{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T10:42:21Z","timestamp":1779100941509,"version":"3.51.4"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,1,16]],"date-time":"2024-01-16T00:00:00Z","timestamp":1705363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,16]],"date-time":"2024-01-16T00:00:00Z","timestamp":1705363200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"FWO","award":["G0B6922N"],"award-info":[{"award-number":["G0B6922N"]}]},{"DOI":"10.13039\/501100004837","name":"Ministry of Science and Innovation","doi-asserted-by":"crossref","award":["VARIATIVA (PID2021-128695OB-I00)"],"award-info":[{"award-number":["VARIATIVA (PID2021-128695OB-I00)"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1007\/s10115-023-02042-x","type":"journal-article","created":{"date-parts":[[2024,1,16]],"date-time":"2024-01-16T13:02:08Z","timestamp":1705410128000},"page":"2699-2746","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A systematic literature review on the application of process mining to Industry 4.0"],"prefix":"10.1007","volume":"66","author":[{"given":"Katsiaryna","family":"Akhramovich","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Estefan\u00eda","family":"Serral","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos","family":"Cetina","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,16]]},"reference":[{"issue":"4","key":"2042_CR1","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/s12599-014-0334-4","volume":"6","author":"H Lasi","year":"2014","unstructured":"Lasi H, Fettke P, Kemper HG, Feld T, Hoffmann M (2014) Industry 4.0. Bus Inf Syst Eng 6(4):239\u2013242. https:\/\/doi.org\/10.1007\/s12599-014-0334-4","journal-title":"Bus Inf Syst Eng"},{"key":"2042_CR2","doi-asserted-by":"publisher","unstructured":"Mehta P, Rao P, Wu ZD, Jovanovi\u0107 V, Wodo O, Kuttolamadom M (2018) Smart manufacturing: state-of-the-art review in context of conventional and modern manufacturing process modeling, monitoring and control. In: Manufacturing equipment and systems. ASME 2018 13th international manufacturing science and engineering conference, vol. 3, pp. 1\u201321. https:\/\/doi.org\/10.1115\/MSEC2018-6658","DOI":"10.1115\/MSEC2018-6658"},{"key":"2042_CR3","doi-asserted-by":"publisher","unstructured":"Romero D, Bernus P, Noran O, Stahre J, Fast-Berglund \u00c5 (2016) The operator 4.0: human cyber-physical systems adaptive automation towards human-automation symbiosis work systems. In: N\u00e4\u00e4s I et al. (Eds) Advances in production management systems. Initiatives for a sustainable world. APMS 2016. IFIP advances in information and communication technology, vol 488, pp. 677\u2013686. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-51133-7-P_80","DOI":"10.1007\/978-3-319-51133-7-P_80"},{"key":"2042_CR4","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/978-3-319-06755-1_2","volume-title":"Towards the internet of services: the THESEUS Research Program. Cognitive Technologies","author":"S Fischer","year":"2014","unstructured":"Fischer S (2014) Challenges of the internet of services. In: Wahlster W, Grallert HJ, Wess S, Friedrich H, Widenka T (eds) Towards the internet of services: the THESEUS Research Program. Cognitive Technologies. Springer, Cham, Switzerland, pp 15\u201327. https:\/\/doi.org\/10.1007\/978-3-319-06755-1_2"},{"key":"2042_CR5","doi-asserted-by":"publisher","unstructured":"Qin J, Liu Y, Grosvenor R (2016) A categorical framework of manufacturing for industry 4.0 and beyond. In: Procedia CIRP. The sixth international conference on changeable, Agile, Reconfigurable and virtual production (CARV2016), vol. 52, pp. 173\u2013178. https:\/\/doi.org\/10.1016\/j.procir.2016.08.005","DOI":"10.1016\/j.procir.2016.08.005"},{"key":"2042_CR6","doi-asserted-by":"publisher","unstructured":"Hala\u0161ka M, \u015aperka R (2018) Process mining - the enhancement of elements of industry 4.0. In: 2018 4th international conference on computer and information sciences (ICCOINS), pp. 1\u20136. IEEE. https:\/\/doi.org\/10.1109\/ICCOINS.2018.8510578","DOI":"10.1109\/ICCOINS.2018.8510578"},{"issue":"5","key":"2042_CR7","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1016\/J.ENG.2017.05.015","volume":"3","author":"RY Zhong","year":"2017","unstructured":"Zhong RY, Xu X, Klotz E, Newman ST (2017) Intelligent manufacturing in the context of industry 4.0: a review. Engineering 3(5):616\u2013630. https:\/\/doi.org\/10.1016\/J.ENG.2017.05.015","journal-title":"Engineering"},{"key":"2042_CR8","doi-asserted-by":"publisher","unstructured":"Paschek D, Luminosu CT, Draghici A (2017) Automated business process management - in times of digital transformation using machine learning or artificial intelligence. In: 8th international conference on manufacturing science and education \u2013 MSE 2017 Trends in New Industrial Revolution, vol. 121, pp. 04007. https:\/\/doi.org\/10.1051\/matecconf\/201712104007","DOI":"10.1051\/matecconf\/201712104007"},{"key":"2042_CR9","doi-asserted-by":"publisher","unstructured":"van der Aalst WMP (2022) Process mining: a 360 degree overview. In: Lecture notes in business information processing, vol. 448, pp. 3\u201334. https:\/\/doi.org\/10.1007\/978-3-031-08848-3_1","DOI":"10.1007\/978-3-031-08848-3_1"},{"issue":"4","key":"2042_CR10","doi-asserted-by":"publisher","first-page":"18e","DOI":"10.1145\/2685352","volume":"5","author":"W van der Aalst","year":"2015","unstructured":"van der Aalst W, Zhao JL, Wang HJ (2015) Editorial: business process intelligence: connecting data and processes. ACM Trans Manag Inf Syst 5(4):18e. https:\/\/doi.org\/10.1145\/2685352","journal-title":"ACM Trans Manag Inf Syst"},{"key":"2042_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-49851-4","volume-title":"Process mining: data science in action","author":"W van der Aalst","year":"2016","unstructured":"van der Aalst W (2016) Process mining: data science in action, 2nd edn. Springer, Berlin. https:\/\/doi.org\/10.1007\/978-3-662-49851-4","edition":"2"},{"key":"2042_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19345-3","volume-title":"Process mining: discovery, conformance and enhancement of business processes","author":"W van der Aalst","year":"2011","unstructured":"van der Aalst W (2011) Process mining: discovery, conformance and enhancement of business processes. Springer, Berlin. https:\/\/doi.org\/10.1007\/978-3-642-19345-3"},{"issue":"2","key":"2042_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2229156.2229157","volume":"3","author":"W van der Aalst","year":"2012","unstructured":"van der Aalst W (2012) Process mining: overview and opportunities. ACM Trans Manag Inf Syst 3(2):1\u201317. https:\/\/doi.org\/10.1145\/2229156.2229157","journal-title":"ACM Trans Manag Inf Syst"},{"key":"2042_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/S13748-022-00281-7","author":"G Park","year":"2022","unstructured":"Park G, van der Aalst WMP (2022) Action-oriented process mining: bridging the gap between insights and actions. Progress Artif Intell. https:\/\/doi.org\/10.1007\/S13748-022-00281-7","journal-title":"Progress Artif Intell"},{"key":"2042_CR15","doi-asserted-by":"publisher","first-page":"119790","DOI":"10.1016\/j.techfore.2019.119790","volume":"150","author":"G B\u00fcchi","year":"2020","unstructured":"B\u00fcchi G, Cugno M, Castagnoli R (2020) Smart factories performance and Industry 4.0. Technol Forecast Soc Change 150:119790. https:\/\/doi.org\/10.1016\/j.techfore.2019.119790","journal-title":"Technol Forecast Soc Change"},{"issue":"1","key":"2042_CR16","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/s10845-018-1433-8","volume":"31","author":"E Oztemel","year":"2020","unstructured":"Oztemel E, Gursev S (2020) Literature review of Industry 4.0 and related technologies. J Intell Manuf 31(1):127\u2013182. https:\/\/doi.org\/10.1007\/s10845-018-1433-8","journal-title":"J Intell Manuf"},{"key":"2042_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jii.2017.04.005","volume":"6","author":"Y