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A method to select a successful interoperability solution through a simulation approach

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Abstract

Enterprise applications and software systems need to be interoperable in order to achieve seamless business across organizational boundaries and thus realize virtual networked organizations. Our proposition can be considered as an interoperability project selection approach and is based on three steps: (1) Modelling both collaborative business processes and potential related interoperability projects; (2) Evaluating the accessibility of each project regarding the current state of the organization; (3) Simulating each project and assessing the associated performance. These results are finally projected on a comparison matrix used as a decision support to select the most appropriate interoperability solution. An application case extracted from the French aerospace sector demonstrates the applicability and the benefits of the proposition.

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References

  • Akyuz, G. A., & Erkan, T. E. (2010). Supply chain performance measurement: A literature review. International Journal of Production Research, 48(17), 5137–5155.

    Article  Google Scholar 

  • Alfaro, J. J., Rodriguez-Rodriguez, R., Verdecho, M. J., & Ortiz, A. (2009). Business process interoperability and collaborative performance measurement. International Journal of Computer Integrated Manufacturing, 22(9), 877–889.

    Article  Google Scholar 

  • Archer, N. P., & Ghasemzadeh, F. (1999). An integrated framework for project portfolio selection. International Journal of Project Management, 17(4), 207–216.

    Article  Google Scholar 

  • Ameri, F., & Patil, L. (2010). Digital manufacturing market: A semantic web-based framework for agile supply chain deployment. Journal of Intelligent Manufacturing, 23, 1817–1832.

    Article  Google Scholar 

  • Badri, M. A., Davis, D., & Davis, D. (2001). A comprehensive 0–1 goal programming model for project selection. International Journal of Project Management, 19, 243–252.

    Article  Google Scholar 

  • Baccarini, D. (1996). The concept of project complexity—a review. International Journal of Project Management, 14(4), 201–204.

    Article  Google Scholar 

  • Beamon, B. M. (1999). Measuring supply chain performance. International Journal of Operations and Production Management, 19(3), 275–292.

    Article  Google Scholar 

  • Bititci, U. S., Carrie, A. S., & Mcdevitt, L. (1997). Integrated performance measurement system: A development guide. International Journal of Operations & Production Management, 17(5–6), 522–534.

    Article  Google Scholar 

  • Blanc, S. (2006). Contribution à la caractérisation et l’évaluation de l’interopérabilité pour les entreprises collaboratives. Thèse de doctorat de l’université Bordeaux 1.

  • Boehm, B., Clark, B., Horowitz, E., & Westlan, C. (1995). Cost models for future software life cycle processes: COCOMO 2.0. Annals of Software Engineering, 1(1), 57–94.

    Google Scholar 

  • Chen, C., Dassisti, M., & Elvesaeter, B. (2006). Interoperability knowledge corpus. Deliverable DI.1b, Workpackage DI, INTEROP NoE. http://interop-vlab.eu/backoffice/ei_public_deliverables/.

  • Chen, D., & Daclin, N. (2007). Barrier driven methodology for enterprise interoperability, PROVE2007. In Proceedings of the establishing the foundation of collaborative, networks (pp. 453–460). Guimarães.

  • Chen, D., Doumeingts, G., & Vernadat, F. (2008). Architectures for enterprise integration and interoperability: Past, present and future. Computers in Industry, 59(7), 647–659.

    Article  Google Scholar 

  • Clark, T., & Jones, R. (1999). Organisational interoperability maturity model for C2. In Proceedings of the command and control research and technology symposium. USA.

  • Coutinho, C., Cretant, A., Ferreira da Silva, C., Ghodous, P., & Jardim-Goncalves, R. (2014). Service-based negotiation for advanced collaboration in enterprise networks. Journal of Intelligent Manufacturing. doi:10.1007/s10845-013-0857-4.

  • Ducq, Y., & Vallespir, B. (2005). Definition and aggregation of a performance measurement system in three aeronautical workshops using the ECOGRAI Method. International Journal of Production Planning and Control, 16(2), 163–177.

