A new paradigm for the continuous alignment of business and IT : combining enterprise architecture modelling and enterprise ontology

The paper deals with Next Generation Enterprise Information Systems in the context of Enterprise Engineering. The continuous alignment of business and IT in a rapidly changing environment is a grand challenge for today’s enterprises. The ability to react timeously to continuous and unexpected change is called agility and is an essential quality of the modern enterprise. Being agile has consequences for the engineering of enterprises and enterprise information systems. In this paper a new paradigm for next generation enterprise information systems is proposed, which shifts the development approach of model-driven engineering to continuous alignment of business and IT for the agile enterprise. It is based on a metamodelling approach, which supports both human-interpretable graphical enterprise architecture and machine-interpretable enterprise ontologies. Furthermore, next generation enterprise information systems are described, which embed modelling tools and algorithms for model analysis.http://www.elsevier.com/locate/compind2017-06-30hb201

Service-oriented modeling for e-business applications components

The emerging trends for e-business engineering revolve around specialisation and cooperation. Successful companies focus on their core competences, and rely on a network of business partners for the support services required to compose a comprehensive offer for their customers. Modulariy is crucial for a flexible e-business infrastructure, but related requirements seldom reflect on the design and operational models of business information systems. Software components are widely used for the implementation of e-business applications, with proved benefits in terms of system development and maintenance. We propose a service-oriented componentisation of ebusiness systems as a way to close the gap with the business models they support. Blurring the distinction between external services and internal capabilities, we propose a homogeneous model for the definition of ebusiness applications components. After a brief discussion on the foundational aspects of the approach, we present the process-based technique we adopted for component modelling. We then present an infrastructure compliant with the model proposed that we built on top of an EJB (Enterprise Java Beans) platform

Enterprise Modeling in the context of Enterprise Engineering: State of the art and outlook

