VR-PMS: a new approach for performance measurement and management of industrial systems

A new performance measurement and management framework based on value and risk is proposed. The proposed framework is applied to the modelling and evaluation of the a priori performance evaluation of manufacturing processes and to deciding on their alternatives. For this reason, it consistently integrates concepts relevant to objectives, activity, and risk in a single framework comprising a conceptual value/risk model, and it conceptualises the idea of value- and risk based performance management in a process context. In addition, a methodological framework is developed to provide guidelines for the decision-makers or performance evaluators of the processes. To facilitate the performance measurement and management process, this latter framework is organized in four phases: context establishment, performance modelling, performance assessment, and decision-making. Each phase of the framework is then instrumented with state of-the-art quantitative analysis tools and methods. For process design and evaluation, the deliverable of the value- and risk-based performance measurement and management system (VR-PMS) is a set of ranked solutions (i.e. alternative business processes) evaluated against the developed value and risk indicators. The proposed VR-PMS is illustrated with a case study from discrete parts manufacturing but is indeed applicable to a wide range of processes or systems

Towards A System-Based Model For Overall Performance Evaluation In A Supply Chain Context

International audienceThe paper deals with the wide issue of overall performance expression of a system made of interacting entities. Formal aspects of overall performance expression are considered as a first step of this reflection in the context of supply chains (SC's). Indeed, a SC being a network of interconnected business entities, it is proposed to consider it as a system of systems. Because system behavior depends on process dynamics, the performance of any company of the SC highly depends on the performance of its processes. However, while process performance is clearly defined in the literature, performance of complex systems or systems of systems is more difficult to assess due to process interactions. The overall performance concept is usually unsatisfactory either for each company or for the whole SC. To express such performance in SC's, recent proposals have focused on the performance of the prime manufacturer. This performance being linked to the ones of the suppliers, the impact of supplier performances on the prime manufacturer performance has to be integrated. It is therefore proposed to respectively use the SCOR model for describing the involved sub-system processes and, from a computational point of view, to use the MAUT (Multi Attribute Utility Theory) MACBETH methodology to consistently compute the expected performances. More specifically, the Choquet integral is used as the aggregation operator to handle interactions between systems and processes. The case of a bearings manufacturer is used to illustrate the proposal for a supplier selection problem

18th ICPR paper: INDUSTRIAL PERFORMANCE MEASUREMENT: AN APPROACH BASED ON THE AGGREGATION OF UNIPOLAR OR BIPOLAR EXPRESSIONS

International audienceIndustrial performance concerns numerous criteria, often in interaction and of complex nature, not related to one elementary measure. Performance Measurement Systems (PMSs) have been developed to support decision-making for reaching the objectives and launching adequate action plans. PMSs provide thus performance expressions which identify objective satisfaction degrees. Two kinds of performance expressions are useful in industrial problems, according to the scale (unipolar, bipolar) that is used for their definition. Moreover, these expressions generally have to be synthesized for global control purposes, determining an overall performance raises the issue of performance aggregation. To address such an aggregation issue, adequate multi-criteria methods need to be implemented. Most of the approaches proposed in the literature either do not provide explicit mechanisms, or rely on too simple methods. This paper deals with the definition of a performance combination based on mathematical tools, especially the generalized Choquet integral to take into account on the one hand criteria interactions and on the other hand both unipolar and bipolar scales. An application to a PMS for the service rate of a SME producing kitchen elements is used to illustrate the approach

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

A formal verification framework and associated tools for enterprise modeling : application to UEML

The aim of this paper is to propose and apply a verification and validation approach to Enterprise Modeling that enables the user to improve the relevance and correctness, the suitability and coherence of a model by using properties specification and formal proof of properties

Decision-making in the manufacturing environment using a value-risk graph

A value-risk based decision-making tool is proposed for performance assessment of manufacturing scenarios. For this purpose, values (i.e. qualitative objective statements) and concerns (i.e. qualitative risk statements) of stakeholders in any given manufacturing scenario are first identified and are made explicit via objective and risk modeling. Next, performance and risk measures are derived from the corresponding objective and risk models to evaluate the scenario under study. After that, upper and lower bounds, and target value is defined for each measure in order to determine goals and constraints for the given scenario. Because of the multidimensionality nature of performance, the identified objectives and risks, and so, their corresponding measures are usually numerous and heterogeneous in nature. These measures are therefore consolidated to obtain a global performance indicator of value and global indicator of risk while keeping in views the inter-criteria influences. Finally, the global indicators are employed to develop minimum acceptable value and maximum acceptable risk for the scenario under study and plotted on the VR-Graph to demarcate zones of “highly desirable”, “feasible”, “and risky” as well as the “unacceptable” one. The global scores of the indicators: (value-risk) pair of the actual scenario is then plotted on the defined VR-Graph to facilitate decision-making by rendering the scenarios’ performance more visible and clearer. The proposed decision-making tool is illustrated with an example from manufacturing setup in the process context but it can be extended to product or systems evaluation

The Intra-cell layout problem in automated manufacturing systems

The problem of the machine layout inside manufacturing cells (intra-cell layout problem) of an automated manufacturing system is addressed in this paper. The solution presented is divided into two main steps. The first step consists of selecting the materials handling system and the possible machine layout type. This procedure is based on the characteristics of : products (which belong to the same product family), their manufacturing processes and machines. An expert system has been developed for this part. The second step consists of evaluating the alternative arrangements of the machines inside the manufacturing cell in order to minimize the intra-cell traffic (costs) while respecting the physical constraints between the machines, between the machines and their environment, product constraints, technological contraints, user preference, etc. This part is performed using operations research algorithms

Towards a Formal Verification of Process Model's Properties - SimplePDL and TOCL Case Study

International audienceMore and more, models, through Domain Specific Languages (DSL), tend to be the solution to define complex systems. Expressing properties specific to these metamodels and checking them appear as an urgent need. Until now, the only complete industrial solutions that are available consider structural properties such as the ones that could be expressed in OCL. There are although some attempts on behavioural properties for DSL. This paper addresses a method to specify and then check temporal properties over models. The case study is SimplePDL, a process metamodel. We propose a way to use a temporal extension of OCL, TOCL, to express properties. We specify a models transformation to Petri Nets and LTL formulae for both the process model and its associated temporal properties. We check these properties using a model checker and enrich the model with the analysis results. This work is a first step towards a generic framework to specify and effectively check temporal properties over arbitrary models