{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:14:37Z","timestamp":1760148877145,"version":"build-2065373602"},"reference-count":58,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T00:00:00Z","timestamp":1686700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","award":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"],"award-info":[{"award-number":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"]}]},{"name":"Portuguese Foundation for Science and Technology","award":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"],"award-info":[{"award-number":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"]}]},{"name":"University of Aveiro","award":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"],"award-info":[{"award-number":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"]}]},{"name":"European Regional Development Fund","award":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"],"award-info":[{"award-number":["ref. 2020.06926.BD","reference UIDB\/04106\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>A considerable part of enterprises\u2019 total expenses is dedicated to maintenance interventions. Predictive maintenance (PdM) has appeared as a solution to decrease these costs; however, the necessity of end-to-end solutions in deploying predictive models and the fact that these models are often difficult to interpret by maintenance practitioners hinder the adoption of PdM approaches. In this work, we propose a flexible architecture for PdM to recommend maintenance actions. The proposed architecture is based on containerized microservices on intelligent edge devices together with a hybrid model which fuses generalized fault trees (GFTs) and anomaly detection. Results on injection molds carried out at OLI, a Portuguese company, show that the proposed solution is suitable for deploying predictive models and services such as data preprocessing, sensor management, and data flow control, among others. These services run near the shop floor, allowing for greater flexibility, as they may be remotely managed and customized according to the company\u2019s requirements. The results of the GFT model show an estimated reduction of more than 63% in current maintenance costs, while the distribution of analytics tasks by the edge devices reduces the burden on the network, requiring only 0.2% of the current cloud storage.<\/jats:p>","DOI":"10.3390\/app13127131","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T02:28:56Z","timestamp":1686796136000},"page":"7131","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Using Intelligent Edge Devices for Predictive Maintenance on Injection Molds"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8001-2172","authenticated-orcid":false,"given":"Pedro","family":"Nunes","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal"},{"name":"Centre for Mechanical Technology and Automation, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3628-6795","authenticated-orcid":false,"given":"Eug\u00e9nio","family":"Rocha","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of Aveiro, 3810-193 Aveiro, Portugal"},{"name":"Center for Research and Development in Mathematics and Applications (CIDMA), 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0417-8167","authenticated-orcid":false,"given":"Jos\u00e9 Paulo","family":"Santos","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal"},{"name":"Centre for Mechanical Technology and Automation, 3810-193 Aveiro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,14]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Osswald, T.A., Hern\u00e1ndez-Ortiz, J.P., Hanser Publishers, and Hanser Gardner Publications (2006). 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Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.procir.2017.12.229","article-title":"Monitoring and Control for Thermoplastics Injection Molding A Review","volume":"67","author":"Ogorodnyk","year":"2018","journal-title":"Procedia CIRP"},{"doi-asserted-by":"crossref","unstructured":"Ageyeva, T., Horv\u00e1th, S., and Kov\u00e1cs, J.G. (2019). In-Mold Sensors for Injection Molding: On the Way to Industry 4.0. Sensors, 19.","key":"ref_5","DOI":"10.3390\/s19163551"},{"doi-asserted-by":"crossref","unstructured":"Gomes, T.E.P., Cadete, M.S., Ferreira, J.A.F., Febra, R., Silva, J., Noversa, T., Pontes, A.J., and Neto, V. (2023). Development of an Open-Source Injection Mold Monitoring System. Sensors, 23.","key":"ref_6","DOI":"10.3390\/s23073569"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.cirpj.2022.11.004","article-title":"Challenges in predictive maintenance\u2014A review","volume":"40","author":"Nunes","year":"2023","journal-title":"CIRP J. Manuf. Sci. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1108\/13552511111116259","article-title":"Cost of poor maintenance: A concept for maintenance performance improvement","volume":"17","author":"Salonen","year":"2011","journal-title":"J. Qual. Maint. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"177","DOI":"10.7158\/14488388.2013.11464858","article-title":"Application of Reliability Centred Maintenance Methodology to Develop Maintenance Program for a Heavy Duty Hydraulic Stretching Machine","volume":"9","author":"Deshpande","year":"2013","journal-title":"Aust. J. Multi-Discip. Eng."},{"unstructured":"Moubray, J. (1997). Reliability-Centered Maintenance, Butterworth Heinemann.","key":"ref_10"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/978-3-030-20948-3_13","article-title":"A Fog Computing Approach for Predictive Maintenance","volume":"Volume 349","author":"Cerquitelli","year":"2019","journal-title":"Lecture Notes in Business Information Processing"},{"unstructured":"Bosch Software Innovations GmbH (2018). Edge Computing for IoT, Bosch Software Innovations GmbH.","key":"ref_12"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.1016\/j.procs.2022.12.302","article-title":"Predictive maintenance on injection molds by generalized fault trees and anomaly detection","volume":"217","author":"Nunes","year":"2023","journal-title":"Procedia Comput. Sci."},{"unstructured":"Balena (2022, February 02). OpenBalena. Available online: https:\/\/github.com\/balena-io\/open-balena.","key":"ref_14"},{"unstructured":"Groover, M.P. (2019). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems, Enhanced eText, Wiley. [4th ed.].","key":"ref_15"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"107440","DOI":"10.1016\/j.cie.2021.107440","article-title":"Fuzzy reliability centered maintenance considering personnel experience and only censored data","volume":"158","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1103\/PhysRev.106.620","article-title":"Information Theory and Statistical Mechanics","volume":"106","author":"Jaynes","year":"1957","journal-title":"Phys. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3465","DOI":"10.1007\/s00170-017-1402-y","article-title":"RCM implementation on plastic injection molding machine considering correlated failure modes and small size sample","volume":"95","year":"2018","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ifacol.2019.12.364","article-title":"Is Big Data About to Retire Expert Knowledge? A Predictive Maintenance Study","volume":"52","author":"Rivera","year":"2019","journal-title":"IFAC-PapersOnLine"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1007\/s00170-015-7981-6","article-title":"A predictive maintenance approach based on real-time internal parameter monitoring","volume":"85","author":"Park","year":"2016","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1080\/00224065.1984.11978921","article-title":"The Shewhart Control Chart\u2014Tests for Special Causes","volume":"16","author":"Nelson","year":"1984","journal-title":"J. Qual. Technol."},{"doi-asserted-by":"crossref","unstructured":"Bazargan-Lari, M.R., and Taghipour, S. (2021, January 24\u201327). A Data Mining Approach for Forecasting Machine Related Disruptions. Proceedings of the 2021 Annual Reliability and Maintainability Symposium (RAMS), Orlando, FL, USA.","key":"ref_22","DOI":"10.1109\/RAMS48097.2021.9605729"},{"doi-asserted-by":"crossref","unstructured":"Ghaleb, M., Namoura, H.A., and Taghipour, S. (2021, January 24\u201327). Reinforcement Learning-based Real-time Scheduling under Random Machine Breakdowns and Other Disturbances: A Case Study. Proceedings of the 2021 Annual Reliability and Maintainability Symposium (RAMS), Orlando, FL, USA.","key":"ref_23","DOI":"10.1109\/RAMS48097.2021.9605791"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"107896","DOI":"10.1016\/j.cie.2021.107896","article-title":"A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing","volume":"164","author":"Bregon","year":"2022","journal-title":"Comput. Ind. Eng."