{"page":"527-536","doi":"10.36001/phme.2021.v6i1.3042","issue":"1","publication_status":"published","editor":[{"first_name":"Phuc","full_name":"Do, Phuc","last_name":"Do"},{"last_name":"King","full_name":"King, Steve","first_name":"Steve"},{"first_name":"Olga","full_name":"Fink, Olga","last_name":"Fink"}],"date_created":"2021-11-03T12:26:39Z","keyword":["PHME 2021","Feature Selection Classification","Feature Selection Clustering","Interpretable Model","Transparent Model","Industry 4.0","Real-World Diagnostics","Quality Control","Predictive Maintenance"],"quality_controlled":"1","abstract":[{"lang":"eng","text":"In the industry 4.0 era, there is a growing need to transform unstructured data acquired by a multitude of sources into information and subsequently into knowledge to improve the quality of manufactured products, to boost production, for predictive maintenance, etc. Data-driven approaches, such as machine learning techniques, are typically employed to model the underlying relationship from data. However, an increase in model accuracy with state-of-the-art methods, such as deep convolutional neural networks, results in less interpretability and transparency. Due to the ease of implementation, interpretation and transparency to both domain experts and non-experts, a rule-based method is proposed in this paper, for prognostics and health management (PHM) and specifically for diagnostics. The proposed method utilizes the most relevant sensor signals acquired via feature extraction and selection techniques and expert knowledge. As a case study, the presented method is evaluated on data from a real-world quality control set-up provided by the European prognostics and health management society (PHME) at the conference’s 2021 data challenge. With the proposed method, our team took the third place, capable of successfully diagnosing different fault modes, irrespective of varying conditions."}],"oa":"1","conference":{"name":"PHM Society European Conference"},"publication":"Proceedings of the European Conference of the PHM Society 2021","date_updated":"2023-09-22T09:13:01Z","type":"conference","language":[{"iso":"eng"}],"main_file_link":[{"url":"http://papers.phmsociety.org/index.php/phme/article/download/3042/1812","open_access":"1"}],"citation":{"bibtex":"@inproceedings{Aimiyekagbon_Muth_Wohlleben_Bender_Sextro_2021, title={Rule-based Diagnostics of a Production Line}, volume={6}, DOI={<a href=\"https://doi.org/10.36001/phme.2021.v6i1.3042\">10.36001/phme.2021.v6i1.3042</a>}, number={1}, booktitle={Proceedings of the European Conference of the PHM Society 2021}, author={Aimiyekagbon, Osarenren Kennedy and Muth, Lars and Wohlleben, Meike Claudia and Bender, Amelie and Sextro, Walter}, editor={Do, Phuc and King, Steve and Fink, Olga}, year={2021}, pages={527–536} }","chicago":"Aimiyekagbon, Osarenren Kennedy, Lars Muth, Meike Claudia Wohlleben, Amelie Bender, and Walter Sextro. “Rule-Based Diagnostics of a Production Line.” In <i>Proceedings of the European Conference of the PHM Society 2021</i>, edited by Phuc Do, Steve King, and Olga Fink, 6:527–36, 2021. <a href=\"https://doi.org/10.36001/phme.2021.v6i1.3042\">https://doi.org/10.36001/phme.2021.v6i1.3042</a>.","short":"O.K. Aimiyekagbon, L. Muth, M.C. Wohlleben, A. Bender, W. Sextro, in: P. Do, S. King, O. Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021, 2021, pp. 527–536.","mla":"Aimiyekagbon, Osarenren Kennedy, et al. “Rule-Based Diagnostics of a Production Line.” <i>Proceedings of the European Conference of the PHM Society 2021</i>, edited by Phuc Do et al., vol. 6, no. 1, 2021, pp. 527–36, doi:<a href=\"https://doi.org/10.36001/phme.2021.v6i1.3042\">10.36001/phme.2021.v6i1.3042</a>.","ama":"Aimiyekagbon OK, Muth L, Wohlleben MC, Bender A, Sextro W. Rule-based Diagnostics of a Production Line. In: Do P, King S, Fink O, eds. <i>Proceedings of the European Conference of the PHM Society 2021</i>. Vol 6. ; 2021:527-536. doi:<a href=\"https://doi.org/10.36001/phme.2021.v6i1.3042\">10.36001/phme.2021.v6i1.3042</a>","ieee":"O. K. Aimiyekagbon, L. Muth, M. C. Wohlleben, A. Bender, and W. Sextro, “Rule-based Diagnostics of a Production Line,” in <i>Proceedings of the European Conference of the PHM Society 2021</i>, 2021, vol. 6, no. 1, pp. 527–536, doi: <a href=\"https://doi.org/10.36001/phme.2021.v6i1.3042\">10.36001/phme.2021.v6i1.3042</a>.","apa":"Aimiyekagbon, O. K., Muth, L., Wohlleben, M. C., Bender, A., &#38; Sextro, W. (2021). Rule-based Diagnostics of a Production Line. In P. Do, S. King, &#38; O. Fink (Eds.), <i>Proceedings of the European Conference of the PHM Society 2021</i> (Vol. 6, Issue 1, pp. 527–536). <a href=\"https://doi.org/10.36001/phme.2021.v6i1.3042\">https://doi.org/10.36001/phme.2021.v6i1.3042</a>"},"user_id":"9557","department":[{"_id":"151"}],"_id":"27111","title":"Rule-based Diagnostics of a Production Line","volume":6,"author":[{"last_name":"Aimiyekagbon","id":"9557","full_name":"Aimiyekagbon, Osarenren Kennedy","first_name":"Osarenren Kennedy"},{"first_name":"Lars","orcid":"0000-0002-2938-5616","last_name":"Muth","id":"77313","full_name":"Muth, Lars"},{"full_name":"Wohlleben, Meike Claudia","last_name":"Wohlleben","id":"43991","orcid":"0009-0009-9767-7168","first_name":"Meike Claudia"},{"first_name":"Amelie","full_name":"Bender, Amelie","id":"54290","last_name":"Bender"},{"first_name":"Walter","full_name":"Sextro, Walter","id":"21220","last_name":"Sextro"}],"intvolume":"         6","status":"public","year":"2021"}