A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data

Jiaming Cui; Yihai He; Fengdi Liu; Min Xie

doi:10.1109/RAM.2018.8463125

A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data

Jiaming Cui
, Yihai He
, Fengdi Liu
, Min Xie

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

Abstract

In this paper, a health risk modeling approach based on big operational data is developed for complex manufacturing systems. Focusing on the relationship from processing machine performance to the process quality and the produced product reliability, the connotation of manufacturing system health risk is defined and modeled based on potential impacts of the possible machine degradation on the whole manufacturing process. Then, the concept of big operational data is proposed to provide a data foundation for the comprehensive performance evaluation and prediction of manufacturing systems, where all the original data that correspond to the same output product are organized as a set.

Original language	English
Title of host publication	2018 Annual Reliability and Maintainability Symposium (RAMS)
Publisher	IEEE
ISBN (Electronic)	9781538628706
ISBN (Print)	9781538628713
DOIs	https://doi.org/10.1109/RAM.2018.8463125
Publication status	Published - Jan 2018
Event	2018 Annual Reliability and Maintainability Symposium, RAMS 2018 - Reno, United States Duration: 22 Jan 2018 → 25 Jan 2018

Publication series

Name	Proceedings - Annual Reliability and Maintainability Symposium
Volume	2018-January
ISSN (Print)	0149-144X
ISSN (Electronic)	2577-0993

Conference

Conference	2018 Annual Reliability and Maintainability Symposium, RAMS 2018
Place	United States
City	Reno
Period	22/01/18 → 25/01/18

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

Complex manufacturing system
Health state
Risk modeling
RQR chain

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10.1109/RAM.2018.8463125

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Cite this

@inproceedings{a1c294fd9ec64d928baa25d1aea2809c,

title = "A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data",

abstract = "In this paper, a health risk modeling approach based on big operational data is developed for complex manufacturing systems. Focusing on the relationship from processing machine performance to the process quality and the produced product reliability, the connotation of manufacturing system health risk is defined and modeled based on potential impacts of the possible machine degradation on the whole manufacturing process. Then, the concept of big operational data is proposed to provide a data foundation for the comprehensive performance evaluation and prediction of manufacturing systems, where all the original data that correspond to the same output product are organized as a set.",

keywords = "Complex manufacturing system, Health state, Risk modeling, RQR chain",

author = "Jiaming Cui and Yihai He and Fengdi Liu and Min Xie",

year = "2018",

month = jan,

doi = "10.1109/RAM.2018.8463125",

language = "English",

isbn = "9781538628713",

series = "Proceedings - Annual Reliability and Maintainability Symposium",

publisher = "IEEE",

booktitle = "2018 Annual Reliability and Maintainability Symposium (RAMS)",

address = "United States",

note = "2018 Annual Reliability and Maintainability Symposium, RAMS 2018 ; Conference date: 22-01-2018 Through 25-01-2018",

}

Cui, J, He, Y, Liu, F & Xie, M 2018, A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data. in 2018 Annual Reliability and Maintainability Symposium (RAMS)., 8463125, Proceedings - Annual Reliability and Maintainability Symposium, vol. 2018-January, IEEE, 2018 Annual Reliability and Maintainability Symposium, RAMS 2018, Reno, United States, 22/01/18. https://doi.org/10.1109/RAM.2018.8463125

A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data. / Cui, Jiaming; He, Yihai; Liu, Fengdi et al.
2018 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2018. 8463125 (Proceedings - Annual Reliability and Maintainability Symposium; Vol. 2018-January).

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

TY - GEN

T1 - A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data

AU - Cui, Jiaming

AU - He, Yihai

AU - Liu, Fengdi

AU - Xie, Min

PY - 2018/1

Y1 - 2018/1

N2 - In this paper, a health risk modeling approach based on big operational data is developed for complex manufacturing systems. Focusing on the relationship from processing machine performance to the process quality and the produced product reliability, the connotation of manufacturing system health risk is defined and modeled based on potential impacts of the possible machine degradation on the whole manufacturing process. Then, the concept of big operational data is proposed to provide a data foundation for the comprehensive performance evaluation and prediction of manufacturing systems, where all the original data that correspond to the same output product are organized as a set.

AB - In this paper, a health risk modeling approach based on big operational data is developed for complex manufacturing systems. Focusing on the relationship from processing machine performance to the process quality and the produced product reliability, the connotation of manufacturing system health risk is defined and modeled based on potential impacts of the possible machine degradation on the whole manufacturing process. Then, the concept of big operational data is proposed to provide a data foundation for the comprehensive performance evaluation and prediction of manufacturing systems, where all the original data that correspond to the same output product are organized as a set.

KW - Complex manufacturing system

KW - Health state

KW - Risk modeling

KW - RQR chain

UR - https://www.scopus.com/pages/publications/85054124485

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85054124485&origin=recordpage

U2 - 10.1109/RAM.2018.8463125

DO - 10.1109/RAM.2018.8463125

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

SN - 9781538628713

T3 - Proceedings - Annual Reliability and Maintainability Symposium

BT - 2018 Annual Reliability and Maintainability Symposium (RAMS)

PB - IEEE

T2 - 2018 Annual Reliability and Maintainability Symposium, RAMS 2018

Y2 - 22 January 2018 through 25 January 2018

ER -

A Health Risk Modeling Approach of Complex Manufacturing Systems Based on Big Operational Data

Abstract

Publication series

Conference

UN SDGs

Research Keywords

Access Output

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