Digitalisation allows mines to generate more value from existing assets without incurring more labour costs
After a long-standing trend of declining productivity, the mining sector is gradually reversing the course – according to the new analysis by McKinsey. This is because mine operators are increasingly focusing on extending asset lifecycles, re-examining and remodelling their processes with a strong focus on digital. Yet, despite recent improvements, productivity is still some 25% lower than the baseline and even more so compared with other global industries.
A combination of market volatility, radically different input economics and limitations of existing measurement approaches have been hindering the industry’s ability to address the challenge. For example, an overall equipment effectiveness (OEE) metric provides important insights about availability, utilisation and performance of a cone crusher or a processing plant, but doesn’t offer guidance on the whole operations progress and total productivity performance.
Technological complexity is increasingly beyond the human field of vision. Systems are not only working at speed but are also built on top of and within each other, often interacting in unexpected ways. Operators find it difficult to consistently predict what is coming next, even with condition monitoring solutions in their toolbox.
“Many mines have adopted a mixture of technologies – including sensors, industrial internet of things (IIoT) devices, hardware and software – facilitating reach to difficult asset locations and stretching monitoring distances,” says Ben Berwick, who is responsible for asset performance management (APM) at ABB. “But, because these solutions typically operate in silos, there is still too much manual effort involved, with subject-matter experts (SMEs) running in and out of multiple systems, relying on visual interpretation, assembling insights, etc., before they can recommend actions. Their time could be better used.”
These problems have been compounded by the fact that the people with mechanical and electrical asset expertise are in high demand and in short supply around the world. When capable technicians and reliability engineers leave or retire, the knowledge of assets they worked on often leaves the mine with them.
Obtaining Higher Productivity
This means that mining still has some latent capacity to go for. The stage is set for a more mature approach that would free up people, resources and maximise return on all assets. Momentum is gathering around the next generation of APM, referred to as APM 4.0 by LNS Research. APM 4.0 is described by LNS analysts as an evolutionary shift to align with Industry 4.0 and drive lower operations cost, improved asset reliability, longer asset life and better decommissioning and disposal costs.
APM 4.0 is a step change in the way industrial companies maintain their mechanical, electrical, and rotating assets. It will ensure that assets are available at the time and at the performance level required by operations, depending on changing production goals.
“Think of APM 4.0 as the most cost-effective way to extend the life of both ageing and newer assets,” explains Eduardo Ingegneri, a product manager for APM in mining at ABB.
According to Berwick, APM is a productivity tool: “Successful implementations automate the delivery of early predictions and truly actionable information to the reliability, maintenance and operations personnel – long promised, but scarcely delivered previously.”
Consider the following important factors of productivity improvement with APM 4.0.
Build Upon Best Practices
Make sure your next-level APM programme is not perceived as a ‘flavour of the month’ but builds upon the software packages and continuous improvement initiatives already in place – creating a better system out of existing solutions. New skills and changes to historic work processes will be eagerly adopted by experts if they reduce their burden of juggling assets, provide earlier signs of degradation and speed up the analysis. By learning to perform more advanced analytics on a combined OT and IT dataset, they will gain a means to monetise different maintenance options, consider impacts of planned maintenance schedules, devise a means to extend intervention intervals and asset longevity.
“Realising greater APM effectiveness and augmenting the underlying digital systems involves not only the newest mature technologies, but also alignment with what mining experts already do well,” says Berwick. “This only accentuates the imperative role that experts play now and will forever play in delivering the outcomes you expect.”
Conquer Your Data
Today’s Big Data analytics – evident in Amazon or Google consumer prediction – are augmenting APM systems as well. However, addressing integration complexity and aggregating data is not a trivial task and can be the most time-consuming element of a transformation. Companies often discover that they have gaps either in the data that’s available for analysis, or in the quality of that data, or both. The most suitable approach is evolutionary from past implementation of automation, control and condition monitoring systems, previous modelling, and simulation of such systems. Availability of cloud connectors, context-aware data aggregators and template libraries with cyber security built into an APM platform considerably improve the initial engineering productivity and time to value.
“The most reliable approach with an APM 4.0 transformation is to start with the existing data from the assets that are known to cause trouble or be energy-hungry,” says Ingegneri. “It is prudent to first select the equipment types that fall within our standard asset model library developed either from first principles or from historical data. The functioning fault models will deliver quick wins. Then, invest in additional instrumentation and connectivity, focusing on data management and governance, gradually increasing the volume of manageable assets by a single individual and reaching a centralised view of all assets and processes.
“This could all be considered theoretical should mining personnel not buy-in to the change and trust the APM models and the people building them. For ABB, we believe this trust comes from domain-specific expertise gained through delivering and servicing complex systems. Many pure software companies have tried and failed, and often the missing link is that industry knowledge.”
Fine-Tune Your Models
The mining industry is beginning to realise the benefits of technology partners knowing what equipment needs to be monitored, when it might need to be maintained, repaired or replaced and increasingly, process and performance correlations that can only ever be revealed through machine learning (ML). Automating diagnostics means another leap in productivity.
One key recommendation is for companies to continuously fine-tune failure mode and effects analysis (FMEA) libraries. Learning to do this properly is a steep learning curve both for SMEs and data scientists, but it considerably improves trust, increases programme outcomes, and captures and stores institutional knowledge.
“It is understood that every mine site is different and so are the mindsets of the people working there – you cannot buy an off-the-shelf APM solution any more than you can buy Industry 4.0 or digital transformation,” concludes Ingegneri. “Implementing an APM 4.0 platform is a journey you take in increments based on business priorities, budget, appetite for transformation and sustainability goals.
“Operations teams across all process industries appear to have a lot to gain from embracing these platforms,” adds Ben Berwick. “People and technology are working together to increase understanding and possibilities. Those who succeed in the race to achieve higher productivity with the next-generation asset performance management will be among the biggest winners.”