Lu","year":"2017","unstructured":"Lu Y (2017) Industry 4.0: a survey on technologies, applications and open research issues. J Ind Inf Integr 6:1\u201310. https:\/\/doi.org\/10.1016\/j.jii.2017.04.005","journal-title":"J Ind Inf Integr"},{"key":"2042_CR18","doi-asserted-by":"publisher","first-page":"107617","DOI":"10.1016\/j.ijpe.2020.107617","volume":"226","author":"G Culot","year":"2020","unstructured":"Culot G, Nassimbeni G, Orzes G, Sartor M (2020) Behind the definition of Industry 4.0: analysis and open questions. Int J Prod Econ 226:107617. https:\/\/doi.org\/10.1016\/j.ijpe.2020.107617","journal-title":"Int J Prod Econ"},{"issue":"4","key":"2042_CR19","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1080\/21681015.2018.1462863","volume":"35","author":"DC Fettermann","year":"2018","unstructured":"Fettermann DC, Cavalcante CGS, de Almeida TD, Tortorella GL (2018) How does Industry 4.0 contribute to operations management? J Ind Prod Eng 35(4):255\u2013268. https:\/\/doi.org\/10.1080\/21681015.2018.1462863","journal-title":"J Ind Prod Eng"},{"key":"2042_CR20","doi-asserted-by":"publisher","first-page":"127052","DOI":"10.1016\/J.JCLEPRO.2021.127052","volume":"302","author":"M Ghobakhloo","year":"2021","unstructured":"Ghobakhloo M, Fathi M, Iranmanesh M, Maroufkhani P, Morales ME (2021) Industry 4.0 ten years on: a bibliometric and systematic review of concepts, sustainability value drivers, and success determinants. J Clean Prod 302:127052. https:\/\/doi.org\/10.1016\/J.JCLEPRO.2021.127052","journal-title":"J Clean Prod"},{"key":"2042_CR21","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1007\/978-3-319-64218-5_27","volume":"748","author":"A Riel","year":"2017","unstructured":"Riel A, Flatscher M (2017) A design process approach to strategic production planning for industry 4.0. Commun Comput Inf Sci 748:323\u2013333. https:\/\/doi.org\/10.1007\/978-3-319-64218-5_27","journal-title":"Commun Comput Inf Sci"},{"key":"2042_CR22","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2020.1824085","author":"T Zheng","year":"2020","unstructured":"Zheng T, Ardolino M, Bacchetti A, Perona M (2020) The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review. Int J Prod Res. https:\/\/doi.org\/10.1080\/00207543.2020.1824085","journal-title":"Int J Prod Res"},{"issue":"10\u201311","key":"2042_CR23","doi-asserted-by":"publisher","first-page":"1017","DOI":"10.1080\/0951192X.2020.1775295","volume":"33","author":"M Sanchez","year":"2020","unstructured":"Sanchez M, Exposito E, Aguilar J (2020) Industry 4.0: survey from a system integration perspective. Int J Comput Integr Manuf 33(10\u201311):1017\u20131041. https:\/\/doi.org\/10.1080\/0951192X.2020.1775295","journal-title":"Int J Comput Integr Manuf"},{"key":"2042_CR24","doi-asserted-by":"publisher","unstructured":"Fernandes EC, Fitzgerald B, Brown L, Borsato M (2019) Machine learning and process mining applied to process optimization: bibliometric and systemic analysis. In: Procedia manufacturing. 29th international conference on flexible automation and intelligent manufacturing (FAIM 2019), vol. 38, pp. 84\u201391. https:\/\/doi.org\/10.1016\/j.promfg.2020.01.012","DOI":"10.1016\/j.promfg.2020.01.012"},{"key":"2042_CR25","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.eswa.2019.05.003","volume":"133","author":"CDS Garcia","year":"2019","unstructured":"Garcia CDS, Meincheim A, Faria Junior ER, Dallagassa MR, Sato DMV, Carvalho DR, Santos EAP, Scalabrin EE (2019) Process mining techniques and applications\u2014a systematic mapping study. Expert Syst Appl 133:260\u2013295. https:\/\/doi.org\/10.1016\/j.eswa.2019.05.003","journal-title":"Expert Syst Appl"},{"key":"2042_CR26","doi-asserted-by":"publisher","unstructured":"Chaydy N, Madani A (2019) An overview of Process Mining and its applicability to complex, real-life scenarios. In: 2019 international conference on systems of collaboration, big data, internet