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Blockchain-based business process management (BPM) framework for service composition in industry 4.0

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A Correction to this article was published on 19 October 2018

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Abstract

Business process management (BPM) aims to optimize business processes to achieve better system performance such as higher profit, quicker response, and better services. BPM systems in Industry 4.0 are required to digitize and automate business process workflows and support the transparent interoperations of service vendors. The critical bottleneck to advance BPM systems is the evaluation, verification, and transformation of trustworthiness and digitized assets. Most of BPM systems rely heavily on domain experts or third parties to deal with trustworthiness. In this paper, an automated BPM solution is investigated to select and compose services in open business environment, Blockchain technology (BCT) is explored and proposed to transfer and verify the trustiness of businesses and partners, and a BPM framework is developed to illustrate how BCT can be integrated to support prompt, reliable, and cost-effective evaluation and transferring of Quality of Services in the workflow composition and management.

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Change history

  • 19 October 2018

    Unfortunately, the corresponding author name is misspelled as Wattana Viryasitavat in the original article. The correct name is Wattana Viriyasitavat.

References

  • Ali, A. S., Ludwig, S. A., & Rana, O. F. (2005). A cognitive trust-based approach for web service discovery and selection. In Third European conference on web services (ECOWS’05). https://doi.org/10.1109/ECOWS.2005.2.

  • Altunay, M., Brown, D., Byrd, G., & Dean, R. (2005). Trust-based secure workflow path construction. In Proceedings of international conference on service oriented computing.

  • Ardagna, D., & Pernici, B. (2005). Global and local QoS guarantee in web service selection. In Business process management workshops.

  • Ardakani, M. R. M., Hashemi, S. M., & Razzazi, M. (2018). A cloud-based solution/reference architecture for establishing collaborative networked organizations. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-017-1387-2.

  • Barbon, F., Traverso, P., Pistore, M., & Trainotti, M. (2006). Run-time monitoring of instances and classes of web-service compositions. In Proceedings of ICWS 2006. https://doi.org/10.1109/ICWS.2006.113.

  • Camarinha-Matos, L. M., & Pantoja-Lima, C. (2001). Cooperation coordination in virtual enterprises. Journal of Intelligent Manufacturing, 12(2), 133–150.

    Article  Google Scholar 

  • Chhun, S., Moalla, N., & Ouzrout, Y. (2016). QoS ontology for service selection and reuse. Journal of Intelligent Manufacturing, 27(1), 187–199.

    Article  Google Scholar 

  • Coutinho, C., Cretan, A., da Silva, C. F., Ghodous, P., & Jardim-Goncalves, R. (2016). Service-based negotiation for advanced collaboration in enterprise networks. Journal of Intelligent Manufacturing, 27(1), 201–216.

    Article  Google Scholar 

  • Dan, A., Davis, D., Kearney, R., Keller, A., King, R. P., Kuebler, D., et al. (2004). Web services on demand: WSLA-driven automated management. IBM Systems Journal, 43(1), 136–158.

    Article  Google Scholar 

  • Danila, C., Stegaru, G., Stanescu, A. M., & Serbanescu, C. (2016). Web-service based architecture to support SCM context-awareness and interoperability. Journal of Intelligent Manufacturing, 27(1), 73–82.

    Article  Google Scholar 

  • Dustdar, S., & Schreiner, W. (2005). A survey on web services composition. International Journal of Web and Grid Services, 1(1), 1–30. https://doi.org/10.1504/IJWGS.2005.007545.

    Article  Google Scholar 

  • Faizod (2006). Blockchain, industry 4.0 and the internet of things. Faizod. https://faizod.com/blockchain-industrie-4-0-und-das-internet-der-dinge/. Accessed 5 Feb 2018.

  • Fehling, C., Koetter, F., & Leymann, F. (2014). Compliance modeling-formal descriptors and tools. Report. University of Stuttgart. http://www.iaas.uni-stuttgart.de/institut/ehemalige/fehling/TR-2014-Compliance-Modeling.pdf. Accessed 5 Feb 2018.

  • Franz, P., & Kirchmer, M. (2012). Value-driven business process management: The value-switch for lasting competitive advantage. New York: McGraw Hill Professional.

    Google Scholar 

  • García-Bañuelos, L., Ponomarev, A., Dumas, M., & Weber, I. (2017). Optimized execution of business processes on blockchain. In J. Carmona, G. Engels, & A. Kumar (Eds.), Business process management. BPM 2017. Lecture notes in computer science (Vol. 10445). Cham: Springer.