[EN] Enterprise Modeling is a central activity in Enterprise Engineering and can facilitate Production Management activities. This state-of-the-art paper first recalls definitions and fundamental principles of enterprise modelling, which goes far beyond process modeling. The CIMOSA modeling framework, which is based on an event-driven process-based modeling language suitable for enterprise system analysis and model enactment, is used as a reference conceptual framework because of its generality. Next, the focus is on new features of enterprise modeling languages including risk, value, competency modeling and service orientation. Extensions for modeling collaborative aspects of networked organizations are suggested as research outlook. Major approaches used in enterprise modeling are recalled before concluding.Vernadat, F. (2014). Enterprise Modeling in the context of Enterprise Engineering: State of the art and outlook. International Journal of Production Management and Engineering. 2(2):57-73. doi:10.4995/ijpme.2014.2326SWORD577322AMICE. (1993). CIMOSA: Open System Architecture for CIM, 2nd revised and extended edition. Berlin: Springer-Verlag. 234 pages.Camarinha-Matos, L. M., & Afsarmanesh, H. (2007). A comprehensive modeling framework for collaborative networked organizations. Journal of Intelligent Manufacturing, 18(5), 529-542. doi:10.1007/s10845-007-0063-3Camarinha-Matos, L. M., Afsarmanesh, H., Galeano, N., & Molina, A. (2009). Collaborative networked organizations – Concepts and practice in manufacturing enterprises. Computers & Industrial Engineering, 57(1), 46-60. doi:10.1016/j.cie.2008.11.024Chakravarthy, S. (1989). Rule management and evaluation: an active DBMS perspective. ACM SIGMOD Record, 18(3), 20-28. doi:10.1145/71031.71034Chen, H. (2010). Editorial. ACM Transactions on Management Information Systems, 1(1), 1-5. doi:10.1145/1877725.1877726Clivillé, V., Berrah, L., & Mauris, G. (2007). Quantitative expression and aggregation of performance measurements based on the MACBETH multi-criteria method. International Journal of Production Economics, 105(1), 171-189. doi:10.1016/j.ijpe.2006.03.002Curtis, B., Kellner, M. I., & Over, J. (1992). Process modeling. Communications of the ACM, 35(9), 75-90. doi:10.1145/130994.130998Dalal, N. P., Kamath, M., Kolarik, W. J., & Sivaraman, E. (2004). Toward an integrated framework for modeling enterprise processes. Communications of the ACM, 47(3), 83-87. doi:10.1145/971617.971620Doumeingts, G., & Vallespir, B. (1995). A methodology supporting design and implementation of CIM systems including economic evaluation. In P. Brandimarte & A. Villa, Eds. Optimization Models and Concepts in Produc-tion Management (pp. 307-331). New-York, NY: Gordon and Breach Science Publishers.Doumeingts, G., & Ducq, Y. (2001). Enterprise modelling techniques to improve efficiency of enterprises. Production Planning & Control, 12(2), 146-163. doi:10.1080/09537280150501257Harzallah, M., Berio, G., & Vernadat, F. (2006). Analysis and modeling of individual competencies: toward better management of human resources. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 36(1), 187-207. doi:10.1109/tsmca.2005.859093Jagdev, H. S., & Thoben, K.-D. (2001). Anatomy of enterprise collaborations. Production Planning & Control, 12(5), 437-451. doi:10.1080/09537280110042675JORYSZ, H. R., & VERNADAT, F. B. (1990). CIM-OSA Part 1: total enterprise modelling and function view. International Journal of Computer Integrated Manufacturing, 3(3-4), 144-156. doi:10.1080/09511929008944444Khalaf, R., Curbera, F., Nagy, W.A., Mukhi, N., Tai, S., & Duftler, M. (2005). Understanding Web Services. In M. Singh, Ed. Practical Handbook of Internet Computing (Chap. 27). Boca Raton, FL: Chapman & Hall/CRC Press.Kosanke, K., & Nell, J. G. (Eds.). (1997). Enterprise Engineering and Integration. doi:10.1007/978-3-642-60889-6Kosanke, K., Vernadat, F.B., & Zelm, M. (2014). Means to enable Enterprise Interoperation: CIMOSA Object Capa-bility Profiles and CIMOSA Collaboration View, Proc. of the 19th World Congress of the IFAC, Cape Town, South Africa, 24-19 August 2014.Larson, N., & Kusiak, A. (1996). Managing design processes: a risk assessment approach. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 26(6), 749-759. doi:10.1109/3468.541335Li, Q., Wang, Z., Li, W., Li, J., Wang, C., & Du, R. (2013). Applications integration in a hybrid cloud computing environment: modelling and platform. Enterprise Information Systems, 7(3), 237-271. doi:10.1080/17517575.2012.677479Owen, S., & Walker, Z. (2013). Enterprise Modelling and Architecture. New Dehli, India: Ocean Media Pvt. Ltd.Roboam, M., Zanettin, M., & Pun, L. (1989). GRAI-IDEF0-Merise (GIM): Integrated methodology to analyse and design manufacturing systems. Computer Integrated Manufacturing Systems, 2(2), 82-98. doi:10.1016/0951-5240(89)90021-9Ross, D. T., & Schoman, K. E. (1977). Structured Analysis for Requirements Definition. IEEE Transactions on Software Engineering, SE-3(1), 6-15. doi:10.1109/tse.1977.229899Shah, L.A., Etienne, A., Siadat, A., & Vernadat, F. (2014). Decision-making in the manufacturing environment using a value-risk graph. Journal of Intelligent Manufacturing, 25, 2.Scheer, A.-W. (1992). Architecture of Integrated Information Systems. doi:10.1007/978-3-642-97389-5Scheer, A.-W. (1999). ARIS — Business Process Modeling. doi:10.1007/978-3-642-97998-9Vernadat, F.B. (1996). Enterprise Modeling and Integration: Principles and Applications. London: Chapman & Hall. 528 pages.Vernadat, F. B. (2007). Interoperable enterprise systems: Principles, concepts, and methods. Annual Reviews in Control, 31(1), 137-145. doi:10.1016/j.arcontrol.2007.03.00

The use of knowledge management systems and Event-B modelling in a lean enterprise