of things and security (SysCoBIoTS), pp. 1\u20139. IEEE. https:\/\/doi.org\/10.1109\/SysCoBIoTS48768.2019.9028024","DOI":"10.1109\/SysCoBIoTS48768.2019.9028024"},{"issue":"4","key":"2042_CR27","doi-asserted-by":"publisher","first-page":"900","DOI":"10.1108\/BPMJ-06-2017-0148","volume":"24","author":"M Thiede","year":"2017","unstructured":"Thiede M, Fuerstenau D, Barquet APB (2017) How is process mining technology used by organizations? A systematic literature review of empirical studies. Bus Process Manag J 24(4):900\u2013922. https:\/\/doi.org\/10.1108\/BPMJ-06-2017-0148","journal-title":"Bus Process Manag J"},{"key":"2042_CR28","doi-asserted-by":"publisher","unstructured":"Dakic D, Stefanovic D, Cosic I, Lolic T, Medojevic M (2018) Business process mining application: a literature review. In: Katalinic B (Ed.) Proceedings of the 29th international DAAAM symposium, vol. 1, pp. 0866\u20130875. DAAAM International, Vienna. https:\/\/doi.org\/10.2507\/29th.daaam.proceedings.125","DOI":"10.2507\/29th.daaam.proceedings.125"},{"issue":"5","key":"2042_CR29","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1080\/17517575.2017.1402371","volume":"12","author":"ARC Maita","year":"2018","unstructured":"Maita ARC, Martins LC, L\u00f3pez Paz CR, Rafferty L, Hung PCK, Peres SM, Fantinato M (2018) A systematic mapping study of process mining. Enterp Inf Syst 12(5):505\u2013549. https:\/\/doi.org\/10.1080\/17517575.2017.1402371","journal-title":"Enterp Inf Syst"},{"issue":"3","key":"2042_CR30","doi-asserted-by":"publisher","first-page":"e1346","DOI":"10.1002\/widm.1346","volume":"10","author":"K Diba","year":"2020","unstructured":"Diba K, Batoulis K, Weidlich M, Weske M (2020) Extraction, correlation, and abstraction of event data for process mining. WIREs Data Min Knowl Discov 10(3):e1346. https:\/\/doi.org\/10.1002\/widm.1346","journal-title":"WIREs Data Min Knowl Discov"},{"issue":"6","key":"2042_CR31","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1109\/TSC.2017.2772256","volume":"11","author":"AE Marquez-Chamorro","year":"2018","unstructured":"Marquez-Chamorro AE, Resinas M, Ruiz-Cortes A (2018) Predictive monitoring of business processes: a survey. IEEE Trans Serv Comput 11(6):962\u2013977. https:\/\/doi.org\/10.1109\/TSC.2017.2772256","journal-title":"IEEE Trans Serv Comput"},{"issue":"2","key":"2042_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3301300","volume":"13","author":"I Teinemaa","year":"2019","unstructured":"Teinemaa I, Dumas M, La Rosa M, Maggi FM (2019) Outcome-oriented predictive process monitoring: review and benchmark. ACM Trans Knowl Discov Data 13(2):1\u201357. https:\/\/doi.org\/10.1145\/3301300","journal-title":"ACM Trans Knowl Discov Data"},{"key":"2042_CR33","doi-asserted-by":"publisher","unstructured":"Di Francescomarino C, Ghidini C, Maggi FM, Milani F (2018) Predictive process monitoring methods: which one suits me best? In: Weske M, Montali M, Weber I, vomBrocke J (Eds) Business process management. BPM 2018. Lecture notes in computer science, vol. 11080, pp. 462\u2013479. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-98648-7_27","DOI":"10.1007\/978-3-319-98648-7_27"},{"issue":"1","key":"2042_CR34","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.pmcj.2011.01.004","volume":"8","author":"J Ye","year":"2012","unstructured":"Ye J, Dobson S, McKeever S (2012) Situation identification techniques in pervasive computing: a review. Pervasive Mob Comput 8(1):36\u201366. https:\/\/doi.org\/10.1016\/j.pmcj.2011.01.004","journal-title":"Pervasive Mob Comput"},{"key":"2042_CR35","doi-asserted-by":"publisher","unstructured":"Mannhardt F, Bovo R, Oliveira MF, Julier S (2018) A taxonomy for combining activity recognition and process discovery in industrial environments. In: Intelligent data engineering and automated learning \u2013 IDEAL 2018 19th international conference, vol. 11315, pp. 