Many mining companies are seeking to address their productivity gap by introducing autonomous mining fleets. The variable results highlight that operating an autonomous mining fleet is not as easy as it seems.
The mining industry is suffering from falling commodity prices, aging mines, increasing strip ratios, longer haul distances and tightening cash flows. Inevitably, this raises the focus on productivity – getting more from the assets, spending less on them and running them longer.
A strategy many mining companies are pursuing is using the benefits of autonomous trucks to effectively ‘buy’ productivity. Autonomous trucks have been trialled and operated around the world since the late 1990s.
Rio Tinto was the first mover on a large scale, operating under their Mine of the FutureTM technology banner. Rio Tinto started in-pit trials in late 2008, and moved to large-scale deployment in 2011. FMG and BHP have both conducted trials, with FMG moving to large-scale deployment in 2014.
Rio Tinto, FMG and BHP have publicly declared that they are expanding their autonomous truck programs.
Technically, autonomous trucks should quickly provide a significant return through:
- improved safety
- reduced operator numbers
- reduced variability.
However, in practice, autonomous truck fleets have produced surprisingly variable results. Clearly there is more to deploying autonomous trucks than ‘plug-and-play’.
Perhaps Bill Gates’ observations on automation also apply to autonomous trucks:
The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.
How autonomous trucks really work
It may seem obvious, but autonomous trucks are just machines. They are wholly controlled by computers and their decisions are determined by the software program. They are as fallible as the people who coded the software, and they are no smarter than your laptop.
Further, contrary to widespread belief, the current autonomous trucks do not even use basic ‘artificial intelligence’.
The trucks are primarily controlled via GPS and ‘dead reckoning’ navigation, with various forms of object detection to ensure they will not run into anything – including other machines, objects or humans.
Autonomous truck performance profiles are a little different from traditional trucks in that they are:
- more precise than traditional trucks in the loading and dumping zones – but typically slower
- more precise on the haul routes – they operate exactly to the manufacturer’s parameters so, through corners and on ramps, the speed is always correct, which delivers reduced tyre wear and no overspeed events
- highly dependent on the skills of the loading unit operator to ensure consistent operation of the system – the autonomous trucks are all 100 per cent predictable, whereas with a staffed operation each truck driver introduces a variable.
Typically, an autonomous truck will not match the cycle time that a skilled operator can deliver. But the cycle time will be better than an unskilled operator, and it will be 100 per cent predictable, with no variances or errors. The currently operating autonomous truck fleets have average cycle times equivalent to traditional trucks, but there is enormous potential upside.
Figure 1 demonstrates a typical hour-by-hour utilisation curve for traditional and autonomous fleets. For autonomous fleets, variability is mainly influenced by fleet availability and the activities of the loading unit operator. Traditional fleets have the added variabilities of:
- the truck operators
- managing shift changes and breaks
- the impacts of surging and queuing.
- The consistency and efficiency of an autonomous fleet can be exceptional. This is the true business benefit.
What is the business case?
Autonomous trucks deliver:
- Improved safety – significant reduction in pit vehicle-to-vehicle interactions and (obviously) elimination of muscular-skeletal and sprain/strain injuries for truck drivers.
- Reduced staffing requirements – all truck haul driver roles are eliminated, while there are a handful of additional supervision, technical and control roles. The compound effects are a reduction to infrastructure, transport, training and support needs, delivering substantial cost reductions, particularly for remote areas.
- Reduced truck requirements – with the increased utilisation of autonomous trucks, a mine can either purchase or use less trucks (capital savings), or move more tonnes with the same fleet (production increase).
- Reduced operating costs – reduced fuel consumption, reduced maintenance costs and increased tyre life are all documented benefits from autonomous trucks. But the magnitude of these benefits and capacity to achieve them are subject to debate.
- Improved consistency and reduced complexity – the introduction of machine control has the effect of transitioning the mining environment from managing discrete components (people) to managing a continuous process. This, and significantly fewer people in the mine, provides much greater consistency and significantly reduced management complexity.
The commercial models for the two major autonomous truck suppliers are significantly different. The base cost structures are quite distinct, and the suppliers tailor their commercial agreements by customer, factoring in existing relationships and agreements, and potential for future business. In short, the commercial arrangements are negotiable and can be flexible.
Why do we hear about variable results from autonomous trucks?
An autonomous truck fleet is an operating tool, not a technical solution. Referring to the quote from Bill Gates, automation magnifies both good operations and bad operations.
The key to getting a great result from autonomous fleets is to have a well-operated site.
Autonomous fleets will not compensate for poor operations and they cannot be used to ‘buy’ good operations.
Getting expected autonomous fleet results often requires a business transformation – a social and cultural change along with the technical change. The technical component is relatively easy compared with the cultural change.
The mine culture will determine how the operation uses the autonomous trucks and gets productivity from them. An operation may choose to use the trucks as an excuse for mediocre performance, or they may embrace the technology and use it to excel. The mine leadership team that chooses the performance they expect from their autonomous system will deliver outstanding success.
What about the people?
Autonomous trucks introduce a different skillset to the business. Some roles (notably haul truck drivers) will no longer be required, and new roles will be created. An exciting prospect is that the new roles will require a different level of thinking – non-routine and with increased levels of ingenuity.
Remaining roles will change
Many roles in mining are either entirely routine, or have a high proportion of repetitive tasks. The role of the truck driver is an example of a highly-repetitive task that is likely better suited to a machine. The remaining roles have reduced routine work. For example, mine planners and engineers will work with models and simulations and apply a higher level of thinking to anticipate and plan the truck activity.
