Big Data Services
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It is now hard to find an enterprise without a CMMS, many of which are full of rich information. However, there are not many companies that are making use of their rich maintenance data.
Utilising scientifically proven data mining techniques, our expert predictive data analysts and data miners can develop data mining and statistical models that can shed light on the hidden patterns in your CMMS data.
Using the results of these analyses, the outcome of the existing strategies could be tested to see if the maintenance management system is performing as well as it should be.
Also, based on these results, new maintenance policies could be formed to excel the maintenance management systems.
Below is a list of some of big data and data mining services offered by IntelData.
Asset Condition Management (ACM)
Our data mining experts have developed a novel data mining model that not only can clearly identify the condition of your assets but also can help you discover the major contributing factors to your asset conditions so that you can take measures to rectify your maintenance processes.
This novel model utilises data mining and machine learning algorithms in such way that can give your maintenance team clear rules to follow to improve upon the conditions of your assets.
Identifying the Inefficient Maintenance Activities
Knowing which one of the maintenance activities in your maintenance management system is effective or not can give you a good and clear picture to focus your efforts on.
This cannot easily be done by any human beings. It is not easy for any reliability and maintenance engineer to walk into a plant and spend some time (even months) and decide which one of the maintenance activities are not contributing to the maintenance systems efficiency in terms of increasing machinery uptime and reliability, cost reduction etc. And even more importantly, what the reasons for this are. Is the personnel training? Is it the spare parts availability? Is it the logistics and support element?
Therefore, we have developed a novel data mining model which utilises machine learning algorithms which can easily sift through your maintenance system data and point out clearly to the maintenance activities that are not effective.
Failure, Reliability and Cost Prediction
In industrial environments, data generated during equipment maintenance and monitoring activities is increasing overwhelmingly. In many instances the maintenance personnel are simply unable to analyse this volume of data in-house. However, mining this data provides opportunities to forecast the future of a maintenance system.
Our data mining experts use data mining techniques to predict maintenance parameters such as assets’ reliability, maintenance costs, assets’ failure rates etc.
Furthermore, using CMMS, logistics and support data, different scenarios can be simulated. This helps the maintenance management clearly see what future holds as a consequence of their decisions and how they can improve the performance of the system under their management.