A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance
Probabilistic Boolean Networks (PBN) can model the dynamics of complex biological systems, as well as other non-biological systems like manufacturing systems and smart grids. In this proof-of-concept paper, we propose a PBN architecture with a learning process that significantly enhances fault and f...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/27/5/463 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849327647277973504 |
|---|---|
| author | Pedro Juan Rivera Torres Chen Chen Sara Rodríguez González Orestes Llanes Santiago |
| author_facet | Pedro Juan Rivera Torres Chen Chen Sara Rodríguez González Orestes Llanes Santiago |
| author_sort | Pedro Juan Rivera Torres |
| collection | DOAJ |
| description | Probabilistic Boolean Networks (PBN) can model the dynamics of complex biological systems, as well as other non-biological systems like manufacturing systems and smart grids. In this proof-of-concept paper, we propose a PBN architecture with a learning process that significantly enhances fault and failure prediction in manufacturing systems. This concept was tested using a PBN model of an ultrasound welding process and its machines. Through various experiments, the model successfully learned to maintain a normal operating state. Leveraging the complex properties of PBNs, we utilize them as an adaptive learning tool with positive feedback, demonstrating that these networks may have broader applications than previously recognized. This multi-layered PBN architecture offers substantial improvements in fault detection performance within a positive feedback network structure that shows greater noise tolerance than other methods. |
| format | Article |
| id | doaj-art-5beb048b59f5490eb64d31ecaccf002b |
| institution | Kabale University |
| issn | 1099-4300 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-5beb048b59f5490eb64d31ecaccf002b2025-08-20T03:47:49ZengMDPI AGEntropy1099-43002025-04-0127546310.3390/e27050463A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset MaintenancePedro Juan Rivera Torres0Chen Chen1Sara Rodríguez González2Orestes Llanes Santiago3Departmento de Informática y Automática, Universidad de Salamanca, Patio de las Escuelas 1, 37006 Salamanca, SpainSt. Edmund’s College, University of Cambridge, Mount Pleasant, Cambridge CB3 0BN, UKDepartmento de Informática y Automática, Universidad de Salamanca, Patio de las Escuelas 1, 37006 Salamanca, SpainDepartamento de Automática y Computación, Universidad Tecnológica de La Habana José Antonio Echeverría (CUJAE), Marianao, La Habana 11500, CubaProbabilistic Boolean Networks (PBN) can model the dynamics of complex biological systems, as well as other non-biological systems like manufacturing systems and smart grids. In this proof-of-concept paper, we propose a PBN architecture with a learning process that significantly enhances fault and failure prediction in manufacturing systems. This concept was tested using a PBN model of an ultrasound welding process and its machines. Through various experiments, the model successfully learned to maintain a normal operating state. Leveraging the complex properties of PBNs, we utilize them as an adaptive learning tool with positive feedback, demonstrating that these networks may have broader applications than previously recognized. This multi-layered PBN architecture offers substantial improvements in fault detection performance within a positive feedback network structure that shows greater noise tolerance than other methods.https://www.mdpi.com/1099-4300/27/5/463fault detection and isolationmachine learning algorithmsprobabilistic Boolean networksprobabilistic Boolean network modeling |
| spellingShingle | Pedro Juan Rivera Torres Chen Chen Sara Rodríguez González Orestes Llanes Santiago A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance Entropy fault detection and isolation machine learning algorithms probabilistic Boolean networks probabilistic Boolean network modeling |
| title | A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance |
| title_full | A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance |
| title_fullStr | A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance |
| title_full_unstemmed | A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance |
| title_short | A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance |
| title_sort | learning probabilistic boolean network model of a manufacturing process with applications in system asset maintenance |
| topic | fault detection and isolation machine learning algorithms probabilistic Boolean networks probabilistic Boolean network modeling |
| url | https://www.mdpi.com/1099-4300/27/5/463 |
| work_keys_str_mv | AT pedrojuanriveratorres alearningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT chenchen alearningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT sararodriguezgonzalez alearningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT orestesllanessantiago alearningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT pedrojuanriveratorres learningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT chenchen learningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT sararodriguezgonzalez learningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance AT orestesllanessantiago learningprobabilisticbooleannetworkmodelofamanufacturingprocesswithapplicationsinsystemassetmaintenance |