Controlling cost and expenses has always been the biggest challenge faced by many maintenance managers. In a world where there is pressure to do more with less, digitalisation is changing the face of preventative maintenance. Sandvik Mining and Rock Technology is one of the OEMs at the forefront of the digital revolution and believes digitalisation offers a different dynamic to preventative maintenance, writes Munesu Shoko.
Traditionally, equipment maintenance has always been viewed as a costly exercise. Today it is increasingly characterised by digital services such as telemetry solutions and data analytics, among others.
This is in line with the digital trend sweeping across the industry globally. Digital developments are progressing rapidly, and what many are calling the Fourth Industrial Revolution (4IR) is starting to take shape, with interconnected machines communicating and able to take decisions and integrate with their environment. Five areas or trends where these opportunities are particularly evident are big data analytics, cloud services and increased mobility, the Internet of Things (IoT) and connectivity; artificial intelligence and augmented reality; and automation and robotics.
Niel McCoy, business line manager Automation at Sandvik Mining and Rock Technology -Southern Africa, says the digital revolution from a preventative maintenance perspective is a big talking point globally, and Sandvik has been an industry leader for providing solutions in this regard.
“We have been at the forefront of preventative maintenance for many years in the industry. We have had performance maintenance contracts running in South Africa for more than 18 years, but this has always been a manual process. Traditionally we utilised a Computerised Maintenance Management System (CMMS) to do manual predictions and forecasts based on trends and experience of people on site,” says McCoy.
He says that process has worked fairly well over the years but the downside is that it never gives you true insights into what’s happening with the equipment. “We have since embarked on a data analytics journey, which is part of our digital offering. We have three legs to our digital strategy, namely connected equipment, autonomous equipment and features, and analytics and process optimisation,” says McCoy.
The first leg of Sandvik’s digital offering is connected equipment. This basically utilises telemetry off the equipment, pushing it into the Cloud and providing basic reporting and insight to the customer.
The third leg is the OptiMine® process optimization package, which includes OptiMine® Analytics, OptiMine® 3D Mine Visualiser, OptiMine® Scheduler, OptiMine® Task Management, OptiMine® Location Tracking and OptiMine® Monitoring.
A key component of the OptiMine® package is Analytics, the next generation of OptiMine® that transforms real-time data into process improvement via predictive insights and actionable dashboards. “Analytics provides insights into equipment health and also predicts potential failures in the short to long term,” explains McCoy.
“Sandvik has established a global pool of information from our connected equipment worldwide. We have data collection units on as much equipment as possible worldwide and this creates a pool of information that we can pull from on a global scale. It gives a raw spectrum of information coming out of the equipment,” says McCoy.
Sandvik has implemented Analytics looking at site-specific conditions. The company pulls a wide range of data from the site, not just the telemetry of the equipment. McCoy reiterates that telemetry is very important because it gives you readings from the equipment itself, but there are other factors that also influence the performance of equipment.
“This includes your maintenance effort and the actions of the operator on the equipment – this has a marked impact on how the equipment performs and when it could potentially fail. Through our Analytics database, we look at these parameters, we process and provide the predictions in terms of potential failures and overall equipment health,” says McCoy.
From an equipment health point of view, McCoy focuses currently on three core areas, namely engines, transmissions and brake systems, as well as the associated components around these three core areas. “That’s our starting point of data analytics. As our intelligence grows and we gather more information, we will start spreading the focus to other systems on the machines,” says McCoy.
McCoy notes that one important thing to remember with data analytics is that it only truly functions when you have proper telemetry off the equipment. By default, it requires equipment to be Controller Area Network (CAN bus) enabled. If equipment doesn’t have CAN bus systems on, you get very limited data in terms of equipment health and performance, and not the full telemetry.
“For example, our intelligent 14-t loader produces over 2 000 CAN signals at any given stage, which you can analyse to inform your maintenance effort. Comparably, with a non-intelligent loader, you can only pull off basic engine information and maybe four or five pressure sensors and gauges of the equipment,” says McCoy.
There are two ways in which Sandvik operates when it comes to data analytics. The original equipment manufacturer (OEM) can provide analytic solutions directly to the customer if they wish to purchase the solution. Alternatively, through its performance contracts, Sandvik can utilise the analytics to better its maintenance practices.
“We have two ways of approaching it. If the customer has owner-based maintenance, they can purchase the OptiMine® software package and through the system they can get all the relevant information that’s necessary to their maintenance effort. Alternatively, we can do it internally,” explains McCoy.
McCoy is of the view that data analytics brings a whole new dimension to maintenance in the long run. He says traditionally maintenance has always been hourly-based. The hourly intervals have been set up based on experience in the industry and consultation with component manufacturers.
Despite the digital approach to maintenance, McCoy is of the view that in the short to medium term, hourly-based maintenance intervals will not fall away. “There is still need to do some form of preventative maintenance and the hourly-based intervals provide for that. This will remain the basis of maintenance in the short to medium term, and what data analytics does is that it gives you the ability to optimise maintenance efforts,” reasons McCoy.
“For example, with data analytics you can see a critical health score on a transmission and then plan immediately to pull the machine off, get the component changed and get the machine up and running as quickly as possible. By doing that, you are preventing a catastrophic failure and also reduce the actual cost of repairs,” says McCoy. He adds that the reasoning behind analytics is to catch failures as soon as they start occurring – that’s the optimal zone where you get the maximum value out of data analytics.
From a local market perspective, McCoy says there has been massive interest in digitalisation, especially with preventative maintenance in mind. He says there has been a fundamental change in mindset in the past six months by most of the mining houses in southern Africa, and Africa at large.
Sandvik currently has a few hundred connected machines in South Africa. Globally, the OEM has thousands of connected machines – a mixture of owner-maintained fleets and machines that Sandvik maintains.
“There is a massive drive for digitalisation in the local market. Most mining houses want to jump onto the digital bandwagon. However, most customers still don’t understand what it entails and our job is to guide them to help them develop their digital strategies,” says McCoy.
McCoy says the benefits of data analytics abound. He says that the first and most important one is having full visibility of the fleet. In the past it was difficult to pull information out of the CMMS system and analyse it. It was basically reliant on having a good planner, or maintenance person with extremely good skills to analyse all the data.
“Now, given the tools you have upfront, you have full visualisation. Depending on how good the network is, you can have close to real time visibility of equipment. That’s the number one benefit for me,” says McCoy.
The second benefit of data analytics when it comes to maintenance, according to McCoy, is that you now have a direct impact on the maintenance effort. “You can coordinate your maintenance effort so much better. When we talk about the maintenance effort, we are not just referring to the swinging of physical spanners, we are talking about the whole process behind it, from planning to ordering of parts and getting the machine back up and running,” he says. “The whole value chain is affected by having this data and managing it effectively. Ultimately, the data starts linking up into your resource planning and this can be added into the whole logistics planning.”
McCoy speaks of two important case studies where data analytics has made a big impact when it comes to preventative maintenance – Barminco in Australia and Finsch diamond mine in South Africa. These are the two trial implementation sites for Sandvik’s analytics product. McCoy says that Sandvik has seen significant success at the two sites thus far.