Modern Mining

DIGITALISATION

holdings, just in time delivery and well-planned maintenance windows, all of which will have huge financial savings while increasing plant efficiency,” explains Umar. Ntsele says data analyt- ics is essentially a process of analysing sets of data with the objective of gaining insights that will enable decision making. From a productivity perspective, and because of its timely nature – daily, weekly and monthly – KPIs can be based upon this data and thus guide or drive plant personnel behaviour to achieve the required result or output. According to Nellessen, today’s mining machines gener- ate a large amount of machine data. The vast amount of data needs to be filtered, clustered and aggregated in such a way that it can be processed. “In combination with equipment knowledge the generated data can be interpreted in a mean- ingful way. Data patterns can

for trending and analysis. This will however cause a delay from fault to alarm. To compensate for this, a local display for the operator to reference can be used. This enables the operator to make an informed decision on criticality. Mobile equipment breakdown frequency will be reduced and reliability increased,” explains Zeelie. Every plant will have critical and non-critical equipment, says Umar. Online monitoring devices are usually used for critical equipment and hand- held data devices used when the equipment does not warrant expensive online devices. SKF’s Rotating Equipment Performance model however allows for both online and hand-held data acquisition devices to be deployed in the plant utilising OpEx instead of CapEx. This model bundles together condition monitoring services, remote diagnostics and other services and both lubrication and bearing products into a unique tailor-made package to meet each cli- ent’s needs. Ntsele says where multiple equipment is con- cerned, harnessing the power of digital tools enhances the ability to gather insights that would otherwise be missed due to the inherent complex- ity of the interdependencies of systems. “Therefore, OEE is greatly impacted when an integrated digital approach that covers the four technology clusters I described earlier is adopted and implemented across the mining value chain, especially when ore parameters form part of the data matrix,” he says. Data analytics Data analytics plays a significant role in the digi- talisation process, says Zeelie. “It is the process of interpreting and understanding what is being mea- sured. When done correctly, it will result in better understanding of the process and what are the draw- backs. The drawbacks can then be improved on or eliminated. The end goal of data analytics should be to use the available information to understand the process and improve on productivity and reliability,” explains Zeelie. Umar adds that SKF globally has embarked on the road to Big Data. There are nine certified Remote Diagnostic Centres, which means that equipment can be benchmarked against similar equipment anywhere in the world. These centres are working towards a uniformed methodology of data collection, data management, analysis and reporting. The infor- mation can be viewed via dashboards but it is also used for much larger projects such as Prognosis and Machine Learning. “The goal in the not too distant future will be for plant equipment to self-diagnose impending faults and predict lead times to failure. This will enable pieces of equipment themselves to order critical components for replacement early in the failure curve and help alleviate logistic issues on long lead times. The knock-on effect will be leaner stock

be linked to specific events and machine behaviour, for example, detection of anomalies can prevent machine failures or provide the basis for optimised maintenance effort and optimised holding of spare and wear parts inventory. In other words, data analytics turns data into meaningful information,” concludes Nellessen. 

SKF has embarked a road to Big Data, with nine certified Remote Diagnostic Centres globally.

Key takeaways  One of the current challenges when it comes to productivity increase questions is the lack of reliable data or data at all  Digitalisationmakes datamore accessible and optimisation easier through complex computer models  Every plant will have critical and non-critical equipment. Online monitor- ing devices are usually used for critical equipment and hand-held data devices used when the equipment does not warrant expensive online devices  There are four key digital technological areas that are receiving attention from industry, namely, computation power, data analytics, human-machine- interface and robotics  Connectivity and data are crucial in digitisation – some of the main ben- efits in digitalisation are derived from the real-time access to information derived from a vast amount of data  Data analytics play a significant role in the digitalisation process. It is the process of interpreting and understanding what is beingmeasured. When done correctly, it will result in better understanding of the process and what are the drawbacks 

February 2020  MODERN MINING  31