Current status of machine prognostics in condition-based maintenance: a review
Condition-based maintenance (CBM) is a decision-making strategy based on real-time diagnosis of impending failures and prognosis of future equipment health. It is a proactive process that requires the development of a predictive model that can trigger the alarm for corresponding maintenance. Prognos...
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| Published in | International journal of advanced manufacturing technology Vol. 50; no. 1-4; pp. 297 - 313 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer-Verlag
01.09.2010
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0268-3768 1433-3015 |
| DOI | 10.1007/s00170-009-2482-0 |
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| Abstract | Condition-based maintenance (CBM) is a decision-making strategy based on real-time diagnosis of impending failures and prognosis of future equipment health. It is a proactive process that requires the development of a predictive model that can trigger the alarm for corresponding maintenance. Prognostic methodologies for CBM have only recently been introduced into the technical literature and become such a focus in the field of maintenance research and development. There are many research and development on a variety of technologies and algorithms that can be regarded as the steps toward prognostic maintenance. They are needed in order to support decision making and manage operational reliability. In this paper, recent literature that focuses on the machine prognostics has been reviewed. Generally, prognostic models can be classified into four categories: physical model, knowledge-based model, data-driven model, and combination model. Various techniques and algorithms have been developed depending on what models they usually adopt. Based on the review of some typical approaches and new introduced methods, advantages and disadvantages of these methodologies are discussed. From the literature review, some increasing trends appeared in the research field of machine prognostics are summarized. Furthermore, the future research directions have been explored. |
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| AbstractList | Condition-based maintenance (CBM) is a decision-making strategy based on real-time diagnosis of impending failures and prognosis of future equipment health. It is a proactive process that requires the development of a predictive model that can trigger the alarm for corresponding maintenance. Prognostic methodologies for CBM have only recently been introduced into the technical literature and become such a focus in the field of maintenance research and development. There are many research and development on a variety of technologies and algorithms that can be regarded as the steps toward prognostic maintenance. They are needed in order to support decision making and manage operational reliability. In this paper, recent literature that focuses on the machine prognostics has been reviewed. Generally, prognostic models can be classified into four categories: physical model, knowledge-based model, data-driven model, and combination model. Various techniques and algorithms have been developed depending on what models they usually adopt. Based on the review of some typical approaches and new introduced methods, advantages and disadvantages of these methodologies are discussed. From the literature review, some increasing trends appeared in the research field of machine prognostics are summarized. Furthermore, the future research directions have been explored. |
| Author | Zuo, Ming Jian Peng, Ying Dong, Ming |
| Author_xml | – sequence: 1 givenname: Ying surname: Peng fullname: Peng, Ying organization: Antai College of Economics & Management, Shanghai Jiao Tong University – sequence: 2 givenname: Ming surname: Dong fullname: Dong, Ming email: mdong@sjtu.edu.cn organization: Antai College of Economics & Management, Shanghai Jiao Tong University – sequence: 3 givenname: Ming Jian surname: Zuo fullname: Zuo, Ming Jian organization: Department of Mechanical Engineering, University of Alberta |
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| Title | Current status of machine prognostics in condition-based maintenance: a review |
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