    Google Scholar 

  • Gibelin, N., & Makpangou, M. (2005). Efficient and transparent web-services selection. In B. Benatallah, F. Casati, & P. Traverso (Eds.), ICSOC 2005 (pp. 145–156). LNCS. 3826 (pp. 527–532). Heidelberg: Springer.

    Google Scholar 

  • Halle, S., Villemaire, R., Cherkaoui, O., & Ghandour, B. (2007). Model checking data-aware workflow properties with CTL-FO+. In Enterprise distributed object computing conference, 2007. EDOC 2007. 11th IEEE International (pp. 267–267). Annapolis, MD.

  • Han, L., Xing, K., Chen, X., & Xiong, F. (2018). A Petri net-based particle swarm optimization approach for scheduling deadlock-prone flexible manufacturing systems. Journal of Intelligent Manufacturing, 29(5), 1083–1096.

    Article  Google Scholar 

  • Haq, I., Alnemr, R., Paschke, A., Schikuta, E., Boley, H., & Meinel, C. (2010). Distributed trust management for validating SLA choreographies. In P. Wieder, R. Yahyapour, & W. Ziegler (Eds.), Grids and service-oriented architectures for service level agreements. Boston, MA: Springer.

    Google Scholar 

  • Hollingsworth, D. (1994). Workflow management coalition: The workflow reference model. WFMC document WFMCTC00-1003.

  • Hsieh, F. S., & Lin, J. B. (2014). Context-aware workflow management for virtual enterprises based on coordination of agents. Journal of Intelligent Manufacturing, 25(3), 393–412.

    Article  Google Scholar 

  • Huang, L., Walker, D. W., Huang, Y., & Rana, O. F. (2005). Dynamic Web Service Selection for Workflow Optimisation. In Proceedings of 4th UK e-science Programme All Hands Meeting (AHM).

  • Hwang, S.-Y., Lim, E.-P., Lee, C.-H., & Chen, C.-H. (2008). Dynamic web service selection for reliable web service composition. IEEE Transactions on Service Computing, 1(2), 104–116. https://doi.org/10.1109/TSC.2008.2.

    Article  Google Scholar 

  • IBM (2018), Watson IoT and Blockchain: Disruptor and game changer. https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=WW912350USEN. Accessed 5 Feb 2018.

  • Jurca, R., Faltings, B., & Binder, W. (2007). Reliable QoS monitoring based on client feedback. In Proceedings of the 16th international conference on World Wide Web (WWW ’07) (pp. 1003–1012). ACM, New York, NY, USA. https://doi.org/10.1145/1242572.1242708.

  • Kshetri, N. (2017). Can Blockchain strengthen the internet of things? IT Professional, 19(4), 68–72. https://doi.org/10.1109/MITP.2017.3051335.

    Article  Google Scholar 

  • Lee, M., Yoon, H., Shin, H., & Lee, D. G. (2009). Intelligent dynamic workflow support for a ubiquitous web service-based manufacturing environment. Journal of Intelligent Manufacturing, 20(3), 295–302.

    Article  Google Scholar 

  • Li, F., Shaung, K., & Su, S. (2007). Q-Peer: A decentralized qos registry architecture for web services. In Service-oriented computing-ICSOC 2007. Springer, Berlin, Heidelberg.

  • Liu, Y., Ngu, A. H., & Zeng, L. Z. (2004). QoS computation and policing in dynamic web service selection. In Proceedings of the 13th international conference on World Wide Web (pp. 66–73). ACM Press, New York.

  • Liu, B., Yu, X. L., Chen, S., Xu, X., & Zhu, L. (2017). Blockchain based data integrity service framework for IoT data. 2017 IEEE International Conference on Web Services (ICWS)(pp. 468–475). Honolulu, HI. https://doi.org/10.1109/ICWS.2017.54.

  • Lu, Y. (2017b). Cyber physical system (CPS)-based industry 4.0: A survey. Journal of Industrial Integration and Management, 2(3), 1–57.

  • Lu, Y. (2017a). A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1–10.

    Article  Google Scholar 

  • Ludwig, H., Dan, A., & Kearney. R., (2004) Cremona: An architecture and library for creation and monitoring of WS-Agreements. In ICSOC ’04. Proceedings of the 2nd international conference on Service oriented computing (pp. 65–74). ACM Press, New York, NY, USA.

