Our advanced data analytics platform and expert engineering capability will provide maximum insight about the effectiveness of your preventive maintenance from your data, no matter the information system or how poor or limited that data appears to be at first sight. With our approach using a combination of machine learning, expert engineers and heuristic and meta-heuristic analysis, low-quality data is utilised to provide insightful and powerful reports designed to optimise the specific decisions which need to be taken by a range of stakeholders.
We will work with your teams to extract the required data fields from your information systems. To assist in this process, we will provide you with data extract requirement and templates. The data that we will require is both master data and transactional data.
The minimum data required for the analysis is:
We also process other data sources for enhanced outcomes. These are but not limited to:
We utilise ShareFile by Citrix, a secure encrypted data transfer service for data transfer and secure storage at rest. This enables your team to securely transmit the data to us without limits to file sizes.
We will undertake analysis based on data from your asset information systems and provide you PM effectiveness reporting which will allow you to make informed decisions in the optimisation of your preventive maintenance. This analysis will focus on the two key concerns with the specification of preventive maintenance (PM) in an enterprise:
The analysis considers these two questions by searching all the work order history and for each asset considers the following scenarios:
Covaris reports provide detailed information of where the client needs to look to commence improving their preventive maintenance strategy.
In this example extract below a number of machines have high rates of corrective work and the current PM strategy is obviously not effective in addressing the failure modes in these machines.
We will provide a comprehensive report which will allow you to work with your teams to investigate specific preventive maintenance performance issues identified. You can make informed decisions on preventive maintenance optimisation using empirical evidence from this analysis. The time frame from receipt of data to the issue of the report is between 2 to 3 weeks. We can provide this type of in depth preventive maintenance performance reporting very quickly due to our proprietary software which we have developed over 18 years, our experienced engineers and analytical processes.