This paper provides a case study describing an approach to improving the efficiency of an information system (IS) by supporting processes outside the IS, using the ontology-driven knowledge management systems (KMS) as a mini-application in the area of so-called lean enterprise. Lean enterprise is focused on creating a maximal value for final customers while eliminating all kinds of waste and unnecessary costs, which significantly helps to increase the level of its competitiveness. It is about managerial decision-making, which can be in some cases contradictory (solving a local problem can cause a problem in another place). In this paper, we describe the KMS ATOM, which supports the innovation process in a lean enterprise. We show how the risk of wrong decisions due to contradictory effects can be eliminated by implementing a safety-critical system into the traditional IS. Our model is supported by Event-B modelling, a refinement-based formal modelling method, which is successfully used in important areas such as infrastructure, medicine, nuclear engineering and transportation (fire alarm systems, robotic surgery machines, braking systems in transportation, etc.). Nowadays, Event-B modelling is starting to be used for various management decision-making activities, and it is becoming a powerful competitiveness tool. This paper introduces a simple example of how Event-B modelling and its proof obligations can help improve and automate the decision-making process by eliminating potential threats of inefficient decisions.RVO project "Modelling of effective production and administration processes parameters in industrial companies based on the concept Industry 4.0

Towards a framework for inter-enterprise architecture to boost collaborative networks

A complete Inter-Enterprise Architecture should be conformed to a framework, a methodology and a modelling language. In this sense, this paper proposes an initial Framework for Inter-Enterprise Architecture (FIEA), which organizes, stores, classifies and communicates in a conceptual level the elements of the Inter-Enterprise Architecture (IEA) and their relationships, ensuring their consistency and integrity. This FIEA provides a clear picture about the elements and perspectives that make up the collaborative network and their inter-relationships, supported for technology base on the Internet for its inter-operation.This research has been carried out for the project “Sistema de ayuda a la toma de decisiones ante decisiones no programadas en la planificación jerárquica de la producción (ADENPRO-PJP)” Ref. SP20120703 Universitat Politècnica de València.Vargas, A.; Boza García, A.; Cuenca, L.; Ortiz Bas, Á. (2013). Towards a framework for inter-enterprise architecture to boost collaborative networks. En On the Move to Meaningful Internet Systems: OTM 2013 Workshop. Springer Verlag (Germany). 179-188. https://doi.org/10.1007/978-3-642-41033-8_26S179188Cuenca, L., Boza, A., Ortiz, A.: Enterprise Architecture Framework with Early Business/ICT Alignment for Extended Enterprises. In: Ortiz, Á., Franco, R.D., Gasquet, P.G. (eds.) BASYS 2010. IFIP AICT, vol. 322, pp. 11–18. Springer, Heidelberg (2010a)Vargas, A., Boza, A., Cuenca, L., Sacala, I.: Inter-Enterprise Architecture and Internet of the Future. In: Camarinha-Matos, L.M., Tomic, S., Graça, P. (eds.) DoCEIS 2013. IFIP AICT, vol. 394, pp. 25–32. Springer, Heidelberg (2013)Camarinha-Matos, L., Afsarmanesh, H.: Collaborative networks: Reference Modeling. Media, Springer Science + Business (2008)European Commission European Society and Media: Dygital Business Ecosystems. Office for Official Publications of the European Communities, Luxembourg (2007)Future Internet Enterprise Systems (FInES) Cluster: FInES Research Roadmap 2025, http://cordis.europa.eu/Vargas, A., Boza, A., Cuenca, L., Ortiz, A.: The importance of strategic alignment in enterprise collaboration. In: Prado-Prado, J.C. (ed.) Annals of Industrial Engineering 2012, pp. 1–8. Springer, London (2013)Henderson, J., Venkatraman, N.: Strategic alignment: Leveraging information technology for transforming organizations. IBM Systems Journal 32(1), 472–484 (1993)Vargas, A., Boza, A., Cuenca, L.: Lograr la alineación estratégica de negocio y las tecnologías de la información a través de Arquitecturas Empresariales: Revisión de la Literatura. In: XV Congreso de Ingeniería de Organización, Cartagena-España, pp. 1061–1070 (2011a)ISO 15704: Industrial automation systems - Requirements for enterprise-reference architectures and methodologies (2000)Kosanke, K.: CIMOSA Primer on key concepts, purpose and business value. CIMOSA Association, http://cimosa.cnt.pl/Cuenca, L., Boza, A., Ortiz, A.: An enterprise engineering approach for the alignment of business and information technology strategy. International Journal of Computer Integrated Manufacturing 24(11), 974–992 (2011)Vernadat, F.: Enterprise modelling and integration: From fact modelling to Enterprise Interoperability (2003)Vargas, A., Boza, A., Cuenca, L.: Towards Interoperability Through Inter-Enterprise Collaboration Architectures. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM-WS 2011. LNCS, vol. 7046, pp. 102–111. Springer, Heidelberg (2011)Plaza, J., Burgos, J., Carmona, E.: Measuring Stakeholder Integration: Knowledge, Interaction and Adaptational Behavior Dimensions. Journal of Business Ethics 93, 419–442 (2010)Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative networks: A new scientific discipline, pp. 439–452 (2005)Afsarmanesh, H., Msanjila, S.: Inter-organizational trust in VBEs. In: Camarinha-Matos, L.M., Afsarmanesh, H., Ollus, M. (eds.) Methods and Tools for Collaborative Networked Organizations. Springer (2008)Mehandjiev, N., Grefen, P.: Dynamic business process formation for instant virtual enterprises, London (2010)Kosanke, K., Vernadat, F., Zelm, M.: CIMOSA: enterprise engineering and integration. Computers in Industry 40, 83–97 (1999)Chen, D., Vallespir, B., Doumeingts, G.: GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology. Computers in Industry 33, 387–394 (1997)IFIP: GERAM: Generalised Enterprise Reference Architecture and Methodology. In: International Federation for Information Processing, http://dl.ifip.org/index.php/index/indexOrtiz, A., Lario, F., Ros, L.: Enterprise Integration—Business Processes Integrated Management: a proposal for a methodology to develop Enterprise Integration Programs. Computers in Industry 40, 155–171 (1999)Cuenca, L., Ortiz, A., Boza, A.: Business and IS/IT strategic alignment framework. In: Camarinha-Matos, L.M., Pereira, P., Ribeiro, L. (eds.) DoCEIS 2010. IFIP AICT, vol. 314, pp. 24–31. Springer, Heidelberg (2010b)THE OPEN GROUP: TOGAF, http://www.opengroup.org/togaf/Vesterager, J., T{\o}lle, M., Bernus, P.: VERA: Virtual Enterprise Reference Architecture. In: GMNBook, GLOBEMEN Final Plenary (2002)Chalmeta, R., Grangel, R.: ARDIN extension for virtual enterprise integration. The Journal of Systems and Software 67 (2003

