ScholarIQanswers from OpenAlex

Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research.

PaperCitations, authors & open-access status

Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. is a paper indexed in ScholarIQ from OpenAlex.

How many citations does Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. have?

ScholarIQcitation count

Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. has 41 citations in the OpenAlex counts ScholarIQ stores.

When was Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. published?

ScholarIQyear

Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. has 2015 year in the ScholarIQ index.

What is the open-access status of Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research.?

ScholarIQoa status

Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. has diamond oa status in the ScholarIQ index.

What is the DOI of Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research.?

ScholarIQdoi

The DOI for Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. is on the source record.

What is the OpenAlex record for Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research.?

ScholarIQopenalex

The OpenAlex for Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach ★ ★The authors gratefully acknowledge STMicroelectronics for their support and provision of data for TT case study. The authors also acknowledge European project INTEGRATE and region RhoneAlpes for ongoing Research. is on the source record.

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