84\u201393. https:\/\/doi.org\/10.1007\/978-3-030-03496-2_10","DOI":"10.1007\/978-3-030-03496-2_10"},{"key":"2042_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.inffus.2018.09.013","volume":"49","author":"D Praveen Kumar","year":"2019","unstructured":"Praveen Kumar D, Amgoth T, Annavarapu CSR (2019) Machine learning algorithms for wireless sensor networks: a survey. Inf Fusion 49:1\u201325. https:\/\/doi.org\/10.1016\/j.inffus.2018.09.013","journal-title":"Inf Fusion"},{"issue":"1","key":"2042_CR37","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1109\/SURV.2013.042313.00197","volume":"16","author":"C Perera","year":"2014","unstructured":"Perera C, Zaslavsky A, Christen P, Georgakopoulos D (2014) Context aware computing for the internet of things: a survey. IEEE Commun Surv Tutor 16(1):414\u2013454. https:\/\/doi.org\/10.1109\/SURV.2013.042313.00197","journal-title":"IEEE Commun Surv Tutor"},{"key":"2042_CR38","doi-asserted-by":"publisher","first-page":"103298","DOI":"10.1016\/j.compind.2020.103298","volume":"123","author":"J Dalzochio","year":"2020","unstructured":"Dalzochio J, Kunst R, Pignaton E, Binotto A, Sanyal S, Favilla J, Barbosa J (2020) Machine learning and reasoning for predictive maintenance in Industry 4.0: current status and challenges. Comput Ind 123:103298. https:\/\/doi.org\/10.1016\/j.compind.2020.103298","journal-title":"Comput Ind"},{"key":"2042_CR39","doi-asserted-by":"publisher","first-page":"8211","DOI":"10.3390\/su12198211","volume":"12","author":"ZM \u00c7inar","year":"2020","unstructured":"\u00c7inar ZM, Nuhu AA, Zeeshan Q, Korhan O, Asmael M, Safaei B (2020) Machine learning in predictive maintenance towards sustainable smart manufacturing in Industry 4.0. Sustainability 12:8211. https:\/\/doi.org\/10.3390\/su12198211","journal-title":"Sustainability"},{"key":"2042_CR40","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.neucom.2017.01.078","volume":"239","author":"S Ram\u00edrez-Gallego","year":"2017","unstructured":"Ram\u00edrez-Gallego S, Krawczyk B, Garc\u00eda S, Wo\u017aniak M, Herrera F (2017) A survey on data preprocessing for data stream mining: current status and future directions. Neurocomputing 239:39\u201357. https:\/\/doi.org\/10.1016\/j.neucom.2017.01.078","journal-title":"Neurocomputing"},{"key":"2042_CR41","doi-asserted-by":"publisher","first-page":"2130","DOI":"10.1016\/J.PROCS.2019.09.386","volume":"159","author":"CC Osman","year":"2019","unstructured":"Osman CC, Ghiran AM (2019) When Industry 4.0 meets process mining. Proced Comput Sci 159:2130\u20132136. https:\/\/doi.org\/10.1016\/J.PROCS.2019.09.386","journal-title":"Proced Comput Sci"},{"key":"2042_CR42","unstructured":"Kitchenham BA, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report EBSE-2007-01. Accesssed from http:\/\/citeseerx.ist.psu.edu\/viewdoc\/summary?doi=10.1.1.117.471"},{"key":"2042_CR43","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1007\/BF03177550","volume":"1","author":"HM Cooper","year":"1988","unstructured":"Cooper HM (1988) Organizing knowledge syntheses: a taxonomy of literature reviews. Knowl Soc 1:104\u2013126. https:\/\/doi.org\/10.1007\/BF03177550","journal-title":"Knowl Soc"},{"key":"2042_CR44","doi-asserted-by":"publisher","unstructured":"Wohlin C (2014) Guidelines for snowballing in systematic literature studies and a replication in software engineering. In: Proceedings of the 18th international conference on evaluation and assessment in software engineering (EASE), pp. 1\u201310. https:\/\/doi.org\/10.1145\/2601248.2601268","DOI":"10.1145\/2601248.2601268"},{"key":"2042_CR45","doi-asserted-by":"publisher","unstructured":"Bertrand Y, Van den Abbeele B, Veneruso S, Leotta F, Mecella M, Serral E (2023) A survey on the application of process mining to smart spaces data. In: Montali M, Senderovich A, Weidlich M (eds) ICPM 2022:Process mining workshops. Lecture notes in business information processing, vol 468, pp. 57\u201370. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-031-27815-0_5","DOI":"10.1007\/978-3-031-27815-0_5"},{"issue":"5","key":"2042_CR46","doi-asserted-by":"publisher","first-page":"1342","DOI":"10.1177\/0954405417736547","volume":"233","author":"S Mittal","year":"2017","unstructured":"Mittal S, Khan MA, Romero D, Wuest T (2017) Smart manufacturing: characteristics, technologies and enabling factors. Smart Manuf Dig Fact 233(5):1342\u20131361. https:\/\/doi.org\/10.1177\/0954405417736547","journal-title":"Smart Manuf Dig Fact"},{"issue":"3","key":"2042_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/designs4030017","volume":"4","author":"J Butt","year":"2020","unstructured":"Butt J (2020) A conceptual framework to support digital transformation in manufacturing using an integrated business process management approach. Designs 4(3):1\u201339. https:\/\/doi.org\/10.3390\/designs4030017","journal-title":"Designs"},{"issue":"8","key":"2042_CR48","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1080\/09537287.2018.1424960","volume":"29","author":"H Fatorachian","year":"2018","unstructured":"Fatorachian H, Kazemi H (2018) A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework. Prod Plan Control 29(8):633\u2013644. https:\/\/doi.org\/10.1080\/09537287.2018.1424960","journal-title":"Prod Plan Control"},{"issue":"2","key":"2042_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/DESIGNS4020011","volume":"4","author":"J Butt","year":"2020","unstructured":"Butt J (2020) A strategic roadmap for the manufacturing industry to implement Industry 4.0. Designs 4(2):1\u201331. https:\/\/doi.org\/10.3390\/DESIGNS4020011","journal-title":"Designs"},{"key":"2042_CR50","doi-asserted-by":"publisher","unstructured":"Guo Q, Wen L, Wang J, Yan Z, Yu PS (2015) Mining invisible tasks in non-free-choice constructs. In: Motahari-Nezhad H, Recker J, Weidlich M (eds) BPM 2016: business process management. Lecture notes in computer science, vol 9253, pp. 109\u2013125. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-23063-4_7","DOI":"10.1007\/978-3-319-23063-4_7"},{"key":"2042_CR51","doi-asserted-by":"publisher","unstructured":"Leemans SJJ, Fahland D, van der Aalst W (2014) Discovering block-structured process models from incomplete event logs. In: Ciardo G, Kindler E (eds) PETRI NETS 2014: application and theory of petri nets and concurrency. Lecture notes in computer science, vol. 8489, pp. 91\u2013110. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-07734-5_6","DOI":"10.1007\/978-3-319-07734-5_6"},{"key":"2042_CR52","doi-asserted-by":"publisher","unstructured":"Leemans SJJ, Fahland D, van der Aalst W (2016) Using life cycle information in process discovery. In: Reichert M, Reijers H (eds) BPM 2016: business process management workshops. Lecture notes in business information processing, vol. 256, pp. 204\u2013217. Springer, Charm. https:\/\/doi.org\/10.1007\/978-3-319-42887-1_17","DOI":"10.1007\/978-3-319-42887-1_17"},{"key":"2042_CR53","doi-asserted-by":"publisher","unstructured":"Stertz F, Rinderle-Ma S (2018) Process histories - detecting and representing concept drifts based on event streams. In: Panetto H, Debruyne C, Proper H, Ardagna C, Roman D, Meersman R (eds) On the move to meaningful internet systems. OTM 2018 conferences. OTM 2018. Lecture notes in computer science, vol. 11229, pp. 318\u2013335. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-02610-3_18","DOI":"10.1007\/978-3-030-02610-3_18"},{"key":"2042_CR54","doi-asserted-by":"publisher","unstructured":"Leemans SJJ, Fahland D, van der Aalst W (2015) Exploring processes and deviations. In: Fournier F, Mendling J (eds) BPM 2014: business process management workshops. Lecture notes in business information processing, vol. 202, pp. 304\u2013316. https:\/\/doi.org\/10.1007\/978-3-319-15895-2_26","DOI":"10.1007\/978-3-319-15895-2_26"},{"key":"2042_CR55","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.datak.2018.04.007","volume":"117","author":"A Augusto","year":"2018","unstructured":"Augusto A, Conforti R, Dumas M, La Rosa M, Bruno G (2018) Automated