Online Condition Monitoring systems provide the promise of 24/7 coverage of asset condition and are seen by adopters as an enabler for moving from costly scheduled or reactive maintenance practices towards an optimised predictive maintenance approach.
A client operating within the mining industry contacted ALS for support dealing with operational downtime issues. At the time of contacting ALS, approximately 10 percent of their production time was associated with unplanned maintenance downtime. With this causing significant disruptions to production, the client engaged ALS to help reduce this to <1 to 2 percent - a downtime percentage in-line with world class operations.
So, this client engaged ALS to perform an Asset Monitoring Study with the end goal of implementing an Online Condition Monitoring strategy that would make this <1 to 2 percent goal feasible.
Asset Monitoring Study Process
ALS’s Asset Monitoring Study involves the following procedure:
1. Identify target equipment;
2. Identify monitoring technologies;
3. IT security and integration;
4. Select technologies and develop business case;
5. Data analytics reporting and alignment of technologies; and,
Universal to all clients adopting condition monitoring is the interdependent relationship between integration levels with the client’s existing systems and the benefits which can be derived by the client. With this integration critical to success, online systems present the optimal solution given their high integration levels and flexibility. When identifying and assessing systems, our team focus solely on systems capable of integrating with our clients existing operations.y
During a review of the client’s Computerised Maintenance Management System (CMMS) data, our team identified 43 out of their 371 assets were high impact targets for Online Condition Monitoring. These 43 assets included conveyors, pumps, screens, crushers, electrical transformers and beyond.
ISO 13379 defines the failure mode and symptoms analysis (FMSA) process with the output being a Monitoring Priority Number that can be used to select the technologies that will provide the greatest benefit. In order to align with these standards, ALS created FMSAs using the clients CMMS history and our experience for each target asset.
As with integration levels, our team recognise that to be of benefit data needs to end up in the right places. Given this, when ensuring effective integration, ALS completed vendor system assessments in-line with the client’s IT requirements and drawed upon our team’s diverse experience. This was done to ensure IT approval and to detail the data path.
Deriving the Value
Business due diligence requires a robust financial analysis be performed in order to justify capital expenditure. ALS delivered a preliminary design that was used to calculate the equipment and labour costs required to implement the online monitoring system.
A conservative benefit forecast was derived using agreed assumptions. ALS proposed solution was one-quarter of the implementation cost of the client’s preferred solution, with the potential to facilitate 40 percent greater downtime recovery.
Installing and operating the system is the start to improving asset reliability. Once installed, our client was better positioned to use Automated Machinery Learning in the future. From ALS’s experience working with data, a reporting and data strategy was developed ensuring all information collected is of value, both now and into the future.
Discover more about ALS's Online Condition Monitoring approach here.