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- W3204179639 abstract "This thesis work is part of a collaboration between FEMTO-ST / ENSMM and the SCODER company which is an SME located in the Doubs and specializes in the manufacture of high precision automotive parts. This project aims to develop a data management and predictive analysis approach (Prognostics and Health Management (PHM)). This is a partnership within the framework of the digital transformation of the SCODER company. One of the originalities of this thesis work is to develop a data-oriented PHM approach adapted to SMEs. Our approach is based on the needs of users to quantitatively and qualitatively identify the needed data and estimate the resulting cost. To achieve these objectives, a study is carried out on the basis of the state of the art and reinforced by field observations to identify the determining parameters for the application of PHM in SMEs. These parameters can be summarized in three points: user needs, data and cost. In fact, the advantage in SMEs is the versatility of the staff which allows a detailed analysis of the problems and their impact on the entire production process. Consequently, the phase of modeling the problem and identifying the needed parameters for the resolution seems easier and more efficient in the case of SMEs. One of the challenges of the proposed approach is the analysis of return on investment (ROI). We have proposed a first formalization of the cost of the PHM in order to size the budget necessary for its implementation. This thesis was developed in three stages. The first is to optimize the data acquisition phase and study their quality. The second part concerns the development of a collaborative PHM approach, the objective of which is to formalize human expertise and use it in the PHM process. The third part proposes a cost model to estimate the investments necessary for the success of a PHM project while estimating the ROI. Our entire approach is offered in the form of a general methodology for the implementation of PHM dedicated to SMEs. This methodology has been encapsulated in a software called Scoder Data System (DS2) in order to facilitate its implementation. The validation phase was carried out with data and knowledge from the SCODER company." @default.
- W3204179639 created "2021-10-11" @default.
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- W3204179639 date "2021-04-22" @default.
- W3204179639 modified "2023-09-27" @default.
- W3204179639 title "Knowledge extraction from SME data for the implementation of PHM process" @default.
- W3204179639 hasPublicationYear "2021" @default.
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