    Article  Google Scholar 

  • ENSEMBLE (2011) EISB Models and Tools Report, Deliverable 2.4, Envisioning, Supporting and Promoting Future Internet Enterprise Systems Research through Scientific Collaboration (ENSEMBLE) project-FP7-ICT-2009-5 Support Action (SA) Project. http://www.fines-cluster.eu/fines/jm/Publications/Download-document/303-ENSEMBLE_D2.4_EISB-Models-and-Tools-Report-v1.00.html, Accessed online April 9, 2013.

  • ENSEMBLE (2012-1) EISB State of Play, Deliverable 2.1, Envisioning, Supporting and Promoting Future Internet Enterprise Systems Research through Scientific Collaboration (ENSEMBLE) project FP7-ICT-2009-5 Support Action (SA) Project. Available at http://www.fines-cluster.eu/fines/jm/Publications/Download-document/339-ENSEMBLE_D2.1_EISB_State_of_Play_Report-v2.00.html, Accessed online April 9, 2013.

  • ENSEMBLE (2012-2) EISB Empowerment Actions Report, Deliverable 2.5, Envisioning, Supporting and Promoting Future Internet Enterprise Systems Research through Scientific Collaboration (ENSEMBLE) project-FP7-ICT-2009-5 Support Action (SA) Project. Available at http://www.fines-cluster.eu/fines/jm/Publications/Download-document/364-ENSEMBLE_D2.5_EISB-Empowerment-Actions-Report-v1.00.html, Accessed online April 9, 2013.

  • Enstone, L. J., & Clark, M. F. (2006). BPMN and simulation. Lanner Group Ed. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.130.3248&rep=rep1&type=pdf.

  • Epstein, M. J., & Westbrook, R. A. (2001). Linking actions to profits in strategic decision making. MIT Sloan Management Review, 42(3), 39–49.

    Google Scholar 

  • FINES. (2013). Future Internet Enterprise Systems (FInES): Enterprise Interoperability Science Base (EISB) Glossary. http://www.fines-cluster.eu/fines/mw/index.php/Enterprise_Interoperability (Accessed on April 9, 2013.).

  • Geraldi, J., & Adlbrecht, G. (2007). On faith, fact, and interaction in projects. Project Management Journal, 38(1), 87–98.

    Google Scholar 

  • Ghalayini, A. M., Noble, J. S., & Crowe, T. J. (1997). An integrated dynamic performance measurement system for improving manufacturing competitiveness. International Journal of Production Economics, 48(3), 207–225.

    Article  Google Scholar 

  • Gunasekaran, A., & Kobu, B. (2007). Performance measures and metrics in logistics and supply chain management: A review of recent literature (1995–2004) for research and applications. International Journal of Production Research, 45(12), 2819–2840.

    Article  Google Scholar 

  • Hamschera, W., Kiangb, M. Y., & Langc, R. (1995). Qualitative reasoning in business, finance, and economics: Introduction. Decision Support Systems, 15(2), 99–103.

    Article  Google Scholar 

  • Hani, Y., Amodeo, L., Yalaoui, F., & Chen, H. (2008). Simulation based optimization of a train maintenance facility. Journal of Intelligent Manufacturing, 19(3), 293–300.

    Article  Google Scholar 

  • Hansen, T. A., & Riis, J. O. (1999). Exploratory performance assessment. International Journal of Business Performance Management, 1(2), 113–133.

    Article  Google Scholar 

  • Hinkkanen, A., Lang, K. R., & Whinston, A. B. (2003). A set-theoretic foundation of qualitative reasoning and its application to the modeling of economics and business management problems. Information Systems Frontiers, 5(4), 379–399.

    Article  Google Scholar 

  • INTEROP (2006). Enterprise Interoperability-Framework and knowledge corpus—Advanced report, INTEROP NoE, FP6—Network of Excellence—Contract no 508011, Deliverable DI.2, December 15, 2006.

  • ISO (2009). ISO 16100–1:2009 Ed.2: Industrial automation systems and integration—Manufacturing software capability profiling for interoperability—Part 1: Framework.

  • Jardim-Goncalves, R., Agostinho, C., & Steiger-garcao, A. (2012). A reference model for sustainable interoperability in networked enterprises: Towards the foundation of EI science base. International Journal of Computer Integrated Manufacturing, 25(10), 855–873.