  • Lu, Y., Wang, H., & Xu, X. (2016). ManuService ontology: A product data model for service-oriented business interactions in a cloud manufacturing environment. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-016-1250-x.

  • Mahdavi, I., Mohebbi, S., Zandakbari, M., Cho, N., & M ahdavi-Amiri, N. (2009). Agent-based web service for the design of a dynamic coordination mechanism in supply networks. Journal of Intelligent Manufacturing, 20(6), 727–749.

    Article  Google Scholar 

  • Maximilien, E. M., & Singh, M. P. (2004). A framework and ontology for dynamic web services selection. IEEE Internet Computing, 8(5), 84–93.

    Article  Google Scholar 

  • Mohammad, A., & Thomas, R. (2009). Combining global optimization with local selection for efficient QoS-aware service composition. In Proceedings of the 18th international conference on World Wide Web (WWW ’09) (pp. 881–890). ACM, New York, NY, USA. https://doi.org/10.1145/1526709.1526828.

  • Nakamoto, S., (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org.

  • Puttonen, J., Lobov, A., Soto, M. A. C., & Lastra, J. L. M. (2016). Cloud computing as a facilitator for web service composition in factory automation. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-016-1277-z.

  • Ran, S. (2003). A model for web services discovery with QoS. SIGecom Exchanges, 4(1), 1–10. https://doi.org/10.1145/844357.844360.

    Article  Google Scholar 

  • Rao, J., & Su, X., (2005). A survey of automated web service composition methods. In Semantic web services and web process composition (pp. 43–54). Springer, Berlin.

  • Sahai, A., Machiraju, V., Sayal, M., van Moorsel, A. P. A., & Casati, F. (2002). Automated SLA monitoring for web services. In DSOM. Lecture Notes in Computer Science, 2506 (pp. 28-41). Springer, Berlin.

  • Seok, H., & Nof, S. Y. (2018). Intelligent information sharing among manufacturers in supply networks: Supplier selection case. Journal of Intelligent Manufacturing, 29(5), 1097–1113.

    Article  Google Scholar 

  • Serhani, M. A., Dssouli, R., & Hafid, A., et al. (2005). A QoS broker based architecture for efficient web services selection. In: ICWS 2005. Proceedings of IEEE international conference on web services (pp. 113–120). IEEE Computer Society Press, Los Alamitos.

  • van der Aalst, W. M. P. (2005). Pi calculus versus petri nets: Let us eat “humble pie” rather than further inflate the “pi hype”. BPTrends, 3(5), 1–11.

    Google Scholar 

  • Viriyasitavat, W. (2009). Modeling delegation in requirements-driven trust framework. In 2009 Congress on services-I (pp. 522–529). Los Angeles, CA.

  • Viriyasitavat, W. (2013). A framework of trust in service workflows. Ph.D. dissertation. Department of Computer Science, University of Oxford, Oxford, UK.

  • Viriyasitavat, W., & Martin, A. (2010). Formal trust specification in service workflows. In IEEE/IFIP 8th international conference on embedded and ubiquitous computing (EUC) (pp. 703–710).

  • Viriyasitavat, W., & Martin, A. (2012). An improvement of requirement-based compliance checking algorithm in service workflows. In Proceedings of international conference on advances in information technology (AIT) (pp. 41–45). UACEE, Bangkok, Thailand.

  • Viriyasitavat, W. (2016). Multi-criteria selection for services selection in service workflow. Journal of Industrial Information Integration, 1, 20–25.

    Article  Google Scholar 

  • Viriyasitavat, W., & Martin, A. (2011b). In the relation of workflow and trust characteristics, and requirements in service workflows. Communications in Computer Information Science, 251, 492–506.

    Article  Google Scholar 

  • Viriyasitavat, W., & Martin, A. (2011a). Formalizing trust requirements and specification in service workflow environment. In R. Zhang, J. Cordeiro, X. Li, Z. Zhang, & J. Zhang (Eds.), ICEIS (Vol. 3, pp. 196–206). Setúbal: SciTePress.

    Google Scholar 

  • Viriyasitavat, W., & Martin, A. (2017). The reviews and analysis of the state-of-the-art service workflow specification languages. Journal of Industrial Information Integration., 8, 1–7.