Towards the development of the framework for inter sensing enterprise architecture

[EN] Inter-enterprise architecture (IEA) is a new concept that seeks to apply the tools and methodologies of enterprise architecture (EA) in a collaborative context, in order to model collaborative organizations in an inclusive manner. According to the main enterprise architectures proposed to this point, an EA should be conformed at least for a framework, a methodology and a modelling language. Sensing enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the Internet. These fields have come into focus recently, and there is not evidence of the use of IEA for modelling a SE, while finding an interesting gap to work on. Thus, this paper proposes an initial framework for inter sensing enterprise architecture (FISEA), which seeks to classify, organize, store and communicate, at the conceptual level, all the elements for inter-sensing enterprise architectures and their relationships, ensuring their consistency and integrity. This FISEA provides a clear idea about the elements and views that create collaborative network and their inter-relationships, based on the support of Future Internet.This work was supported by the European Commission FP7 UNITE Project, through its Secondment Programme and the Universitat Politecnica de Valencia ADENPRO-PJP project (ref. SP20120703).Vargas, A.; Cuenca, L.; Boza, A.; Sacala, I.; Moisescu, M. (2016). Towards the development of the framework for inter sensing enterprise architecture. Journal of Intelligent Manufacturing. 27(1):55-72. https://doi.org/10.1007/s10845-014-0901-zS5572271Adaba, G., Rusu, L., & Mekawy, M. (2010). Business-IT alignment in trade facilitation: A case study. In organizational, business, and technological aspects of the knowledge society. Communications in Computer and Information. Science, 44(112), 146–154.Afsarmanesh, H., & Msanjila, S. (2008). Inter-organizational trust in VBEs. In L. Camarinha-Matos, H. Afsarmanesh, & M. Ollus (Eds.), Methods and tools for collaborative networked organizations (pp. 91–118). New York: Springer.Afsarmanesh, H., Camarinha-Matos, L., & Ermilova, E. (2008). VBE reference framework. In L. Camarinha-Matos, H. Afsarmanesh, & M. Ollus (Eds.), Methods and tools for collaborative networked organizations (pp. 35–68). New York: Springer.Arango, M., Londoño, J., & Zapata, J. (2010). Arquitectura empresarial- Una visión general. Revista Ingenierías Universidad de Medellín, 9(16), 101–111.Audy, J., Lehoux, N., & D’Amours, S. (2012). A framework for an efficient implementation of logistics collaborations. International Transactions in Operational Research, 19(5), 633–657.Boza, A., Cuenca, L., Poler, R., Michaelides, Z., & Systems, Enterprise Information. (2014). The interoperability force in the ERP field. Enterprise Information Systems,. doi: 10.1080/17517575.2013.866697Camarinha-Matos, L., & Afsarmanesh, H. (2005). Collaborative networks: A new scientific discipline. Journal of Intelligent Manufacturing, 16(4–5), 439–452.Camarinha-Matos, L., & Afsarmanesh, H. (2008). Collaborative networks: Reference modeling. New York: Springer.Camarinha-Matos, L., Afsarmanesh, H., & Ollus, M. (2008). ECOLEAD and CNO base concepts. In L. M. Camarinha-Matos, H. Afsarmanesh, & M. Ollus (Eds.), Methods and tools for collaborative networked organizations (pp. 35–68). New York: Springer.Chalmeta, R., & Grangel, R. (2003). ARDIN extension for virtual enterprise integration. The Journal of Systems and Software, 67(3), 141–152.Chen, D., Vallespir, B., & Doumeingts, G. (1997). GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology. Computers in Industry, 33(2), 387–394.Choi, Y., Kang, D., Chae, H., & Kim, K. (2008). An enterprise architecture framework for collaboration of virtual enterprise chains. The International Journal of Advanced Manufacturing Technology, 35(11–12), 1065–1078.CIMOSA Asociation. (1996). CIMOSA Primer on key concepts, purpose and business value.Council of Supply Chain Management Professionals CSCMP. (2010). CSCMP. Glosary of terms. from http://cscmp.org/resources-research/glossary-terms . Accessed 9 February 2013Coutinho, C., Cretan, A., Ferreira, C., Ghodous, P., & Jardim-Goncalves, R. (2014). Service-based