This work presents an iterative methodology for reliability design of production equipment based on the diagnostic and prognostic approach. The proposed method starts with the FMECA analysis in order to identify the main critical components of mechanical systems (e.g. robotic cells, robots, automatic machines). The mitigation actions are selected evaluating a design review of the project or imposing a maintenance strategy by critical component. This selection is defined by the calculated risk (e.g. risk priority number) and the life cycle cost assessment of the production equipment. The analysis of failure causes may support in evaluating preventive or predictive techniques focused on physical or data driven models. The use of a general database that collects and shares information from systems/components already installed in the field permits to analyse life and performance data in real time in an integrated closed loop. This research is a part of PROGRAMS: PROGnostics based Reliability Analysis for Maintenance Scheduling, H2020-FOF-09-2017-767287.
Design for Reliability of Robotic Systems Based on the Prognostic Approach
Aggogeri F.
;Pellegrini N.;Taesi C.;Tiboni M.
2019-01-01
Abstract
This work presents an iterative methodology for reliability design of production equipment based on the diagnostic and prognostic approach. The proposed method starts with the FMECA analysis in order to identify the main critical components of mechanical systems (e.g. robotic cells, robots, automatic machines). The mitigation actions are selected evaluating a design review of the project or imposing a maintenance strategy by critical component. This selection is defined by the calculated risk (e.g. risk priority number) and the life cycle cost assessment of the production equipment. The analysis of failure causes may support in evaluating preventive or predictive techniques focused on physical or data driven models. The use of a general database that collects and shares information from systems/components already installed in the field permits to analyse life and performance data in real time in an integrated closed loop. This research is a part of PROGRAMS: PROGnostics based Reliability Analysis for Maintenance Scheduling, H2020-FOF-09-2017-767287.File | Dimensione | Formato | |
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