Predictive Maintenance API

By GK Palem December 2, 2018 #API, #Automotive, #Case study, #Engineering, #M2M, #Reliability

Optimizing the asset usage requires calculating the asset’s remaining-useful-life (RUL) based on the current and historic usage patterns and building a mathematical model that is capable of extrapolating failures from the past to the future. Problem: Calculate the reliability of a system of components Methodology: Cenacle offers Predictive Maintenance API that allows failure estimation based on the below methodology:

Given system is decomposed into individual logical components
Reliability is calculated for each component under the given conditions
Reliability of the system is derived as an aggregated value of the individual results

Results: A truly one of a kind predictive maintenance API that computes reliability based on the design parameters and real-time operating conditions

Key concepts: Predictive Maintenance, M2M Telematics, Reliability Engineering, Failure Prediction, Condition-based Maintenance, API, RUL Domain: Automotive, Engineering

By GK Palem

A seasoned Executive with more than two decades of experience in growing software businesses and executing large-scale enterprise projects around emerging technologies. Proven track record of commercializing R&D concepts into commercial products. Connect with GK Palem if you are trying to adapt AI or Blockchain into Genomics, Computational Biology, Healthcare Informatics, Industrial Digitial Transformation, Cross-border Trade Smart Contracts or other deep-tech solutions or R&D concepts.

Predictive Maintenance API

By GK Palem

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