Otwarty dostęp

Performance of an automated process model discovery – the logistics process of a manufacturing company


Zacytuj

van der Aalst, W. M. P. (2005). Business Alignment: Using Process Mining As a Tool for Delta Analysis and Conformance Testing. Requirements Engineering 10(3), 198-211. doi: 10.1007/s00766-005-0001-xvan der AalstW. M. P.2005Business Alignment: Using Process Mining As a Tool for Delta Analysis and Conformance TestingRequirements Engineering10319821110.1007/s00766-005-0001-xOpen DOISearch in Google Scholar

van der Aalst, W. M. P. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Processes. Berlin Heidelberg, Germany: Springer-Verlag.van der AalstW. M. P.2011Process Mining: Discovery, Conformance and Enhancement of Business ProcessesBerlin Heidelberg, GermanySpringer-Verlag10.1007/978-3-642-19345-3Search in Google Scholar

van der Aalst, W. M. P. (2015). Extracting Event Data from Databases to Unleash Process Mining. In J. vom Brocke & T. Schmiedel (Eds.), BPM - Driving Innovation in a Digital World (pp. 105-128). Switzerland: Springer Cham (Management for Professionals).van der AalstW. M. P.2015Extracting Event Data from Databases to Unleash Process Miningvom BrockeJ.&SchmiedelT.BPM - Driving Innovation in a Digital World105128SwitzerlandSpringer Cham (Management for Professionals)Search in Google Scholar

van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action 2nd edn. Berlin Heidelberg, Germany: Springer-Verlag.van der AalstW. M. P.2016Process Mining: Data Science in Action2nd ednBerlin Heidelberg, GermanySpringer-Verlag10.1007/978-3-662-49851-4Search in Google Scholar

van der et al. Aalst, W. M. P. (2011). Process Mining Manifesto. In F. Daniel, K. Barkaoui, & S. Dustdar (Eds.), Business Process Management Workshops. International Conference on Business Process Management (pp. 169-194). Berlin, Heidelberg, Germany: Springervan der et al. AalstW. M. P.2011Process Mining ManifestoDanielF.BarkaouiK.&DustdarS.Business Process Management Workshops. International Conference on Business Process Management169194Berlin, Heidelberg, GermanySpringerSearch in Google Scholar

van der Aalst, W. M. P., Rubin, V., Verbeek, H. M. V., van Dongen, B. F., Kindler, E., & Günther, C. W. (2010). Process mining: a two-step approach to balance between underfitting and overfitting. Software & Systems Modeling 9(1), 87-111. doi: 10.1007/s10270-008-0106-zvan der AalstW. M. P.RubinV.VerbeekH. M. V.van DongenB. F.KindlerE.&GüntherC. W.2010Process mining: a two-step approach to balance between underfitting and overfittingSoftware & Systems Modeling918711110.1007/s10270-008-0106-zOpen DOISearch in Google Scholar

van der Aalst, W. M. P., Weijters, T., & Maruster, L. (2004). Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128-1142. doi: 10.1109/TKDE.2004.47van der AalstW. M. P.WeijtersT.&MarusterL.2004Workflow mining: discovering process models from event logsIEEE Transactions on Knowledge and Data Engineering1691128114210.1109/TKDE.2004.47Open DOISearch in Google Scholar

van der Aalst, W. M. P., Weijters, T., & Maruster, L. (2004). Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128-1142. doi: 10.1109/TKDE.2004.47van der AalstW. M. P.WeijtersT.&MarusterL.2004Workflow mining: discovering process models from event logsIEEE Transactions on Knowledge and Data Engineering1691128114210.1109/TKDE.2004.47Open DOISearch in Google Scholar

Abar, S., Theodoropoulos, G. K., Lemarinier P., & O’Hare, G. M. P. (2017). Agent Based Modelling and Simulation tools: A review of the state-of-art software. Computer Science Review 24, 13-33. doi: 10.1016/j. cosrev.2017.03.001AbarS.TheodoropoulosG. K.LemarinierP.&O’HareG. M. P.2017Agent Based Modelling and Simulation tools: A review of the state-of-art softwareComputer Science Review24133310.1016/j.cosrev.2017.03.001Open DOISearch in Google Scholar

