System Reliability Engineering Project

Answer in brief the following to get award of the full project.

The reliability engineer (RE) makes a request to develop a prognostic health management (PHM) program for critical components of a complex system to support the sustainment engineering program to develop appropriate maintenance management strategies. The RE recommends a piece of built-in test equipment, or passive fault management and diagnosis, to monitor a list of failure modes and mechanisms resulting from the Failure Mode and Criticality Analysis (FMECA) during the engineering development phase. The RE recommends the use of machine learning (ML) for the equipment to analyze the failures. What type of ML (supervised, unsupervised, reinforcement) would you use? Why?

Then, the integrated logistic support (ILS) team wants to leverage the use of ML to develop an interactive training program to test the maintenance crew troubleshooting and diagnostic skills. What type of ML (supervised, unsupervised, reinforcement) would you use? Why?

Evner: Industriel Ingeniør Videnskab, Mekanisk Ingeniørarbejde, Ingeniørarbejde

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Om arbejdsgiveren:
( 75 bedømmelser ) KARACHI, Pakistan

Projekt ID: #28337427

1 freelancer byder i gennemsnit $30 på dette job


Please review your message, I can¨t reply the chat. Hi. the answer to your questions is 1. ML unsupervised, because you don't have any prior data and you want Criticality Analysis (FMECA) during the engineering develop Flere

$30 USD in 3 dage
(0 bedømmelser)