New roles will be required
People with specialist skills are required to manage the autonomous trucks at a systemic level. These skills include day-to-day management, advanced system development and system integration.
A critical feature of the autonomous trucks is that they require people to manage their activities in the pit, ie ‘be
the eyes of the trucks’. This requires not only a comprehensive technical understanding of how the autonomous system operates, but extensive practical mining experience and skills.
So, while autonomous trucks remove the role of the haul truck operator, there is a greater need for first-class mining professionals.
To complement the skilled mining professionals, new roles in an autonomous mine include highly-skilled technicians, mining engineers and computer/mechatronic engineers.
Autonomous operation also introduces changes for the roles of:
- the leaders, particularly front-line – they will now be leading a process rather than people
- the ancillary fleet operators – who will be learning to manage the human-to-machine interface
- the mining engineers – who are thinking for the mine and trucks
- trainers – the training volume increases exponentially during the initial stages, and quality of training is critical
- remaining machine operators – the work complexity for these workers changes, and it is necessary for them to fully understand what the autonomous system expects from them.
If the people operating the system are not supportive and fluent with the system (particularly the supervisors),
the full benefits of operating a pit autonomously will not be realised.
Autonomous truck deployment cannot be successfully executed without the overt support of the senior leaders. In some respects, pursuing autonomous operations requires a ‘leap of faith’ for the site leaders, particularly as the number of truck drivers reduces to the point where, if there is a system problem, there are not enough people to operate the trucks.
A drawback of autonomous systems is that a system problem can affect the whole fleet. When this occurs, it takes leadership courage and commitment to ‘stay the course’ and allow the technical people to resolve the problem.
Communicating the change
The introduction of autonomous trucks presents a major challenge to the business, primarily due to people’s inherent resistance to change, fear of the unknown and the fact that there will be fewer employees. Some key learnings from successful autonomous truck deployments are:
- the affected people need to be engaged very early and frequently
- thorough communication is required – ideally deliberate messaging that targets the affected people
- delivery of the message must be authentic – it must come from leaders whom people trust.
Deployment of autonomous fleets will likely include a structured business transformation process. This is a change management approach that includes a deliberate cultural change – understanding the existing culture and being deliberate about the desired culture; a true step-change for the business.
The business transformation process (not project) must be led by credible leaders, not technical experts or project managers.
The two major autonomous truck systems are technically different but operationally similar. The choice of which system to use will be largely determined by which truck fleet is being used at the operation (or being evaluated), and the commercial arrangements able to be negotiated with the truck/system supplier.
Both systems are well proven and have delivered excellent results. Both suppliers have successfully supported multiple deployments, are well-resourced and have highly competent teams.
Unfortunately, both systems also have examples of less-than-expected performance.
The performance of an autonomous mining system will be influenced more by the operation of the site than the technical functionality of the system.
What can go wrong?
With the current state of autonomous deployment and the competency of the suppliers, it is unlikely that an autonomous deployment will ‘fail’. But there are many examples where the autonomous fleets do not meet expectations, and some that have not achieved expected performance for several years. Figure 2 illustrates several scenarios that have been seen with autonomous deployments. Mine A demonstrates a ramp-up to full capacity in less than six months – this is achievable. Mine B and Mine C demonstrate a slow ramp-up and, potentially, unmet expectations for years – these are not isolated examples.
Obviously, there is massive economic benefit (and reduced business interruption) through reaching full capacity in months rather than years. Rapid deployment and rapid ramp-up to full capacity is completely achievable if the mine is genuinely operating well and a proven deployment approach is used.
What else needs to be considered?
Autonomous truck deployment affects the whole mining process. The following points also need to be considered when an operation is making the switch to autonomy:
- Mine planning – the trucks only operate to a pre-established plan. There is no room for a ‘pit boss’ in an autonomous mine.
- Wireless communications – the wireless system must be in top shape.
- Pit standards – the condition of the roads and intersections is paramount for autonomous trucks. Autonomous trucks will not ‘complain’ about poor roads.
- Operating practices – the trucks operate strictly according to manufacturer specifications.
- Maintenance interface – in an autonomous mine, maintenance has the biggest variable impact on truck performance, in terms of both planned and unplanned downtime.
- Mine entry management – controlling the access to an autonomous mine is critical for optimising performance of the trucks. This primarily involves minimising the interaction between traditional and autonomous machines.
- Functional safety – given that an autonomous system is programmed by people, it has the potential to contain programming errors. The systems (firmware and hardware) that the program operates on also have the potential for malfunction. This needs to be considered with the design and specifications.
- Human-machine interface – in the autonomous environment, there will be times when people will need to interact with machines. The practical and social effects of this interaction need to be considered, along with design of roles to suit the evolving environment.
What they didn’t tell you about the current autonomous truck fleets is:
- they are not ‘plug-and-play’
- they are not really ‘smart’
- it is very difficult to get them to deliver the expected results
- they require the site to be well-operated and they require first-class mining professionals to manage them
- they will not compensate for poor operations and cannot be used to ‘buy’ good operations.
Many companies are operating autonomous trucks and many more are currently planning to use them. To deliver full value, autonomous trucks require deliberate and
Fortunately, there are examples of autonomous truck fleets delivering exceptional performance and value for the company. These were achieved with good base operations, a structured deployment approach, a business-transformation process and leadership commitment.
In summary, exceptional performance from autonomous truck fleets is achievable. There are proven tactics that will deliver rapid deployment, and sustainable performance that far exceeds that of traditionally staffed fleets.
Feature image: Gary Whitton/Shutterstock.com.