Agrawal, R., Gunopulos, D., & Leymann, F. (1998). Mining Process Models from Workflow Logs. In H. Schek, F. Saltor, I. Ramos, & G. Alonso (Eds.), Proceedings of the 6th International Conference on Extending Database Technology (EDBT’98), Lecture Notes in Computer Science, vol. 1377 (pp. 469-483), Berlin, Germany: Springer.AgrawalR.GunopulosD.&LeymannF.1998Mining Process Models from Workflow LogsSchekH.SaltorF.RamosI.&AlonsoG.Proceedings of the 6th International Conference on Extending Database Technology (EDBT’98), Lecture Notes in Computer Science, vol. 1377469483Berlin, GermanySpringerSearch in Google Scholar

AnyLogic (2019). Simulation modelling software tool. Retrieved from https://www.anylogic.comAnyLogic2019Simulation modelling software toolRetrieved fromhttps://www.anylogic.comSearch in Google Scholar

Augusto, A. Conforti, R., Dumas, M., La Rosa, M., Maggi, F. M., Marrella, A., Mecella, M., & Soo, A. (2017). Automated Discovery of Process Models from Event Logs: Review and Benchmark Retrieved from http://arxiv.org/abs/1705.02288AugustoA. Conforti, R.DumasM.La RosaM.MaggiF. M.MarrellaA.MecellaM.&SooA.2017Automated Discovery of Process Models from Event Logs: Review and BenchmarkRetrieved fromhttp://arxiv.org/abs/1705.02288Search in Google Scholar

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. 1-10), New Orleans, United States: IEEE.AugustoA.ConfortiR.DumasM.&La RosaM.2017Split Miner: Discovering Accurate and Simple Business Process Models from Event Logs2017 IEEE International Conference on Data Mining (ICDM)110New Orleans, United StatesIEEESearch in Google Scholar

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 & Knowledge Engineering 117, 373-392. doi: 10.1016/j.datak.2018.04.007AugustoA.ConfortiR.DumasM.La RosaM.&BrunoG.2018Automated discovery of structured process models from event logs: The discover-and-structure approachData & Knowledge Engineering11737339210.1016/j.datak.2018.04.007Open DOISearch in Google Scholar

Augusto, A., et al. (2019). Measuring Fitness and Precision of Automatically Discovered Process Models: A Principled and Scalable Approach Retrieved from https://minerva-access.unimelb.edu.au/bitstream/handle/11343/219723/main.pdfAugustoA.et al2019Measuring Fitness and Precision of Automatically Discovered Process Models: A Principled and Scalable ApproachRetrieved fromhttps://minerva-access.unimelb.edu.au/bitstream/handle/11343/219723/main.pdfSearch in Google Scholar

Bannat, A., et al. (2011). Artificial Cognition in Production Systems. IEEE Transactions on Automation Science and Engineering 8(1), 148-174. doi: 10.1109/TASE.2010.2053534BannatA.et al2011Artificial Cognition in Production SystemsIEEE Transactions on Automation Science and Engineering8114817410.1109/TASE.2010.2053534Open DOISearch in Google Scholar

BIMP (2019). Business Process Simulator. Retrieved from http://bimp.cs.ut.eeBIMP2019Business Process SimulatorRetrieved fromhttp://bimp.cs.ut.eeSearch in Google Scholar

Boes, J., & Migeon, F. (2017). Self-organizing multi-agent systems for the control of complex systems. Journal of Systems and Software 134, 12-28. doi: 10.1016/j. jss.2017.08.038BoesJ.&MigeonF.2017Self-organizing multi-agent systems for the control of complex systemsJournal of Systems and Software134122810.1016/j.jss.2017.08.038Open DOISearch in Google Scholar

Borshchev, A., & Filippov, A. (2004). From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools Retrieved from https://www.researchgate.net/publication/233820565_From_System_Dynamics_and_Discrete_Event_to_Practical_Agent_Based_Modeling_Reasons_Techniques_ToolsBorshchevA.&FilippovA.2004From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, ToolsRetrieved fromhttps://www.researchgate.net/publication/233820565_From_System_Dynamics_and_Discrete_Event_to_Practical_Agent_Based_Modeling_Reasons_Techniques_ToolsSearch in Google Scholar

van den Broucke, S. K. L. M., & De Weerdt, J. (2017). Fodina: A robust and flexible heuristic process discovery technique. Decision Support Systems 100, 109-118. doi: 10.1016/j.dss.2017.04.005van den BrouckeS. K. L. M.&De WeerdtJ.2017Fodina: A robust and flexible heuristic process discovery techniqueDecision Support Systems10010911810.1016/j.dss.2017.04.005Open DOISearch in Google Scholar