negotiation for advanced collaboration in enterprise networks. Journal of Intelligent Manufacturing,. doi: 10.1007/s10845-013-0857-4Cuenca, L. (2009). Marco arquitectónico para la propuesta IE-GIP. Extensión de la arquitectura CIMOSA. Aplicación a una empresa del sector cerámico. Tesis Doctoral Universidad Politecnica de Valencia.Cuenca, L., Boza, A., & Ortiz, A. (2011). An enterprise engineering approach for the alignment of business and information technology strategy. International Journal of Computer Integrated Manufacturing, 24(11), 974–992.Cuenca, L., Ortiz, A., & Boza, A. (2005). Arquitectura de Empresa. Visión General. Gijón: IX Congreso de Ingeniería de Organización.Dong, X., Liu, Q., & Yin, D. (2008). Business performance, business strategy, and information system strategic alignment: An empirical study on Chinese firms. Tsinghua Science and Technology, 13(3), 348–354.Ermilova, E., & Afsarmanesh, H. (2007). Modeling and management of profiles and competencies in VBEs. Journal of Intelligent Manufacturing, 18(5), 561–586.Estimali, H., Gardesh, H., & Sikari, S. (2010). Validating ITIL maturity to strategic business-IT alignment. In 2nd International conference on computer technology and development (ICCTD 2010).European Commission European Society and Media. (2007). Dygital Business Ecosystems. In F. Nachira, P. Dini, A. Nicolai, M. Le Louarn, & L. Rivera (Eds.). http://www.digital-ecosystems.org/book/ . Luxembourg: Office for Official Publications of the European Communities. Accessed 15 October 2012Executive Branch of the U.S. Federal Government. (2012). A Common Approach to Federal Enterprise Architecture. The White House. http://www.whitehouse.gov/sites/default/files/omb/assets/egov_docs/common_approach_to_federal_ea.pdf . Accessed 13 August 2013Franco, R., Gomez, P., Ortiz, A., & Navarro, R. (2012). Integrated approach for interoperability in collaborative networs and service-based ecosystems. In R. Poler, G. Doumeingts, B. Katzy, & R. Chalmeta (Eds.), Enterpise interoperability V (pp. 329–339). London: Springer.Force, I. F. I. P.-I. F. A. C. Task. (1998). GERAM: Generalised enterprise reference architecture and methodology. International Federation for Information Processing, 1(2), 30.Future Internet Enterprise Systems (FInES) Cluster. (2012). FInES Research Roadmap 2025. From http://cordis.europa.eu/fp7/ict/enet/documents/fines-research-roadmap-v30_en.pdf . Accessed 13 October 2013Henderson, J., & Venkatraman, N. (1993). Strategic alignment: Leveraging information technology for transforming organizations. IBM Systems Journal, 32(1), 472–484.Hu, Q., & Huang, D. (2006). Using the balanced scorecard to achieve sustained IT-business alignment: A case study. Communications of the Association for Information Systems, 17, 181–204.ISO 15704. (2000). Industrial automation systems–Requirements for enterprise-reference architectures and methodologies.ISO/CEN 19439. (2006). Enterprise integration–Framework for enterprise modelling.Kilger, C., Reuter, B., & Stadtler, H. (2008). Collaborative planning. In H. Stadtler & C. Kilger (Eds.), Supply chain management and advanced planning-concepts, models software and case studies (pp. 263–284). Berlin, Heidelberg: Springer.Kosanke, K., Vernadat, F., & Zelm, M. (1999). CIMOSA: Enterprise engineering and integration. Computers in Industry, 40(2), 83– 97.Lankhorst, M. (2009). Enterprise architecture at work: Modelling, communication and analysis. New York: Springer.Luftman, J. (2004). Assessing business-IT alignment maturity. Communications of the Association for Information Systems, 4, 99.Maes, R. (1999). Reconsidering information management through a generic framework. Amsterdam: Universiteit van Amsterdam, Department of Accountancy & Information Management.Mehandjiev, N., & Grefen, P. (2010). Dynamic business process formation for instant virtual enterprises. London.Mekawy, M., Rusu, L., & Ahmed, N. (2009). Business and IT alignment: An evaluation of strategic alignment models. In best practices for the knowledge society. 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Multi-product cost and value stream modelling in support of business process analysis