},{"doi-asserted-by":"crossref","unstructured":"Moreira, E.E., Alves, F.S., Martins, M., Ribeiro, G., Pina, A., Aguiam, D.E., Sotgiu, E., Fernandes, E.P., and Gaspar, J. (2020, January 8\u201311). Industry 4.0: Real-time monitoring of an injection molding tool for smart predictive maintenance. Proceedings of the 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vienna, Austria.","key":"ref_25","DOI":"10.1109\/ETFA46521.2020.9212167"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"109677","DOI":"10.1016\/j.ymssp.2022.109677","article-title":"Framework for stochastic modelling of long-term non-homogeneous data with non-Gaussian characteristics for machine condition prognosis","volume":"184","author":"Shiri","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.cosrev.2015.03.001","article-title":"Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools","volume":"15","author":"Ruijters","year":"2015","journal-title":"Comput. Sci. Rev."},{"unstructured":"Stamatelatos, M., Caraballo, M.J., Vesely, W., Dugan, J., Fragola, M.J., Minarick, M.J., Railsback, M.J., and Jsc, N. (2002). Fault Tree Handbook with Aerospace Applications, Technical Report.","key":"ref_28"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1016\/j.ress.2008.09.007","article-title":"Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment","volume":"94","author":"Gopika","year":"2009","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.ress.2012.07.009","article-title":"Risk-based design of process systems using discrete-time Bayesian networks","volume":"109","author":"Khakzad","year":"2013","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.ssci.2018.02.001","article-title":"Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks","volume":"105","author":"Kabir","year":"2018","journal-title":"Saf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"5559475","DOI":"10.1155\/2021\/5559475","article-title":"Reliability Analysis of Dynamic Fault Tree Based on Binary Decision Diagrams for Explosive Vehicle","volume":"2021","author":"Jiang","year":"2021","journal-title":"Math. Probl. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"106904","DOI":"10.1016\/j.ress.2020.106904","article-title":"A general framework for dependability modelling coupling discrete-event and time-driven simulation","volume":"199","author":"Chiacchio","year":"2020","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"34","DOI":"10.17531\/ein.2021.1.4","article-title":"A numerical simulation method for a repairable dynamic fault tree","volume":"23","author":"Xu","year":"2021","journal-title":"Eksploatacja i Niezawodnosc"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1109\/TR.2009.2035793","article-title":"Probabilistic algebraic analysis of fault trees with priority dynamic gates and repeated events","volume":"59","author":"Merle","year":"2010","journal-title":"IEEE Trans. Reliab."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"136176","DOI":"10.1109\/ACCESS.2019.2942829","article-title":"A Methodology for the Formal Verification of Dynamic Fault Trees Using HOL Theorem Proving","volume":"7","author":"Elderhalli","year":"2019","journal-title":"IEEE Access"},{"unstructured":"Sullivan, K., Dugan, J., and Coppit, D. (1999, January 15\u201318). The Galileo fault tree analysis tool. Proceedings of the Digest of Papers, Twenty-Ninth Annual International Symposium on Fault-Tolerant Computing (Cat. No.99CB36352), Madison, WI, USA.","key":"ref_37"},{"unstructured":"Boudali, H., Nijmeijer, A.P., and Stoelinga, M.I. (2009, January 22\u201327). DFTSim: A simulation tool for extended dynamic fault trees. Proceedings of the 42nd Annual Simulation Symposium 2009, ANSS 2009, Part of the 2009 Spring Simulation Multiconference, San Diego, CA, USA.","key":"ref_38"},{"unstructured":"Arnold, F., Belinfante, A., Van der Berg, F., Guck, D., and Stoelinga, M. (2013). Computer Safety, Reliability, and Security, Springer.","key":"ref_39"},{"unstructured":"Dehnert, C., Junges, S., Katoen, J.P., and Volk, M. (2022, February 02). The Probabilistic Model Checker Storm (Extended Abstract), Available online: http:\/\/xxx.lanl.gov\/abs\/1610.08713.","key":"ref_40"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1109\/TR.2019.2923893","article-title":"A Hierarchical Approach for Dynamic Fault Trees Solution through Semi-Markov Process","volume":"69","author":"Aslansefat","year":"2020","journal-title":"IEEE Trans. Reliab."