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Authors would like to thanks the program INTERREG V Suisse-France for providing financial support to conduct this study in the framework of the project G2 Solar which aims at extending the solar cadaster to the Greater Geneva and intensify energy solar production at this level. We greatly acknowledge R. Giraudon at Urban Solar Energy, and B. Benchenafi at Reservoir Sun, for their helpful discussion and their expertise. We finally thank Manon Turban for her proofreading of the document.
International audienceThis study deals with the supply chain (SC) overall performance expression. The developed idea concerns more particularly the performance of the manufactured products. Indeed, two companies or more contribute to the manufacturing of products that are generally assembled by the prime manufacturer company. Moreover, in the industrial practice, performance scorecards are defined with regard to each process; and the overall performance is neither expressed for each company, nor for the whole SC. We propose here to identify the SC overall performance to the combination of the performances of the different involved companies in the SC. Thus, in order to obtain a definition of such performance, we choose to focus first on the performance of the prime manufacturer. In this sense, the approach is based on the SCOR model for the handling of the main processes around the considered product manufacturing. The prime manufacturer performance is then defined as the aggregation of its involved processes' performances. While the prime manufacturer performance is strongly dependent on the suppliers' performance, we suggest the integration of the impacting supplier performance into the prime manufacturer scorecards. From an operational point of view, the MACBETH methodology is used to coherently express both processes and overall performances. More precisely, the Choquet aggregation integral operator is applied in order to model mutual interactions between processes. Finally, the expression of a bearing's manufacturer performance illustrates the proposition
This article addresses the issue of the industrial performance model and its evolution to cope with the context of Industry 4.0. With its digitalisation, intelligent/autonomous systems and wealth of data, Industry 4.0 offers opportunities that can achieve objectives better. It also presents risks and uncertainties that question the autonomy of the systems, their interaction with humans and the use of available data. The hypothesis put forward in this work is that the efficiency–effectiveness–relevance performance triangle can no longer guarantee long-term performance under these conditions and needs to be associated with an ethical dimension that allows for the risks and uncertainties relating to Industry 4.0 to be considered. Ethics is therefore considered to extend the triangle to a tetrahedron. A brief analysis of current performance management will first show the limits of the current practice in the context of Industry 4.0. The frameworks that could overcome these limits in light of new needs are then recalled and discussed, leading to the choice of ethics, whose main definitions and use in the engineering field are also introduced. The proposed (efficiency–effectiveness–relevance–ethics tetrahedron-based methodology is illustrated through a case study related to an aeronautical supplier, regarding the consequences of the implementation of a MES (Manufacturing Execution System) in terms of product traceability and operator autonomy. The discussion and prospects finally conclude this study.
International audienceThe major industrial control purpose is the reaching of the expected performances. In this sense, improvement processes are continuously carried out in order to define the right actions with regard to the objectives achievement. Thus, in order to better monitor the performance continuous improvement process, we consider a quantitative model for performance assessment. The industrial performance being multi-criteria, the proposed model is thus based on the one hand, on the MACBETH method to express quantitatively elementary performances from qualitative expert pair-wise comparisons and, on the other hand, on the Choquet integral to express the overall performance according to subordination and transverse interactions between the elementary performances. Then, the main focus concerns the decision-maker's requirements for optimising the improvement of the overall performance versus the allocated resources. In this view, we propose useful pieces of information first for diagnosis, then for overall performance improvement optimisation versus the costs of elementary performance improvements. Finally, the proposed approach is applied to an industrial case looking for optimising the improvement of the lean objective satisfactio
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