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Health indicator construction for system health assessment in smart manufacturing

Soualhi, Moncef and Nguyen, Thi Phuong Khanh and Medjaher, Kamal and Lebel, Denis and Cazaban-Loustaunau, David Health indicator construction for system health assessment in smart manufacturing. (2019) In: 2019 Prognostics and System Health Management Conference, 2 May 2019 - 5 May 2019 (Paris, France).

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Smart manufacturing is a part of the fourth industry revolution (Industry 4.0), which offers promising perspectives for high reliability, availability, maintainability, and safety production process. Indeed, smart monitoring methods, that are implemented in this kind of manufacturing process, allow efficient tracking of a system degradation in real time through appropriate sensors. Then, the sensor data are analyzed and processed to extract effective health indicators for fault detection, diagnostic and prognostics. This paper aims to develop a practical methodology for constructing a new health indicator based on heterogeneous sensor measurements to efficiently monitor system states. The proposed methodology is applied to extract the health indicator of a robot cutting tool (i.e. end-flat mill). This indicator is then used to diagnose the different fault types of the tool by an adaptive neuro-fuzzy inference system model.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02487078
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Metallicadour (FRANCE)
Laboratory name:
Deposited On:06 Dec 2019 12:15

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