An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study
Making the correct maintenance strategy decision for industrial multistage machines (MSTM) is a constant challenge for industrial manufacturers. Preventive maintenance strategies are the most popular and provide interesting results but cannot prevent unexpected failures and consequences, such as tim...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/10/5/175 |
| _version_ | 1797469772150996992 |
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| author | Francisco Javier Álvarez García David Rodríguez Salgado |
| author_facet | Francisco Javier Álvarez García David Rodríguez Salgado |
| author_sort | Francisco Javier Álvarez García |
| collection | DOAJ |
| description | Making the correct maintenance strategy decision for industrial multistage machines (MSTM) is a constant challenge for industrial manufacturers. Preventive maintenance strategies are the most popular and provide interesting results but cannot prevent unexpected failures and consequences, such as time lost production (TLP). In these cases, a predictive maintenance strategy should be used to maintain the appropriate level of operation time. This research aims to present a model to identify the component that failed before its mean time to failure (MTTF) and, depending on whether the cause of the failure is known, propose the use of a predictive maintenance strategy and further decision-making to ensure the highest possible value from operating time. Also, it is necessary to check the reliable value of MTTF before taking certain decisions. For this research, a real case study of a MSTM was characterized component by component, setting the individual maintenance times. The initial maintenance strategy used for all the components is the preventive programming maintenance (PPM). If a component presents an unexpected failure, a method is proposed to decide whether the maintenance strategy should be changed, adding a predictive maintenance strategy to monitor said component. The research also provides a trust level to evaluate the reliable value of MTTF of each component. The authors consider this approach very useful for machine manufacturers and end users. |
| first_indexed | 2024-03-09T19:25:53Z |
| format | Article |
| id | doaj.art-7cd85c0ded284d0b9d5b9135dbf0e47d |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-09T19:25:53Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-7cd85c0ded284d0b9d5b9135dbf0e47d2023-11-24T02:55:30ZengMDPI AGSystems2079-89542022-09-0110517510.3390/systems10050175An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case StudyFrancisco Javier Álvarez García0David Rodríguez Salgado1Department of Mechanical, Energy and Materials Engineering, University of Extremadura, C/Sta. Teresa de Jornet 38, 06800 Mérida, SpainDepartment of Mechanical, Energy and Materials Engineering, University of Extremadura, Avda. Elvas s/n, 06006 Badajoz, SpainMaking the correct maintenance strategy decision for industrial multistage machines (MSTM) is a constant challenge for industrial manufacturers. Preventive maintenance strategies are the most popular and provide interesting results but cannot prevent unexpected failures and consequences, such as time lost production (TLP). In these cases, a predictive maintenance strategy should be used to maintain the appropriate level of operation time. This research aims to present a model to identify the component that failed before its mean time to failure (MTTF) and, depending on whether the cause of the failure is known, propose the use of a predictive maintenance strategy and further decision-making to ensure the highest possible value from operating time. Also, it is necessary to check the reliable value of MTTF before taking certain decisions. For this research, a real case study of a MSTM was characterized component by component, setting the individual maintenance times. The initial maintenance strategy used for all the components is the preventive programming maintenance (PPM). If a component presents an unexpected failure, a method is proposed to decide whether the maintenance strategy should be changed, adding a predictive maintenance strategy to monitor said component. The research also provides a trust level to evaluate the reliable value of MTTF of each component. The authors consider this approach very useful for machine manufacturers and end users.https://www.mdpi.com/2079-8954/10/5/175predictive maintenancemultistage machinesensorisationdecision-makingmean time to failurealgorithm |
| spellingShingle | Francisco Javier Álvarez García David Rodríguez Salgado An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study Systems predictive maintenance multistage machine sensorisation decision-making mean time to failure algorithm |
| title | An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study |
| title_full | An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study |
| title_fullStr | An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study |
| title_full_unstemmed | An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study |
| title_short | An Approach for Predictive Maintenance Decisions for Components of an Industrial Multistage Machine That Fail before Their MTTF: A Case Study |
| title_sort | approach for predictive maintenance decisions for components of an industrial multistage machine that fail before their mttf a case study |
| topic | predictive maintenance multistage machine sensorisation decision-making mean time to failure algorithm |
| url | https://www.mdpi.com/2079-8954/10/5/175 |
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