To remain competitive, most Manufacturing Enterprises (MEs) need cost effective and responsive business processes with capability to realise multiple value streams specified by changes in customer needs. To achieve this, there is the need to provide reusable computational representations of organisational structures, processes, information, resources and related cost and value flows especially in enterprises realizing multiple products. Current best process mapping techniques do not suitably capture attributes of MEs and their systems and thus dynamics associated with multi-product flows which impact on cost and value generation cannot be effectively modelled and used as basis for decision making. Therefore, this study has developed an integrated multiproduct dynamic cost and value stream modelling technique with the embedded capability of capturing aspects of dynamics associated with multiple product realization in MEs. The integrated multiproduct dynamic cost and value stream modelling technique rests on well experimented technologies in the domains of process mapping, enterprise modelling, system dynamics and discrete event simulation modelling. The applicability of the modelling technique was tested in four case study scenarios. The results generated out of the application of the modelling technique in solving key problems in case study companies, showed that the derived technique offers better solutions in designing, analysing, estimating cost and values and improving processes required for the realization of multiple products in MEs, when compared with current lean based value stream mapping techniques. Also the developed technique provides new modelling constructs which best describe process entities, variables and business indicators in support of enterprise systems design and business process (re) engineering. In addition to these benefits, an enriched approach for translating qualitative causal loop models into quantitative simulation models for parametric analysis of the impact of dynamic entities on processes has been introduced. Further work related to this research will include the extension of the technique to capture relevant strategic and tactical processes for in-depth analysis and improvements. Also further research related to the application of the dynamic producer unit concept in the design of MEs will be required