Buijs, J. C. A. M., van Dongen, B. F., & van der Aalst, W. M. P. (2012). On the Role of Fitness, Precision, Generalization and Simplicity in Process Discovery. In Meersman, et al. (Eds.), On the Move to Meaningful Internet Systems: OTM 2012. OTM Confederated International Conferences (pp. 305-322). Berlin, Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-33606-5_19BuijsJ. C. A. M.van DongenB. F.&van der AalstW. M. P.2012On the Role of Fitness, Precision, Generalization and Simplicity in Process DiscoveryMeersmanet al. EdsOn the Move to Meaningful Internet Systems: OTM 2012. OTM Confederated International Conferences305322Berlin, Heidelberg, GermanySpringer10.1007/978-3-642-33606-5_19Open DOISearch in Google Scholar

Buijs, J. C. A. M., Dongen, B. F. van, & Aalst, W. M. P. van der (2012). A genetic algorithm for discovering process trees. In 2012 IEEE Congress on Evolutionary Computation (pp. 1-8). Brisbane, Australia: IEEE. doi: 10.1109/CEC.2012.6256458BuijsJ. C. A. M.DongenB. F. van&AalstW. M. P. van der2012A genetic algorithm for discovering process trees2012 IEEE Congress on Evolutionary Computation18Brisbane, AustraliaIEEE10.1109/CEC.2012.6256458Open DOISearch in Google Scholar

Buijs, J. C. a. M., van Dongen, B. F., & van der Aalst, W. M. P. (2014) Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and Simplicity. International Journal of Cooperative Information Systems 23(01), 1440001. doi: 10.1142/S0218843014400012BuijsJ. C. A. M.van DongenB. F.&van der AalstW. M. P.2014Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and SimplicityInternational Journal of Cooperative Information Systems2301144000110.1142/S0218843014400012Open DOISearch in Google Scholar

Buijs, J. C. A. M., van Dongen, B. F., & van der Aalst, W. M. P. (2014). Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and Simplicity. International Journal of Cooperative Information Systems 23(1), p. 1440001. doi: 10.1142/S0218843014400012BuijsJ. C. A. M.van DongenB. F.&van der AalstW. M. P.2014Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and SimplicityInternational Journal of Cooperative Information Systems231144000110.1142/S0218843014400012Open DOISearch in Google Scholar

Chan, W. K. V., Son, Y. J., & Macal, C. M. (2010). Agent-based simulation tutorial - simulation of emergent behavior and differences between agent-based simulation and discrete-event simulation. In Proceedings of the 2010 Winter Simulation Conference (pp. 135-150). Baltimore, United States: IEEE. doi: 10.1109/WSC.2010.5679168ChanW. K. V.SonY. J.&MacalC. M.2010Agent-based simulation tutorial - simulation of emergent behavior and differences between agent-based simulation and discrete-event simulationProceedings of the 2010 Winter Simulation Conference135150Baltimore, United StatesIEEE10.1109/WSC.2010.5679168Open DOISearch in Google Scholar

Claes, D., Oliehoek, F., Baier, H., & Tuyls, K. (2017). Decentralised Online Planning for Multi-Robot Warehouse Commissioning. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems (AAMAS ’17) (pp. 492-500). Richalnd, United States: SC.ClaesD.OliehoekF.BaierH.&TuylsK.2017Decentralised Online Planning for Multi-Robot Warehouse CommissioningProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems (AAMAS ’17)492500Richalnd, United StatesSCSearch in Google Scholar

Cook, J. E., & Wolf, E. L. (1998). Discovering Models of Software Processes from Event-Based Data. ACM Transactions on Software Engineering and Methodology 7, 215-249.CookJ. E.&WolfE. L.1998Discovering Models of Software Processes from Event-Based DataACM Transactions on Software Engineering and Methodology721524910.1145/287000.287001Search in Google Scholar

De Weerdt, J., De Backer, M., Vanthienen, J., & Baesens, B. (2012). A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs. Information Systems 37(7), 654-676. doi: 10.1016/j.is.2012.02.004De WeerdtJ.De BackerM.VanthienenJ.&BaesensB.2012A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logsInformation Systems37765467610.1016/j.is.2012.02.004Open DOISearch in Google Scholar

