Integrated analysis of productivity and machine condition degradation: A geometric-machine case

Yunyi Kang, Feng Ju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We consider a two-machine-one-buffer production system with each machine's condition following a certain degradation process. An analytical model of the integration of machine condition degradation and productivity is introduced. Analytical methods based on the Markov chain approach are developed to quantify the interaction between machine condition degradation process and the overall system performance. In addition, system-theoretical properties are investigated to provide insight on how the system parameters affect the system performance. These methods provide a quantitative tool for modeling, analyzing, and improving manufacturing systems with tight interactions between machine condition degradation and productivity.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
PublisherIEEE Computer Society
Pages1128-1133
Number of pages6
Volume2016-November
ISBN (Electronic)9781509024094
DOIs
StatePublished - Nov 14 2016
Event2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 - Fort Worth, United States
Duration: Aug 21 2016Aug 24 2016

Other

Other2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
CountryUnited States
CityFort Worth
Period8/21/168/24/16

Fingerprint

Productivity
Degradation
Markov processes
Analytical models

Keywords

  • Geometric machine
  • integration
  • Machine condition degradation
  • throughput analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Kang, Y., & Ju, F. (2016). Integrated analysis of productivity and machine condition degradation: A geometric-machine case. In 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 (Vol. 2016-November, pp. 1128-1133). [7743531] IEEE Computer Society. https://doi.org/10.1109/COASE.2016.7743531

Integrated analysis of productivity and machine condition degradation : A geometric-machine case. / Kang, Yunyi; Ju, Feng.

2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. Vol. 2016-November IEEE Computer Society, 2016. p. 1128-1133 7743531.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kang, Y & Ju, F 2016, Integrated analysis of productivity and machine condition degradation: A geometric-machine case. in 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. vol. 2016-November, 7743531, IEEE Computer Society, pp. 1128-1133, 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016, Fort Worth, United States, 8/21/16. https://doi.org/10.1109/COASE.2016.7743531
Kang Y, Ju F. Integrated analysis of productivity and machine condition degradation: A geometric-machine case. In 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. Vol. 2016-November. IEEE Computer Society. 2016. p. 1128-1133. 7743531 https://doi.org/10.1109/COASE.2016.7743531
Kang, Yunyi ; Ju, Feng. / Integrated analysis of productivity and machine condition degradation : A geometric-machine case. 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. Vol. 2016-November IEEE Computer Society, 2016. pp. 1128-1133
@inproceedings{78438a75041446129aa5d020be7480f2,
title = "Integrated analysis of productivity and machine condition degradation: A geometric-machine case",
abstract = "We consider a two-machine-one-buffer production system with each machine's condition following a certain degradation process. An analytical model of the integration of machine condition degradation and productivity is introduced. Analytical methods based on the Markov chain approach are developed to quantify the interaction between machine condition degradation process and the overall system performance. In addition, system-theoretical properties are investigated to provide insight on how the system parameters affect the system performance. These methods provide a quantitative tool for modeling, analyzing, and improving manufacturing systems with tight interactions between machine condition degradation and productivity.",
keywords = "Geometric machine, integration, Machine condition degradation, throughput analysis",
author = "Yunyi Kang and Feng Ju",
year = "2016",
month = "11",
day = "14",
doi = "10.1109/COASE.2016.7743531",
language = "English (US)",
volume = "2016-November",
pages = "1128--1133",
booktitle = "2016 IEEE International Conference on Automation Science and Engineering, CASE 2016",
publisher = "IEEE Computer Society",
address = "United States",

}

TY - GEN

T1 - Integrated analysis of productivity and machine condition degradation

T2 - A geometric-machine case

AU - Kang, Yunyi

AU - Ju, Feng

PY - 2016/11/14

Y1 - 2016/11/14

N2 - We consider a two-machine-one-buffer production system with each machine's condition following a certain degradation process. An analytical model of the integration of machine condition degradation and productivity is introduced. Analytical methods based on the Markov chain approach are developed to quantify the interaction between machine condition degradation process and the overall system performance. In addition, system-theoretical properties are investigated to provide insight on how the system parameters affect the system performance. These methods provide a quantitative tool for modeling, analyzing, and improving manufacturing systems with tight interactions between machine condition degradation and productivity.

AB - We consider a two-machine-one-buffer production system with each machine's condition following a certain degradation process. An analytical model of the integration of machine condition degradation and productivity is introduced. Analytical methods based on the Markov chain approach are developed to quantify the interaction between machine condition degradation process and the overall system performance. In addition, system-theoretical properties are investigated to provide insight on how the system parameters affect the system performance. These methods provide a quantitative tool for modeling, analyzing, and improving manufacturing systems with tight interactions between machine condition degradation and productivity.

KW - Geometric machine

KW - integration

KW - Machine condition degradation

KW - throughput analysis

UR - http://www.scopus.com/inward/record.url?scp=85001065676&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85001065676&partnerID=8YFLogxK

U2 - 10.1109/COASE.2016.7743531

DO - 10.1109/COASE.2016.7743531

M3 - Conference contribution

AN - SCOPUS:85001065676

VL - 2016-November

SP - 1128

EP - 1133

BT - 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016

PB - IEEE Computer Society

ER -