    Article  Google Scholar 

  • Jochem, R. (2010). Enterprise interoperability assessment. In 8th international conference of modeling and simulation MOSIM’10. Conference, Hammamet

  • Kaplan, R. S., & Norton, D. P. (1996). The balanced scorecard. Boston, MA: Harvard Business School Press.

    Google Scholar 

  • Kaplan, R. S., & Norton, D. P. (2001). The strategy-focused organization. Boston, MA: Harvard Business Press.

    Google Scholar 

  • Lee, J. W., & Kim, S. H. (2001). An integrated approach for interdependent information system project selection. International Journal of Project Management, 19, 111–118.

    Google Scholar 

  • Mahmudi, J., Nalchigar, S., & Ebrahimi, S. B. (2008). Selecting the most efficient information system project using data envelopment analysis: Case Study of Iran Ministry of Commerce. In Proceeding of 2008 international joint conference on e-Commerce, e-Administration, e-Society, and e-Education.

  • Martin, N. L., Pearson, J. M., & Furumo, K. A. (2005). IS project management: Size, complexity, practices and the project management office, system sciences. In: HICCS’05 proceedings of the 38th annual Hawaï International Conference on 03–06 Jan 2005.

  • Neely, A., Adams, C., & Kennerley, M. (2002). The performance prism: The scorecard for measuring and managing business success. Harlow, Essex: Financial Times Prentice Hall.

  • Niven, P. R. (2002). Balanced scorecard step by step. New York: Wiley.

    Google Scholar 

  • Panetto, H., & Molina, A. (2008). Enterprise integration and interoperability in manufacturing systems: Trends and issues. Computers in Industry, 59(7), 641–646.

    Article  Google Scholar 

  • Project Management Institute (PMI). (2008). A guide to the project management body of knowledge (4th ed.). Newtown Square, PA: PMI.

  • Ravelomanantsoa, M. (2009). Contribution à la définition d’un cadre générique pour la définition, l’implantation et l’exploitation de la performance: Application à la méthode ECOGRAI. PhD Thesis, University Bordeaux 1, Dec 17th 2009.

  • Ray, S. R., & Jones, A. T. (2006). Manufacturing interoperability. Journal of Intelligent Manufacturing, 17, 681–688.

    Article  Google Scholar 

  • Shenhar, A. J., Dvir, D., Levy, O., & Maltz, A. C. (2002). Project success: A multidimensional strategic concept. Long Range Planning Journal, 34, 699–725.

    Article  Google Scholar 

  • Siller, H. R., Estruch, A., Vila, C., Abellan, J. C., & Romero, F. (2008). Modeling workflow activities for collaborative process planning with product lifecycle management tools. Journal of Intelligent Manufacturing, 19(6), 689–700.

    Article  Google Scholar 

  • Sowlati, T., Paradi, J. C., & Suld, C. (2005). Information systems project prioritization using data envelopment analysis. Mathematical and Computer Modeling, 41, 1279–1298.

    Article  Google Scholar 

  • Supply Chain Council (2010). Model SCOR. version 10.0.

  • Tibaut, A., Rebolj, D., & Nekrep Perc, M. (2014). Interoperability requirements for automated manufacturing systems in construction. Journal of Intelligent Manufacturing. doi:10.1007/s10845-013-0862-7.

  • Value Chain Group (2012). Value Reference Model, 2012: http://www.value-chain.org.

  • Vidal, L. A., Marle, F., & Bocquet, J. C. (2011). Measuring project complexity using the analytic hierarchy process. International Journal of Project Management, 29(6), 718–727.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Wen, H. J., Lim, B., & Huang, H. L. (2003). Measuring e-commerce efficiency: A data envelopment analysis (DEA) approach. Industrial Management and Data Systems, 103(9), 703–710.

    Article  Google Scholar 

  • White, S. A., & Miers, D. (2008). BPMN modeling and reference guide: Understanding and using BPMN. Lighthouse Point, FL: Future Strategies Inc.

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Correspondence to François Galasso.

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Galasso, F., Ducq, Y., Lauras, M. et al. A method to select a successful interoperability solution through a simulation approach. J Intell Manuf 27, 217–229 (2016). https://doi.org/10.1007/s10845-014-0889-4

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