Is your organisation embarking on a digital transformation towards predictive operations, but you don’t know where to start? Then you are not alone, there’s no escaping the fact that the mining and processing industry will, and already has a digital revolution underway. However, before going full steam ahead with a digital transformation, there are some key considerations to think about and implement before taking the plunge which we will go through within this article, such as;
- Understanding your situation better with digital maturity assessment
- Providing a philosophy for enabling predictive operations
- What you need from your technology and systems to enable predictive operations?
Key findings from a study conducted by the World Economic Forum, in 2017 showed that the impact from digital transformation initiatives on the mining and metals industry, its customers, society and the environment, could generate the following value over 10 years.
Improved Safety:
- With around 1,000 lives saved and 44,000 injuries avoided. This equates approximately to a 10% decrease in lives lost and a 20% decrease in injuries in the industry.
Enhanced Environmental Performance:
- A reduction of 610 million tonnes of CO2 emissions, with an estimated value to society and environment of (USD)$30 billion
Increased Revenue / Savings:
- More than (USD)$425 billion of value for the industry, customers, society, and environment. This is the equivalent of 3-4% of industry revenue during the same period.
However, the reality is that the digital transformation challenge keeps many CEOs up at night – and for good reason. Many of these projects fail to deliver results. Front-line staff are not immune to the concerns relating to Digital Transformation either.
Workforces are often faced with receiving insufficiently scoped and planned deployments or being tasked to roll out programs that have been insufficiently aligned to requirements or lack the sponsorship, ownership, and change leadership necessary for success.
The manufacturing sector has already experienced some well-known disappointments from Digital Transformation projects that failed to achieve an adequate return on investment (ROI). In fact, research from McKinsey suggests 70% of transformation initiatives fall short – despite the huge sums dedicated to them. Some organisations can spend billions on a whole of company IoT platform only to discover the company was simply too large to transform all at once, especially without a true vision of what it was trying to achieve.
Yet, the extraction industry faces similar challenges and headwinds that any industry faces. You need to continuously improve operational performance (output, quality, system efficiency, safety, etc.) while simultaneously creating shared value to satisfy the community, shareholders and regulators. However, being afraid of failure isn’t going to cut it at your next performance review. So, what can you do?
Understand your situation better with Mipac’s Digital Maturity Roadmap
There is a combination of ambition, timeline, budget, systems thinking, incremental improvement, operational imperatives, and human factors to consider. Deloitte’s ‘Tracking the Trends 2019: The Top 10 Issues Transforming the Future of Mining’, points out that the need to remain competitive requires operators to ‘push the boundaries on their Digital Transformation, attract truly diverse workforces, and avoid the capital project mistakes of the past.
It also requires them to make technology a strategic priority by acknowledging its role as an enabler across every facet of their business.’ It’s a challenging environment but throwing money and computers at the problem isn’t going to guarantee success. However, ‘understanding where your operation is positioned in its digital maturity journey is the best place to start,’ says Dominic Stoll, Digital Solutions Manager at Mipac. There is no point in applying advanced predictive analytics to data sets that are incomplete or questionable.
By understanding your operations’ digital transformation goals, timeframe and budget, it is possible to develop an actionable roadmap that transitions your operation through the toward predictive operations. Often the first place to start is at the enabling infrastructure level: are you able to accurately measure, monitor, and adjust the critical few parameters that are key to your operation?
In other words, do you have the right instruments, historians, control and information systems in place to detect, alert, interact with and manage variability events?
In Mipac’s experience, any roadmap needs to start with the fundamentals because attempting to transition straight to a predictive operation before the fundamentals are in place will either only distract already stretched resources (e.g. personnel, capital, etc.) or destroy value and is not the ‘silver bullet’ the mining sector hopes for to reverse our multifactor productivity performance declines as reported by McKinsey and Company’s ‘Has global mining productivity reversed course?’
Automation applied to an inefficient operation will magnify the inefficiency.
It is Mipac’s view that most of the latent value available in operations will be unlocked by applying the fundamentals, whereas the benefits obtained from the technologies required to achieve predictive operations, such as machine learning, will only be incremental. After all, the benefits of machine learning will only be realised if the opportunity can be understood, detected, automated and controlled which requires the fundamentals, described above, to be in place.
Mipac’s philosophy for enabling predictive operations
There’s no doubt that over the last few years we have observed an increasing trend of experimentation with predictive solutions in the sector. However, we have unfortunately not observed a correlated trend of successfully obtaining return on investment. In fact, it’s often quite the opposite. That’s why Mipac’s approach to enabling predictive operations and creating value for our clients is as follows:
- Understand the science (e.g. liberation, slurry or slag chemistry, thermodynamics, etc.) and key drivers to ensure the process is positioned within the optimum operating window.
- Engage the workforce and develop their capabilities in the science and key drivers so they are empowered to co-own, co-deliver and sustain the optimisation initiative after the project team disbands.
- Ensure the right instrumentation is in place, well maintained and the communication network architecture is correctly designed and configured to transport data to the control system.
- Configure an integrated control system with automated start/stop sequences that
interact with upstream and downstream plant and assets. - Apply the above principles to optimise the control system using advanced regulatory feedback and feedforward control that is transparent and easily maintainable by site personnel.
- Ensure the right data is being collected, historised and transformed for the purpose of real time insight and foresight.
- Visualise and communicate the insight and foresight to the relevant stakeholders so performance can be monitored and variability events managed and eliminated.
- Create an environment of operational excellence where organisation structure, standardisation, planning, performance tracking and variability management combine for a culture of continuous improvement.
- Focus the above efforts on the system bottleneck to unlock value and incrementally and progressively push the bottleneck downstream.
Only when the above are in place should you consider adding additional predictive layers such as machine learning and only if the return justifies the investment.
How does Mipac’s MPA contribute to enabling predictive operations?
Mipac has specifically designed MPA to complement your existing technology to fill the real time operational system void required to manage variability and enable predictive operations. MPA’s solutions are additive (modular capability, value and pricing based on your requirements), offering stakeholders the ability to interact with and control variability events in real time to maximise productivity through teamwork, structure, insight and foresight.
What MPA is not
It is important not to mistake MPA for the following. MPA is
- Not a historian (e.g. not PI)
- Not an ERP (e.g. not SAP)
- Not a pure reporting tool (e.g. not Power BI)
- Not designed to takeover the role of the control system
Enable predictive operations with Mipac and MPA today
There is no denying it, embarking on a digital transformation journey towards predictive operations may seem rather daunting, however, the benefits are that your operations will become much more sustainable, safer and efficient in the long term for the betterment of all stakeholders. It is important not to throw money into something to make it work but to understand what you want from your operation, what it is capable of now and what are the actionable steps required to get there keeping budget and timeline in mind. In many instances, most of the value will be obtained by implementing the fundamentals:
- Understanding the science
- Engaging the workforce
- Ensuring the appropriate instruments, historians, control and information systems are in place to detect, alert, interact with and manage variability events
- Creating an environment of operational excellence.
We would love to hear from you!
What experiences have you had enabling predictive operations? Let us know which fundamentals you have found that have been captured or are missing in this article?
Is your organisation embarking on a digital transformation towards predictive operations? If so, does it have the fundamentals in place? If not, get in touch to find out more about how Mipac and MPA can help you manage variability and enable predictive operations.
