COUNTERING MINOR FAILURE BEHAVIORS IN AUTOMATED MANUFACTURING SYSTEMS THROUGH OPPORTUNISTIC PREVENTIVE MAINTENANCE INTERVENTIONS.
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| Title: | COUNTERING MINOR FAILURE BEHAVIORS IN AUTOMATED MANUFACTURING SYSTEMS THROUGH OPPORTUNISTIC PREVENTIVE MAINTENANCE INTERVENTIONS. |
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| Authors: | Hakami, Ali1 amahakami@uqu.edu.sa |
| Source: | International Journal of Industrial Engineering. 2026, Vol. 33 Issue 3, p566-587. 22p. |
| Subjects: | Discrete event simulation, Condition-based maintenance, Manufacturing process automation, Failure mode & effects analysis |
| Abstract: | Maintaining continuous operation in high-throughput manufacturing systems with minor failure (MF) problems is challenging to achieve the target production rate by a specific time horizon. The effective use of the dynamic opportunistic maintenance (OM) approach mitigates interference between the continuous schedule production operation and maintenance tasks. The study suggests a simulation-based model combining active and passive maintenance opportunity windows (AMOW, PMOW), Long-Duration Failure Modes (LDFM), and A and B types of downtimes. We aim to determine optimal maintenance policies to enhance system performance and minimize the impact of minor stoppage MF behaviors that take less than 15 minutes. To implement the OM approach, we chose the water bottling factory as a case study, investigated the system's distinctive behavior, and derived appropriate policies for implementing OM actions. The real-time information on machine failure conditions revealed a significant frequency and duration of MF events. Consequently, a discrete-event simulation DES model was developed and validated using the Simio simulation software to achieve the randomness of MF occurrences and derive its impact on the system's performance. The system was exposed to 113 FM modes in various machines and components. To evaluate the solutions to MF's maintenance problem, we compared the production line's performance with the simulation-based optimization of OptQuest. Two functions were defined: (1) to minimize the occurrences of MF for each machine and (2) to maximize the percentage of throughput rate. Finally, the proposed framework was examined against a benchmark of the conceptual model of the current case. The proposed approach was practical as it outperformed the existing benchmark and showed that it can be practically implemented. The experimental results illustrated an improvement in system throughput of up to 10.73% and a reduction in the impact of MF phenomenon frequency of bottlenecks, machine BM and LB machine by 86% and 92%, respectively. The suggested support framework's implementation entails expenses for simulated modeling, continuous evaluation, and optimization programs such as Simio and OptQuest. Cost savings are achieved, however, since it improves productivity, decreases unscheduled interruptions, and minimizes loss of production. Optimization gains, fewer service interruptions, and higher overall equipment effectiveness (OEE) balance the initial expenditure. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Industrial Engineering is the property of International Journal of Industrial Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: COUNTERING MINOR FAILURE BEHAVIORS IN AUTOMATED MANUFACTURING SYSTEMS THROUGH OPPORTUNISTIC PREVENTIVE MAINTENANCE INTERVENTIONS. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hakami%2C+Ali%22">Hakami, Ali</searchLink><relatesTo>1</relatesTo><i> amahakami@uqu.edu.sa</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Industrial+Engineering%22">International Journal of Industrial Engineering</searchLink>. 2026, Vol. 33 Issue 3, p566-587. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Discrete+event+simulation%22">Discrete event simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Condition-based+maintenance%22">Condition-based maintenance</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+process+automation%22">Manufacturing process automation</searchLink><br /><searchLink fieldCode="DE" term="%22Failure+mode+%26+effects+analysis%22">Failure mode & effects analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Maintaining continuous operation in high-throughput manufacturing systems with minor failure (MF) problems is challenging to achieve the target production rate by a specific time horizon. The effective use of the dynamic opportunistic maintenance (OM) approach mitigates interference between the continuous schedule production operation and maintenance tasks. The study suggests a simulation-based model combining active and passive maintenance opportunity windows (AMOW, PMOW), Long-Duration Failure Modes (LDFM), and A and B types of downtimes. We aim to determine optimal maintenance policies to enhance system performance and minimize the impact of minor stoppage MF behaviors that take less than 15 minutes. To implement the OM approach, we chose the water bottling factory as a case study, investigated the system's distinctive behavior, and derived appropriate policies for implementing OM actions. The real-time information on machine failure conditions revealed a significant frequency and duration of MF events. Consequently, a discrete-event simulation DES model was developed and validated using the Simio simulation software to achieve the randomness of MF occurrences and derive its impact on the system's performance. The system was exposed to 113 FM modes in various machines and components. To evaluate the solutions to MF's maintenance problem, we compared the production line's performance with the simulation-based optimization of OptQuest. Two functions were defined: (1) to minimize the occurrences of MF for each machine and (2) to maximize the percentage of throughput rate. Finally, the proposed framework was examined against a benchmark of the conceptual model of the current case. The proposed approach was practical as it outperformed the existing benchmark and showed that it can be practically implemented. The experimental results illustrated an improvement in system throughput of up to 10.73% and a reduction in the impact of MF phenomenon frequency of bottlenecks, machine BM and LB machine by 86% and 92%, respectively. The suggested support framework's implementation entails expenses for simulated modeling, continuous evaluation, and optimization programs such as Simio and OptQuest. Cost savings are achieved, however, since it improves productivity, decreases unscheduled interruptions, and minimizes loss of production. Optimization gains, fewer service interruptions, and higher overall equipment effectiveness (OEE) balance the initial expenditure. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Industrial Engineering is the property of International Journal of Industrial Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.23055/ijietap.2026.33.3.11339 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 566 Subjects: – SubjectFull: Discrete event simulation Type: general – SubjectFull: Condition-based maintenance Type: general – SubjectFull: Manufacturing process automation Type: general – SubjectFull: Failure mode & effects analysis Type: general Titles: – TitleFull: COUNTERING MINOR FAILURE BEHAVIORS IN AUTOMATED MANUFACTURING SYSTEMS THROUGH OPPORTUNISTIC PREVENTIVE MAINTENANCE INTERVENTIONS. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hakami, Ali IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 10724761 Numbering: – Type: volume Value: 33 – Type: issue Value: 3 Titles: – TitleFull: International Journal of Industrial Engineering Type: main |
| ResultId | 1 |