Dinardo, G., Fabbiano, L., & Vacca, G. (2018). A smart and intuitive machine condition monitoring in the Industry 4.0 scenario. Measurement 126, 1-12. doi: 10.1016/j.measurement.2018.05.041DinardoG.FabbianoL.&VaccaG.2018A smart and intuitive machine condition monitoring in the Industry 4.0 scenarioMeasurement12611210.1016/j.measurement.2018.05.041Open DOISearch in Google Scholar

van Dongen, B. F., & van der Aalst, W. M. P. (2004). Multiphase Process Mining: Building Instance Graphs. In P. Atzeni, et al. (Eds.). Conceptual Modeling –ER 2004. International Conference on Conceptual Modeling (pp. 362-376). Berlin Heidelberg, Germany: Springer. doi: 10.1007/978-3-540-30464-7_29van DongenB. F.&van der AalstW. M. P.2004Multiphase Process Mining: Building Instance GraphsAtzeniP.et al. (Eds.)Conceptual Modeling –ER 2004. International Conference on Conceptual Modeling362376Berlin Heidelberg, GermanySpringer10.1007/978-3-540-30464-7_29Open DOISearch in Google Scholar

Doomun, R., & Vunka Jungum, N. (2008). Business process modelling, simulation and reengineering: call centres. Business Process Management Journal 14(6), 838-848.DoomunR.&Vunka JungumN.2008Business process modelling, simulation and reengineering: call centresBusiness Process Management Journal14683884810.1108/14637150810916017Search in Google Scholar

Goedertier, S., Martens, D., Vanthiene, J., Baesens, B. (2009). Robust Process Discovery with Artificial Negative Events. Journal of Machine Learning Research 10, 1305-1340.GoedertierS.MartensD.VanthieneJ.BaesensB.2009Robust Process Discovery with Artificial Negative EventsJournal of Machine Learning Research1013051340Search in Google Scholar

Gries, M., Kulkarni, C., Sauer, C., & Keutzer, K. (2003). Comparing analytical modeling with simulation for network processors: a case study. In Automation and Test in Europe Conference and Exhibition 2003 Design (pp. 256-261). Munich, Germany: IEEE. doi: 10.1109/DATE.2003.1253838GriesM.KulkarniC.SauerC.&KeutzerK.2003Comparing analytical modeling with simulation for network processors: a case studyAutomation and Test in Europe Conference and Exhibition 2003 Design256261Munich, GermanyIEEE10.1109/DATE.2003.1253838Open DOISearch in Google Scholar

Günther, C. W., & van der Aalst, W. M. P. (2007). Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics. In G. Alonso, P. Dadam, & M. Rosemann, (Eds.), Business Process Management (pp. 328-343). Berlin Heidelberg, Germany: Springer.GüntherC. W.&van der AalstW. M. P.2007Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective MetricsAlonsoG.DadamP.&RosemannM.Business Process Management328343Berlin Heidelberg, GermanySpringer10.1007/978-3-540-75183-0_24Search in Google Scholar

Guo, Q., Wen, L., Wang, Z., & Yu, P. S. (2015). Mining Invisible Tasks in Non-free-choice Constructs. In H. R. Motahari-Nezhad, J. Recker, & M. Weidlich, (Eds.). Business Process Management (pp. 109-125). Cham, Germany: Springer International Publishing.GuoQ.WenL.WangZ.&YuP. S.2015Mining Invisible Tasks in Non-free-choice ConstructsR. Motahari-NezhadH.ReckerJ.&WeidlichM.Business Process Management109125Cham, GermanySpringer International Publishing10.1007/978-3-319-23063-4_7Search in Google Scholar

Hlupić, V., & Vukšić, V. B. (2004). Business Process Modelling Using SIMUL8. Retrieved from https://www.researchgate.net/publication/254419366_BUSINESS_PROCESS_MODELLING_USING_SIMUL8HlupićV.&VukšićV. B.2004Business Process Modelling Using SIMUL8Retrieved fromhttps://www.researchgate.net/publication/254419366_BUSINESS_PROCESS_MODELLING_USING_SIMUL8Search in Google Scholar