},{"unstructured":"Rocha, E.M., Nunes, P., and Santos, J. (2022, January 7\u201310). Reliability Analysis of Sensorized Stamping Presses by Generalized Fault Trees. Proceedings of the International Conference on Industrial Engineering and Operations Management, Istanbul, Turkey.","key":"ref_42"},{"unstructured":"Nunes, P., Rocha, E.M., Neves, J., and Santos, J. (2022). ARTIIS 2022: Advanced Research in Technologies, Information, Innovation and Sustainability, Springer.","key":"ref_43"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s13174-010-0007-6","article-title":"Cloud computing: State-of-the-art and research challenges","volume":"1","author":"Zhang","year":"2010","journal-title":"J. Internet Serv. Appl."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e3926","DOI":"10.1002\/dac.3926","article-title":"Elucidating the challenges for the praxis of fog computing: An aspect-based study","volume":"32","author":"Martin","year":"2019","journal-title":"Int. J. Commun. Syst."},{"doi-asserted-by":"crossref","unstructured":"Resende, C., Folgado, D., Oliveira, J., Franco, B., Moreira, W., Oliveira, A., Cavaleiro, A., and Carvalho, R. (2021). TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance. Sensors, 21.","key":"ref_46","DOI":"10.3390\/s21144676"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"178891","DOI":"10.1109\/ACCESS.2019.2953019","article-title":"Predictive maintenance of induction motors using ultra-low power wireless sensors and compressed recurrent neural networks","volume":"7","author":"Markiewicz","year":"2019","journal-title":"IEEE Access"},{"doi-asserted-by":"crossref","unstructured":"Zhang, W., Dong, M., Ota, K., Li, J., Yang, W., and Wu, J. (2020, January 7\u201311). A Big Data Management Architecture for Standardized IoT Based on Smart Scalable SNMP. Proceedings of the 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland.","key":"ref_48","DOI":"10.1109\/ICC40277.2020.9149368"},{"doi-asserted-by":"crossref","unstructured":"D\u00edaz-de-Arcaya, J., Mi\u00f1on, R., and Torre-Bastida, A.I. (2019, January 9\u201313). Towards an architecture for big data analytics leveraging edge\/fog paradigms. Proceedings of the 13th European Conference on Software Architecture, ECSA 2019, Paris, France.","key":"ref_49","DOI":"10.1145\/3344948.3344987"},{"doi-asserted-by":"crossref","unstructured":"Panicucci, S., Nikolakis, N., Cerquitelli, T., Ventura, F., Proto, S., Macii, E., Makris, S., Bowden, D., Becker, P., and O\u2019mahony, N. (2020). A cloud-to-edge approach to support predictive analytics in robotics industry. Electronics, 9.","key":"ref_50","DOI":"10.3390\/electronics9030492"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"102217","DOI":"10.1016\/j.rcim.2021.102217","article-title":"Service-oriented industrial internet of things gateway for cloud manufacturing","volume":"73","author":"Liu","year":"2022","journal-title":"Robot. Comput.-Integr. Manuf."},{"unstructured":"Ayer, L., and Ayer, P.H.L. (2000). Euromap 63\u2014Data Exchange Interface, EUROMAP. Technical Report.","key":"ref_52"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"5494","DOI":"10.1109\/TII.2021.3110808","article-title":"A Verifiable Privacy-Preserving Machine Learning Prediction Scheme for Edge-Enhanced HCPSs","volume":"18","author":"Li","year":"2022","journal-title":"IEEE Trans. Ind. Inform."},{"doi-asserted-by":"crossref","unstructured":"Liu, F.T., Ting, K.M., and Zhou, Z.H. (2008, January 15\u201319). Isolation forest. Proceedings of the IEEE International Conference on Data Mining, ICDM, Washington, DC, USA.","key":"ref_54","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/s13638-021-01941-3","article-title":"Energy-aware task offloading with deadline constraint in mobile edge computing","volume":"2021","author":"Li","year":"2021","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"unstructured":"(2022, February 02). dcaputo-harmoni. OpenBalena. Available online: https:\/\/github.com\/dcaputo-harmoni\/open-balena-admin.","key":"ref_56"},{"doi-asserted-by":"crossref","unstructured":"Saxena, A., Goebel, K., Simon, D., and Eklund, N. (2008, January 25). Damage propagation modeling for aircraft engine run-to-failure simulation. Proceedings of the 2008 International Conference on Prognostics and Health Management, PHM 2008, Denver, CO, USA.","key":"ref_57","DOI":"10.1109\/PHM.2008.4711414"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"107052","DOI":"10.1016\/j.ress.2020.107052","article-title":"An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets","volume":"202","author":"Lee","year":"2020","journal-title":"Reliab. Eng. Syst. 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