Improve quality with faster, increased data insight, reduce hidden bottlenecks – find the causes of faults even before they exist, automatically classify warranty issues, reduce maintenance downtime.
The first comprehensive automated, predictive software suite that optimises scheduling of corrective maintenance and prevent unexpected equipment failures.
For any asset, from aircraft to vehicles to oil refineries and factories. Developed from over a decade of academic research with proprietary algorithms for retrieving signals and processing them.
No need for data scientists or large project teams, just simple, actionable insight, whenever needed, to provide the optimal decisions for any maintenance regime.
How should I optimally manage the asset for best overall OEE? When should I maintain or replace the asset? What is the best course of action I should take? Which issues are repeating and growing and is my condition monitoring set up optimally?
Now you can get the answers to these questions and more with MaintenanceGuardian. The capabilities built in are: • Detect anomalies • Predict both issues and anomalies • Simple sets of business rules which can be understood to help identify root causes and/or predict the issues and anomalies • Dynamic alerts and alarms when anomolies occur in order to provide early warning so that preventative action may be taken • Clusters of error logs, alarms and notes of operators or engineers who maintain equipment – mined from ERP and Asset Maintenance databases as well as live operational systems • Groups of semantically similar events and issues for more valid signals • The output is a simple set of actionable recommendations with their predictive scores and impact
The key technologies behind the workflows: 1 Trend & Anomaly Detection (TAD): Automatic detection of anomalies, whether in or out of tolerance levels 2 Event Clustering & Classification (ECC): Automatic clustering and classification of issues, even unstructured and heterogeneous data such as event logs, error codes and text verbatim maintenance notes 3 Predictive & Explanatory Analysis (PEA): Automatic analytics to explain and/or predict issues as well as anomalies 4 Early Warning and Prediction (EWAP): Alerts and alarms when predictive signals are found, or anomalies are detected 5 Automated Information Retrieval (AIR): Transforms unstructured data including text to find hidden patterns 6 Root Cause Analysis Solver Engine (RCASE): Mines the entire ‘searchspace’ of possible solutions to find the best, actionable solution which explains/predicts issues and anomalies
The first comprehensive automated, predictive software suite for any warranty situation, from aircraft to vehicles to consumer electronics and machines.
Shrink the time from detection to resolution of potentially all issues, on a continual basis, and ensuring that fixed things stay fixed.
No need for an army of data scientists or large project teams, just simple, actionable insight for any maintenance regime.
Decisions can be taken to interpret and prioritise issues, work with engineering to figure root causes, reduce fraud and error with dealers and resellers, and use the feedback to improve the customer experience.
How should I classify the warranty claims? How do I spot fraud and error with dealers and resellers? How can I look for root causes for issues? Which issues are repeating and growing and what should I prioritise?
Now you can get the answers to these questions and more with WarrantyGuardian. The capabilities built in are: • Anomaly detection • Predictions of both issues and anomalies • Appropriate alerts and alarms on anomaly detection • Proactive interrogation of the data • Clusters of the verbatim notes of the dealers, resellers and engineers who maintain equipment • Automatic classification and clustering into groups of semantically similar issues • The output is a simple set of actionable recommendations with their predictive scores and impact
WarrantyGuardian is being used by some of the leading global automotive, aerospace and electronics companies. It acts as an intelligent agent, plugging into your warranty database to automatically generate the insight required to take effective decisions so that warranty professionals can do more.
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