Special section Industry 4.0: Challenges for the future in manufacturing

International audienceThe sensing enterprise is a digital business innovation concept making Cyber-Physical Systems, service-oriented architectures and advanced human-computer interactions converge, supporting a more agile, flexible, and proactive management of unexpected events in today’s global value networks. In essence, it concerns the adoption of future Internet technologies in virtual enterprises. Translating this concept to a general approach to smart systems (smart manufacturing, smart cities, smart logistics, etc.), requires new capabilities by next-generation information systems to perform sensing, modelling, and interpretation of “any” signal from the real world, thus providing the systems with higher flexibility and possibilities for reconfiguration (Panetto et al. 2016). Intuitively, a sensing system requires resources and machineries to be constantly monitored, configured, and easily controlled by human operators. All these functions, and much more indeed, are now implemented by the so-called (Industrial) Internet of Things or Cyber-Physical Systems. With the advent of the new cyber-physical system design paradigm, the number and diversity of systems that need to work together in the future enterprises have significantly increased (Weichhart et al. 2016). This trend highlights the need to shift from the classic central control of systems, towards systems interoperability as a capability to control, sense, and perceive distributed and heterogeneous systems and their environments, as well as to purposefully and socially act upon their perceptions. Such a shift could have important consequences on the future architecture design of the control of these systems. The emergence of cloud-based technologies will also have a significant impact on the design and implementation of cyber-physical systems; using such novel technologies, collaborative engineering practises will increase globally, thus enabling a new generation of small-scale industrial organizations to function in an information-centric manner and enabling industry 4.0 transformations (Cimini, et al, 2017). The potential of such technologies in fostering a leaner and more agile approach towards engineering is very high. Engineers and engineering organizations no longer have to be restricted to the availability of advanced processing capabilities, as they can adopt a ‘pay as you go’ approach, which will enable them to access and use software resources for engineering activities from any remote location in the world

Visualizing Food Traceability Systems: A novel system architecture for mapping material and information flow

Background: Traceability of food products, ingredients and associated operations are important requirements for improving food safety and consumer confidence. Food traceability systems (FTSs) often suffer from inefficiency in either material or information flow within an enterprise or between supply chain partners. Modelling of system architecture is a visualisation approach that allows multiple parties to collaborate in a system design process, identify its inefficiencies and propose improvements. However, there is little academic research on the ability to use a standard visualisation tool that supports collaborative design and considers both material and information flow for a given food traceability system. Scope & Approach: The aim of this research is to propose a new visualisation approach that allows supply chain operators to collaborate effectively in the design process of FTSs capable of maintaining streamlined information flow, minimising information loss, and improving supply chain performance. Key findings & Conclusion: Food traceability systems are complex, encompassing processes, material flow, information flow, techniques, infrastructure, people and control strategies. Screening of literature demonstrates that model-based system engineering (MBSE) offers a sound way for visualisation of such complex systems. However, in the food traceability literature, an MBSE-based standardised traceability system modelling approach is absent. This study makes a strong contribution to existing literature by proposing a novel, material and information flow modelling technique (MIFMT), to visualise FTS architecture. MIFMT can support common understanding and iterative implementation of effective FTSs that contextualise food supply chains at multiple levels and provides opportunity to identify points at where inefficiencies can occur so that actions can be taken to mitigate them

Towards an agent-based model using a hybrid conceptual modelling approach:a case study of relationship conflict within large enterprise system implementations

There is a long history of using modelling and simulation (M&S) to investigate complex systems. With advances in computing power and simulation frameworks, we can now model and simulate increasingly complex systems, in particular socio-technical systems, which has resulted in M&S becoming an essential technique to aid decision-making. An often-overlooked activity within the design and development of computational models for socio-technical systems, is the development of a comprehensive conceptual model defining the scope of the model with respect to actors, technical resources, environment and abstraction level. With specific reference to modelling large IT and IS implementations, this incurs the added challenges of dealing with qualitative information relating to project scope and implementation processes, along with quantitative and qualitative information regarding the social network of the project resources and emergent behaviours that result from interactions between them. Our approach involves a Multi-Paradigm Hybrid Study to develop a Cross-Disciplinary Hybrid Model of relationship conflict within an enterprise system implementation. We identify that Soft Systems Methodology, Social Network Analysis, Unified Modelling Language are complementary approaches from Operational Research, Social Sciences and Software Engineering, that provide a powerful combination of techniques to develop hybrid conceptual models for subsequent encoding into a simplified Agent-Based Model of complex socio-technical systems