PERFORMANCE MONITORING AND RELIABLE OPERATIONS OF INDUSTRIAL AUTOMATION USING LOW COST EMBEDDED PLATFORMS.
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| Title: | PERFORMANCE MONITORING AND RELIABLE OPERATIONS OF INDUSTRIAL AUTOMATION USING LOW COST EMBEDDED PLATFORMS. |
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| Authors: | MALWATKAR, GAJANAN M.1 gajanan.malwatkar@gcoej.ac.in, GUND, ANKUSH M.1 ankush.gund@bvcoenm.edu.in, SHILEDAR, SHAKTIKUMAR R.2 shaktikumar.shiledar@gcoej.ac.in |
| Source: | Reliability: Theory & Applications. Mar2026, Vol. 21 Issue 1, p369-382. 14p. |
| Subjects: | Process optimization, Embedded computer systems, Operating costs, Machine learning, Automation, Real-time computing |
| Abstract: | Industrial process optimization and cost reduction are achieved through the monitoring and advancement of automation systems using low cost embedded platforms. The system integration of affordable sensors, transducers, controllers, and advanced control algorithms enhances system efficiency, stability, and responsiveness. Scalable real time monitoring and optimization frameworks improve industrial productivity while minimizing downtime. The proposed implementation incorporates real time data acquisition, fractional order PID (FOPID) control, and mixed integer programming (MIP) based optimization to ensure efficient operation and adaptive performance evolution. The FOPID controller enhances control precision through fractional derivatives and integrals, while Ziegler Nichols tuning (ZNT) optimizes PID stability and response. Machine learning (ML) algorithms are used for data analysis and visualization of the plant parameters, supporting better insight into process dynamics and control decisions. The research demonstrates that the proposed architecture, developed using open-source software and low cost controller boards, effectively improves system performance when integrated with existing hardware. Validation of the approach was carried out using a multi loop process trainer setup available in the laboratory. Future work involves incorporating artificial intelligence (AI) for autonomous control and further enhancement of system adaptability. [ABSTRACT FROM AUTHOR] |
| Copyright of Reliability: Theory & Applications is the property of International Group on Reliability 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 192779644 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: PERFORMANCE MONITORING AND RELIABLE OPERATIONS OF INDUSTRIAL AUTOMATION USING LOW COST EMBEDDED PLATFORMS. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22MALWATKAR%2C+GAJANAN+M%2E%22">MALWATKAR, GAJANAN M.</searchLink><relatesTo>1</relatesTo><i> gajanan.malwatkar@gcoej.ac.in</i><br /><searchLink fieldCode="AR" term="%22GUND%2C+ANKUSH+M%2E%22">GUND, ANKUSH M.</searchLink><relatesTo>1</relatesTo><i> ankush.gund@bvcoenm.edu.in</i><br /><searchLink fieldCode="AR" term="%22SHILEDAR%2C+SHAKTIKUMAR+R%2E%22">SHILEDAR, SHAKTIKUMAR R.</searchLink><relatesTo>2</relatesTo><i> shaktikumar.shiledar@gcoej.ac.in</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Reliability%3A+Theory+%26+Applications%22">Reliability: Theory & Applications</searchLink>. Mar2026, Vol. 21 Issue 1, p369-382. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Embedded+computer+systems%22">Embedded computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Operating+costs%22">Operating costs</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Industrial process optimization and cost reduction are achieved through the monitoring and advancement of automation systems using low cost embedded platforms. The system integration of affordable sensors, transducers, controllers, and advanced control algorithms enhances system efficiency, stability, and responsiveness. Scalable real time monitoring and optimization frameworks improve industrial productivity while minimizing downtime. The proposed implementation incorporates real time data acquisition, fractional order PID (FOPID) control, and mixed integer programming (MIP) based optimization to ensure efficient operation and adaptive performance evolution. The FOPID controller enhances control precision through fractional derivatives and integrals, while Ziegler Nichols tuning (ZNT) optimizes PID stability and response. Machine learning (ML) algorithms are used for data analysis and visualization of the plant parameters, supporting better insight into process dynamics and control decisions. The research demonstrates that the proposed architecture, developed using open-source software and low cost controller boards, effectively improves system performance when integrated with existing hardware. Validation of the approach was carried out using a multi loop process trainer setup available in the laboratory. Future work involves incorporating artificial intelligence (AI) for autonomous control and further enhancement of system adaptability. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Reliability: Theory & Applications is the property of International Group on Reliability 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: 10.24412/1932-2321-2026-190-369-382 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 369 Subjects: – SubjectFull: Process optimization Type: general – SubjectFull: Embedded computer systems Type: general – SubjectFull: Operating costs Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Automation Type: general – SubjectFull: Real-time computing Type: general Titles: – TitleFull: PERFORMANCE MONITORING AND RELIABLE OPERATIONS OF INDUSTRIAL AUTOMATION USING LOW COST EMBEDDED PLATFORMS. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: MALWATKAR, GAJANAN M. – PersonEntity: Name: NameFull: GUND, ANKUSH M. – PersonEntity: Name: NameFull: SHILEDAR, SHAKTIKUMAR R. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19322321 Numbering: – Type: volume Value: 21 – Type: issue Value: 1 Titles: – TitleFull: Reliability: Theory & Applications Type: main |
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