Hsieh, F.-S. (2015). Scheduling Sustainable Supply Chains based on Multi-agent Systems and Workflow Models. In 2015 10th International Conference on Intelligent Systems and Knowledge Engineering (pp. 252-259). New York, United States: IEEE.HsiehF.-S.2015Scheduling Sustainable Supply Chains based on Multi-agent Systems and Workflow Models2015 10th International Conference on Intelligent Systems and Knowledge Engineering252259New York, United StatesIEEESearch in Google Scholar

Kelly, R. A., et al. (2013). Selecting among five common modelling approaches for integrated environmental assessment and management. Environmental Modelling & Software 47, 159-181. doi: 10.1016/j.envsoft.2013.05.005KellyR. A.et al2013Selecting among five common modelling approaches for integrated environmental assessment and managementEnvironmental Modelling & Software4715918110.1016/j.envsoft.2013.05.005Open DOISearch in Google Scholar

Kolberg, D., & Zühlke, D. (2015). Lean Automation enabled by Industry 4.0 Technologies. IFAC-PapersOnLine 48(3), 1870-1875. doi: 10.1016/j.ifacol.2015.06.359KolbergD.&ZühlkeD.2015Lean Automation enabled by Industry 4.0 TechnologiesIFAC-PapersOnLine4831870187510.1016/j.ifacol.2015.06.359Open DOISearch in Google Scholar

Kozma, T. (2017). Cooperation in the supply chain network. Forum Scientiae Oeconomia 5(3), 45-58.KozmaT.2017Cooperation in the supply chain networkForum Scientiae Oeconomia534558Search in Google Scholar

Leemans, S. J. J., Fahland, D., & van der Aalst, W. M. P. (2013a). Discovering Block-Structured Process Models from Event Logs - A Constructive Approach. In J.-M. Colom, & J. Desel, (Eds.), Application and Theory of Petri Nets and Concurrency. International Conference on Applications and Theory of Petri Nets and Concurrency (pp. 311-329). Berlin Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-38697-8_17LeemansS. J. J.FahlandD.&van der AalstW. M. P.2013aDiscovering Block-Structured Process Models from Event Logs - A Constructive ApproachColomJ.-M.&DeselJ.Application and Theory of Petri Nets and Concurrency. International Conference on Applications and Theory of Petri Nets and Concurrency311329Berlin Heidelberg, GermanySpringer10.1007/978-3-642-38697-8_17Open DOISearch in Google Scholar

Leemans, S. J. J., Fahland, D., & van der Aalst, W. M. P. (2013b). Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour. In N. Lohmann, M. Song, & P., Wohed (Eds.), Business Process Management Workshops. International Conference on Business Process Management (pp. 66-78). Berlin, Germany: Springer International Publishing. doi: 10.1007/978-3-319-06257-0_6LeemansS. J. J.FahlandD.&van der AalstW. M. P.2013bDiscovering Block-Structured Process Models from Event Logs Containing Infrequent BehaviourLohmannN.SongM.&WohedP.Business Process Management Workshops. International Conference on Business Process Management6678Berlin, GermanySpringer International Publishing10.1007/978-3-319-06257-0_6Open DOISearch in Google Scholar

Leemans, S. J. J., Fahland, D., & van der Aalst, W. M. P. (2014). Discovering Block-Structured Process Models from Incomplete Event Logs. In G. Ciardo, & E. Kindler (Eds.), Application and Theory of Petri Nets and Concurrency. International Conference on Applications and Theory of Petri Nets and Concurrency (pp. 91-110). Berlin, Germany: Springer International Publishing. doi: 10.1007/978-3-319-07734-5_6LeemansS. J. J.FahlandD.&van der AalstW. M. P.2014Discovering Block-Structured Process Models from Incomplete Event LogsCiardoG.&KindlerE.Application and Theory of Petri Nets and Concurrency. International Conference on Applications and Theory of Petri Nets and Concurrency91110Berlin, GermanySpringer International Publishing10.1007/978-3-319-07734-5_6Open DOISearch in Google Scholar

Leemans, S. J. J., Fahland, D., & van der Aalst, W. M. P. (2015). Scalable Process Discovery with Guarantees. In K. Gaaloul, et al. (Eds.), Enterprise, Business-Process and Information Systems Modeling. International Conference on Enterprise (pp. 85-101). Berlin, Germany: Springer International Publishing. doi: 10.1007/978-3-319-19237-6_6LeemansS. J. J.FahlandD.&van der AalstW. M. P.2015Scalable Process Discovery with GuaranteesGaaloulK.et al. EdsEnterprise, Business-Process and Information Systems Modeling. International Conference on Enterprise85101Berlin, GermanySpringer International Publishing10.1007/978-3-319-19237-6_6Open DOISearch in Google Scholar