discovery of structured process models from event logs: the discover-and-structure approach. Data Knowl Eng 117:373\u2013392. https:\/\/doi.org\/10.1016\/j.datak.2018.04.007","journal-title":"Data Knowl Eng"},{"key":"2042_CR56","doi-asserted-by":"publisher","unstructured":"Augusto A, Conforti R, Dumas M, La Rosa M (2017) Split miner: discovering accurate and simple business process models from event logs. In: 2017 IEEE international conference on data mining (ICDM), pp. 1\u201310. IEEE. https:\/\/doi.org\/10.1109\/ICDM.2017.9","DOI":"10.1109\/ICDM.2017.9"},{"key":"2042_CR57","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.dss.2017.04.005","volume":"100","author":"SKLM van den Broucke","year":"2017","unstructured":"van den Broucke SKLM, de Weerdt J (2017) Fodina: a robust and flexible heuristic process discovery technique. Decis Support Syst 100:109\u2013118. https:\/\/doi.org\/10.1016\/j.dss.2017.04.005","journal-title":"Decis Support Syst"},{"key":"2042_CR58","doi-asserted-by":"publisher","first-page":"106860","DOI":"10.1016\/j.comnet.2019.106860","volume":"162","author":"MM Golchi","year":"2019","unstructured":"Golchi MM, Saraeian S, Heydari M (2019) A hybrid of firefly and improved particle swarm optimization algorithms for load balancing in cloud environments: performance evaluation. Comput Netw 162:106860. https:\/\/doi.org\/10.1016\/j.comnet.2019.106860","journal-title":"Comput Netw"},{"issue":"1","key":"2042_CR59","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/s10270-008-0106-z","volume":"9","author":"W van der Aalst","year":"2010","unstructured":"van der Aalst W, Rubin V, Verbeek HMW, Van Dongen BF, Kindler E, G\u00fcnther CW (2010) Process mining: a two-step approach to balance between underfitting and overfitting. Softw Syst Model 9(1):87\u2013111. https:\/\/doi.org\/10.1007\/s10270-008-0106-z","journal-title":"Softw Syst Model"},{"key":"2042_CR60","doi-asserted-by":"publisher","unstructured":"Viale P, Benayadi N, Le Goc M, Pinaton J (2010) Modeling large scale manufacturing process from timed data: Using the TOM4L approach and sequence alignment information for modeling STMicroelectronics\u2019 production processes. In: ICEIS 2010 - proceedings of the 12th international conference on enterprise information systems, 2 AIDSS, pp. 129\u2013138. https:\/\/doi.org\/10.5220\/0002971801290138","DOI":"10.5220\/0002971801290138"},{"key":"2042_CR61","doi-asserted-by":"publisher","unstructured":"de Leoni M, van der Aalst W (2013) Data-aware process mining: discovering decisions in processes using alignments. In: SAC '13: proceedings of the 28th annual ACM symposium on applied computing, pp. 1454\u20131461. https:\/\/doi.org\/10.1145\/2480362.2480633","DOI":"10.1145\/2480362.2480633"},{"key":"2042_CR62","doi-asserted-by":"publisher","unstructured":"JagadeeshChandraBose RP, van der Aalst WMP (2009) Abstractions in process mining: a taxonomy of patterns. In: Dayal U, Eder J, Koehler J, Reijers HA (eds) BPM 2009: business process management. Lecture notes in computer science, vol 5701, pp. 159\u2013175. Springer, Berlin. https:\/\/doi.org\/10.1007\/978-3-642-03848-8_12","DOI":"10.1007\/978-3-642-03848-8_12"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-023-02042-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-023-02042-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-023-02042-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:10:59Z","timestamp":1714522259000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-023-02042-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,16]]},"references-count":62,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["2042"],"URL":"https:\/\/doi.org\/10.1007\/s10115-023-02042-x","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,16]]},"assertion":[{"value":"26 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 November 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 December 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}