particular, the integrated methodology is based on three main components: A) a Markov chain model that describes the production systems undergoing maintenance activities; b) stochastic optimal control methods that formulate the dynamics of the system, and a state-costate analysis based on the maximum principle that characterizes the properties of the optimal feedback rule; c) a Markov-based SPC (MSPC) method that monitors the resultant state-dependent process.",

keywords = "APC, Markov chain, Predictive maintenance, SPC, State-costate analysis, Stochastic optimal control",

author = "Irad Ben-Gal and Jingshan Li and Evgeni Khmelnitsky",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].; IIE Annual Conference and Expo 2010 ; Conference date: 05-06-2010 Through 09-06-2010",

year = "2010",

language = "English",

series = "IIE Annual Conference and Expo 2010 Proceedings",

publisher = "Institute of Industrial Engineers",

booktitle = "IIE Annual Conference and Expo 2010 Proceedings",

}

Predictive maintenance via integrated automatic and statistical process control. / Ben-Gal, Irad; Li, Jingshan; Khmelnitsky, Evgeni.
IIE Annual Conference and Expo 2010 Proceedings. Institute of Industrial Engineers, 2010. (IIE Annual Conference and Expo 2010 Proceedings).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Predictive maintenance via integrated automatic and statistical process control

AU - Ben-Gal, Irad

AU - Li, Jingshan

AU - Khmelnitsky, Evgeni

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2010

Y1 - 2010

N2 - This paper proposes a methodology for predictive maintenance of a production system by integrating automatic process control (APC) and statistical process control (SPC). In particular, the integrated methodology is based on three main components: A) a Markov chain model that describes the production systems undergoing maintenance activities; b) stochastic optimal control methods that formulate the dynamics of the system, and a state-costate analysis based on the maximum principle that characterizes the properties of the optimal feedback rule; c) a Markov-based SPC (MSPC) method that monitors the resultant state-dependent process.

AB - This paper proposes a methodology for predictive maintenance of a production system by integrating automatic process control (APC) and statistical process control (SPC). In particular, the integrated methodology is based on three main components: A) a Markov chain model that describes the production systems undergoing maintenance activities; b) stochastic optimal control methods that formulate the dynamics of the system, and a state-costate analysis based on the maximum principle that characterizes the properties of the optimal feedback rule; c) a Markov-based SPC (MSPC) method that monitors the resultant state-dependent process.

KW - APC

KW - Markov chain

KW - Predictive maintenance

KW - SPC

KW - State-costate analysis

KW - Stochastic optimal control

UR - https://www.scopus.com/pages/publications/84901037119

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84901037119&origin=recordpage

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - IIE Annual Conference and Expo 2010 Proceedings

BT - IIE Annual Conference and Expo 2010 Proceedings

PB - Institute of Industrial Engineers

T2 - IIE Annual Conference and Expo 2010

Y2 - 5 June 2010 through 9 June 2010

ER -

Predictive maintenance via integrated automatic and statistical process control

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Research Keywords

Other Access Options

Permanent Link

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Cite this