Leemans, S. J. J., Fahland, D., & van der Aalst, W. M. P. (2018). Scalable process discovery and conformance checking. Software & Systems Modeling 17(2), 599-631. doi: 10.1007/s10270-016-0545-xLeemansS. J. J.FahlandD.&van der AalstW. M. P.2018Scalable process discovery and conformance checkingSoftware & Systems Modeling17259963110.1007/s10270-016-0545-xOpen DOISearch in Google Scholar

Leitão, P., et al. (2016). Smart Agents in Industrial Cyber– Physical Systems. Proceedings of the IEEE 104(5), 1086-1101. doi: 10.1109/JPROC.2016.2521931LeitãoP.et al2016Smart Agents in Industrial Cyber– Physical SystemsProceedings of the IEEE10451086110110.1109/JPROC.2016.2521931Open DOISearch in Google Scholar

Macal, C. M. (2010). To Agent-based Simulation from System Dynamics. In Proceedings of the Winter Simulation Conference (pp. 371-382). Baltimore, Maryland: WSC.MacalC. M.2010To Agent-based Simulation from System DynamicsProceedings of the Winter Simulation Conference371382Baltimore, MarylandWSCSearch in Google Scholar

Macal, C. M., & North, M. J. (2008). Agent-based Modeling and Simulation: ABMS Examples. In Proceedings of the 40th Conference on Winter Simulation (pp. 101-112). Miami, Florida, United States: WSC.MacalC. M.&NorthM. J.2008Agent-based Modeling and Simulation: ABMS ExamplesProceedings of the 40th Conference on Winter Simulation101112Miami, Florida, United StatesWSCSearch in Google Scholar

de Medeiros, A. K. A., van Dongen, B. F., van der Aalst, W. M. P., & Weijters, A. J. M. M. (2005). Process Mining: Extending the α-algorithm to Mine Short Loops Retrieved from https://pdfs.semanticscholar.org/dd4b/bc6f1550fc6601b21bd83f5c5ff3b13a309d.pdfde MedeirosA. K. A.van DongenB. F.van der AalstW. M. P.&WeijtersA. J. M. M.2005Process Mining: Extending the α-algorithm to Mine Short LoopsRetrieved fromhttps://pdfs.semanticscholar.org/dd4b/bc6f1550fc6601b21bd83f5c5ff3b13a309d.pdfSearch in Google Scholar

de Medeiros, A. K. A., Weijters, A. J. M. M., & van der Aalst, W. M. P. (2007). Genetic process mining: an experimental evaluation. Data Mining and Knowledge Discovery 14(2), 245-304. doi: 10.1007/s10618-006-0061-7de MedeirosA. K. A.WeijtersA. J. M. M.&van der AalstW. M. P.2007Genetic process mining: an experimental evaluationData Mining and Knowledge Discovery14224530410.1007/s10618-006-0061-7Open DOISearch in Google Scholar

Nguyen, H., et al. (2016). Business Process Deviance Mining: Review and Evaluation Retrieved from http://arxiv.org/abs/1608.08252NguyenH.et al2016Business Process Deviance Mining: Review and EvaluationRetrieved fromhttp://arxiv.org/abs/1608.08252Search in Google Scholar

Pan, M., et al. (2015). Applying Industry 4.0 to the Jurong Island Eco-industrial Park. Energy Procedia 75, 1536-1541. doi: 10.1016/j.egypro.2015.07.313PanM.et al2015Applying Industry 4.0 to the Jurong Island Eco-industrial ParkEnergy Procedia751536154110.1016/j.egypro.2015.07.313Open DOISearch in Google Scholar

Piccarozzi, M., Aquilani, B., & Gatti, C. (2018). Industry 4.0 in Management Studies: A Systematic Literature Review. Sustainability 10(10), 3821. doi: 10.3390/su10103821PiccarozziM.AquilaniB.&GattiC.2018Industry 4.0 in Management Studies: A Systematic Literature ReviewSustainability1010382110.3390/su10103821Open DOISearch in Google Scholar