    Article  Google Scholar 

  • Viriyasitavat, W., Xu, L., & Martin, A. (2012). SWSpec: The requirement specification language in service workflow environments. IEEE Transactions on Industrial Informatics, 8(3), 631–638.

    Article  Google Scholar 

  • Viriyasitavat, W., Xu, L. D., & Viriyasitavat, W. (2014a). Compliance checking for requirement-oriented service workflow interoperations. IEEE Transactions on Industrial Informatics, 10(2), 1469–1477.

    Article  Google Scholar 

  • Viriyasitavat, W., Xu, L. D., & Viriyasitavat, W. (2014b). A new approach for compliance checking in service workflows. IEEE Transactions on Industrial Informatics, 10(2), 1452–1460.

    Article  Google Scholar 

  • Viriyasitayat, W., Xu, L. D., & Bi, Z. M. (2018a). The extension of semantic formalization of service workflow specification language. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/TII.2018.2807400.

  • Viriyasitayat, W., Xu, L. D., Bi, Z. M., & Sapsomboon, A. (2018b). Extension of specification language for soundness and completeness of service workflow. Enterprise Information System. https://doi.org/10.1080/17517575.2018.1432769.

  • Watanabe, K., Mikoshiba, S., Tateyama, T., & Shimomura, Y. (2012). Service process simulation for integrated service evaluation. Journal of Intelligent Manufacturing, 23(4), 1379–1388.

    Article  Google Scholar 

  • Workflow management coalition (1999). Workflow management coalition specification: Terminology & glossary. WFMC document WFMC-TC-1011.

  • Xie, Y., Chen, S., Ni, Q., & Wu, H. (2017). Integration of resource allocation and task assignment for optimizing the cost and maximum throughput of business processes. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-017-1329-z.

  • Xu, L. D., & Duan, L. (2018). Big data for cyber physical systems in industry 4.0: A survey. Enterprise Information Systems. https://doi.org/10.1080/17517575.2018.1442934.

  • Xu, L. D., Xu, E. L., & Li, L. (2017). Industry 4.0: State of the art and future trends. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1444806.

  • Xu, L. D., Viriyasitavat, W., Ruchikachorn, P., & Martin, A. (2012). Using propositional logic for requirements verification of service workflow. IEEE Transactions on Industrial Informatics., 8(3), 639–646.

    Article  Google Scholar 

  • Yu, T., & Lin, K. J. (2005). A broker-based framework for QoS-aware web service composition. In EEE-2005. Proceeding of IEEE international conference on e-Technology, e-Commerce and e-Service, Hong Kong, China. IEEE Computer Society Press, Los Alamitos.

  • Zeng, L., Benatallah, B., Lei, H., Ngu, A., Flaxer, D., & Chang, H. (2010). Flexible composition of enterprise web services. Electronic Markets, 12(2), 141–152.

    Article  Google Scholar 

  • Zeng, L., Benatallah, B., Ngu, A. H. H., Dumas, M., Kalagnanam, J., & Chang, H. (2004). QoS-aware middleware for web services composition. IEEE Transactions on Software Engineering, 30(5), 311–327.

    Article  Google Scholar 

  • Zhang, Y., Zhang, G., Liu, Y., & Hu, D. (2017). Research on services encapsulation and virtualization access model of machine for cloud manufacturing. Journal of Intelligent Manufacturing, 28(5), 1109–1123.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Statistics, Faculty of Commerce and Accountancy, Chulalongkorn University, Bangkok, Thailand

    Wattana Viriyasitavat & Assadaporn Sapsomboon

  2. Department of Information Technology & Decision Sciences, Old Dominion University, Norfolk, VA, 23529, USA

    Li Da Xu

  3. Department of Civil and Mechanical Engineering, Purdue University Fort Wayne, Fort Wayne, IN, 46805, USA

    Zhuming Bi

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  1. Wattana Viriyasitavat
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  2. Li Da Xu
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  3. Zhuming Bi
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  4. Assadaporn Sapsomboon
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Correspondence to Wattana Viriyasitavat.

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The original version of this article was revised: The spell error in the author name has now been corrected.

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Viriyasitavat, W., Da Xu, L., Bi, Z. et al. Blockchain-based business process management (BPM) framework for service composition in industry 4.0. J Intell Manuf 31, 1737–1748 (2020). https://doi.org/10.1007/s10845-018-1422-y

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