Pisching, M. A., et al. (2018). An architecture based on RAMI 4.0 to discover equipment to process operations required by products. Computers & Industrial Engineering 125, 574-591. doi: 10.1016/j.cie.2017.12.029PischingM. A.et al2018An architecture based on RAMI 4.0 to discover equipment to process operations required by productsComputers & Industrial Engineering12557459110.1016/j.cie.2017.12.029Open DOISearch in Google Scholar

Pomarlan, M., & Bateman, J. (2018). Robot Program Construction via Grounded Natural Language Semantics & Simulation. In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (pp. 857-864). Richland, United States: International Foundation for Autonomous Agents and Multiagent Systems (AAMAS ’18).PomarlanM.&BatemanJ.2018Robot Program Construction via Grounded Natural Language Semantics & SimulationProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems857864Richland, United StatesInternational Foundation for Autonomous Agents and Multiagent Systems (AAMAS ’18)Search in Google Scholar

Qin, J., Liu, Y., & Grosvenor, R. (2016). A Categorical Framework of Manufacturing for Industry 4.0 and Beyond. Procedia CIRP 52, 173-178. doi: 10.1016/j.procir.2016.08.005QinJ.LiuY.&GrosvenorR.2016A Categorical Framework of Manufacturing for Industry 4.0 and BeyondProcedia CIRP5217317810.1016/j.procir.2016.08.005Open DOISearch in Google Scholar

Roblek, V., Meško, M., & Krapež, A. (2016). A Complex View of Industry 4.0. SAGE Open 6(2), 1-11. doi: 10.1177/2158244016653987RoblekV.MeškoM.&KrapežA.2016A Complex View of Industry 4.0SAGE Open6211110.1177/2158244016653987Open DOISearch in Google Scholar

Rodič, B. (2017). Industry 4.0 and the New Simulation Modelling Paradigm. Organizacija 50(3), 193-207. doi: 10.1515/orga-2017-0017RodičB.2017Industry 4.0 and the New Simulation Modelling ParadigmOrganizacija50319320710.1515/orga-2017-0017Open DOISearch in Google Scholar

Savaglio, C., et al. (2018). Agent-Based Computing in the Internet of Things: A Survey. In M. Ivanović, et al. (Eds.), Intelligent Distributed Computing XI (pp. 307-320), Cham, Germany: Springer International Publishing. doi: 10.1007/978-3-319-66379-1_27SavaglioC.et al2018Agent-Based Computing in the Internet of Things: A SurveyIvanovićM.et al. EdsIntelligent Distributed Computing XI307320Cham, GermanySpringer International Publishing10.1007/978-3-319-66379-1_27Open DOISearch in Google Scholar

Siebers, P. O., et al. (2010). Discrete-event simulation is dead, long live agent-based simulation!. Journal of Simulation 4(3), 204-210. doi: 10.1057/jos.2010.14SiebersP. O.et al2010Discrete-event simulation is dead, long live agent-based simulation!Journal of Simulation4320421010.1057/jos.2010.14Open DOISearch in Google Scholar

Ślusarczyk, B. (2018). Industry 4.0 : are we ready?, Polish Journal of Management Studies 17(1), 232-248. doi: 10.17512/pjms.2018.17.1.19ŚlusarczykB.2018Industry 4.0 : are we ready?Polish Journal of Management Studies17123224810.17512/pjms.2018.17.1.19Open DOISearch in Google Scholar

Sony, M. (2018). Industry 4.0 and lean management: a proposed integration model and research propositions. Production & Manufacturing Research 6(1), 416-432. doi: 10.1080/21693277.2018.1540949SonyM.2018Industry 4.0 and lean management: a proposed integration model and research propositionsProduction & Manufacturing Research6141643210.1080/21693277.2018.1540949Open DOISearch in Google Scholar

Tiwari, A., Turner, C. J., & Majeed, B. (2008). A review of business process mining: State-of-the-art and future trends. ResearchGate 14(1), 5-22. doi: 10.1108/14637150810849373TiwariA.TurnerC. J.&MajeedB.2008A review of business process mining: State-of-the-art and future trendsResearchGate14152210.1108/14637150810849373Open DOISearch in Google Scholar

Verbeek, H. M. W., & van der Aalst, W. M. P. (2015). Decomposed Process Mining: The ILP Case. In F. Fournier, & J. Mendling, (Eds.), Business Process Management Workshops (pp. 264-276). Berlin: Springer International Publishing.VerbeekH. M. W.&van der AalstW. M. P.2015Decomposed Process Mining: The ILP CaseFournierF.&MendlingJ.Business Process Management Workshops264276BerlinSpringer International Publishing10.1007/978-3-319-15895-2_23Search in Google Scholar

Verbeek, H. M. W., van der Aalst, W. M. P., & Munoz-Gama, J. (2017). Divide and Conquer: A Tool Framework for Supporting Decomposed Discovery in Process Mining. The Computer Journal 60(11), 1649-1674. doi: 10.1093/comjnl/bxx040VerbeekH. M. W.van der AalstW. M. P.&Munoz-GamaJ.2017Divide and Conquer: A Tool Framework for Supporting Decomposed Discovery in Process MiningThe Computer Journal60111649167410.1093/comjnl/bxx040Open DOISearch in Google Scholar

Wan, J., et al. (2018). Toward Dynamic Resources Management for IoT-Based Manufacturing. IEEE Communications Magazine 56(2), 52-59. doi: 10.1109/MCOM.2018.1700629WanJ.et al2018Toward Dynamic Resources Management for IoT-Based ManufacturingIEEE Communications Magazine562525910.1109/MCOM.2018.1700629Open DOISearch in Google Scholar

Wang, S., et al. (2016). Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks 101, 158-168 10WangS.et al2016Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordinationComputer Networks10115816810Open DOISearch in Google Scholar

Weijters, A. J. M. M., & Ribeiro, J. T. S. (2011). Flexible Heuristics Miner (FHM). In 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) (pp. 310-317). Paris, France: IEEE. doi: 10.1109/CIDM.2011.5949453WeijtersA. J. M. M.&RibeiroJ. T. S.2011Flexible Heuristics Miner (FHM)2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)310317Paris, FranceIEEE10.1109/CIDM.2011.5949453Open DOISearch in Google Scholar

Weijters, A. J. M. M., van der Aalst, W.M.P., & Medeiros, A. K. A. D. (2006). Process Mining with the Heuristics-Miner Algorithm. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118.8288&rep=rep1&type=pdfWeijtersA. J. M. M.van der AalstW.M.P.&MedeirosA. K. A. D.2006Process Mining with the Heuristics-Miner AlgorithmRetrieved fromhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.118.8288&rep=rep1&type=pdfSearch in Google Scholar

Wen, L., et al. (2007). Mining process models with non-free-choice constructs. Data Mining and Knowledge Discovery 15(2), 145-180. doi: 10.1007/s10618-007-0065-yWenL.et al2007Mining process models with non-free-choice constructsData Mining and Knowledge Discovery15214518010.1007/s10618-007-0065-yOpen DOISearch in Google Scholar

Wen, L., Wang, J., & Sun, J. (2006). Detecting Implicit Dependencies Between Tasks from Event Logs. In Frontiers of WWW Research and Development - AP-Web 2006. Asia-Pacific Web Conference (pp. 591-603), Berlin, Heidelberg, Germany: Springer. doi: 10.1007/11610113_52WenL.WangJ.&SunJ.2006Detecting Implicit Dependencies Between Tasks from Event LogsFrontiers of WWW Research and Development - AP-Web 2006. Asia-Pacific Web Conference591603Berlin, Heidelberg, GermanySpringer10.1007/11610113_52Open DOISearch in Google Scholar

van der Werf, J. M. E. M., van Dongen, B. F., Hurkens, C.J., & Serebrenik, A. (2009). Process Discovery using Integer Linear Programming. Fundamenta Informaticae, 94(3-4), 387-412. doi: 10.3233/FI-2009-136van der WerfJ. M. E. M.van DongenB. F.HurkensC.J.&SerebrenikA.2009Process Discovery using Integer Linear ProgrammingFundamenta Informaticae943-438741210.3233/FI-2009-136Open DOISearch in Google Scholar

van Zelst, S. J., et al. (2018). Discovering workflow nets using integer linear programming. Computing 100(5), 529–556. doi: 10.1007/s00607-017-0582-5van ZelstS. J.et al2018Discovering workflow nets using integer linear programmingComputing100552955610.1007/s00607-017-0582-5Open DOISearch in Google Scholar