February 2017

Autonomous haulage systems – the business case

  • By R Price MAusIMM, Manager – Projects, Mining Technicians Group Australia

A cost-benefit analysis of an autonomous haulage system that demonstrates the potential for productivity improvements

The mining industry is constantly seeking ways to lower costs and increase efficiency, particularly given that product differentiation activities are limited due to general commodity homogeneity. Heavy industries, including manufacturing and transport, have adopted various technologies such as robotics-based systems to increase efficiency and lower costs. The mining industry has utilised automated systems in fixed plant applications for decades and, in recent years, has begun utilising self-drive vehicles to enhance project economics, safety and other key metrics on mine sites.

This article is presented from the perspective of an industry insider, with insights gleaned from the presently existing five autonomous haulage system (AHS) operations in the Pilbara region of Western Australia. The current implementations of AHSs are all in iron ore operations and total 134 off-highway heavy haul trucks. A sixth implementation exists at the Gabriela Mistrel mine (Codelco) in Chile. Aside from these six active commercial-scale operations, a number of AHS trials with small fleet numbers are currently starting up.

Autonomous haulage systems

There is no industry standard definition of an AHS, and in this article the term refers to the people, technological devices, infrastructure and software that combine to create a system allowing off-highway haul trucks to operate without truck drivers.

The AHS consists of a number of key components:

  • mining trucks fitted with both commercial and proprietary electronic devices
  • software that commands, controls
    and tracks vehicle movements and interactions
  • a communications network with wireless coverage to all areas
  • a team of control room operators and support staff managing the vehicles, devices, software and network.

The mine site is geographically segmented into manned and unmanned fleet operating zones. All vehicles entering the autonomous zone are fitted with GPS transponders that ensure tracking and a safety perimeter or exclusion zone. The trucks receive commands from the control room (located remotely) over the communications network to navigate using waypoints.

Digging units have a location sensor for the trucks to park underneath the bucket appropriately. The trucks can tip into a crushing station, run-of-mine (ROM) pad or waste dump. Staff in the control room can issue commands to trucks that are transmitted over wireless (wi-fi or LTE/4G) networks. Object detection systems (radar and LiDAR) are programmed to stop the truck should anything get in its way.

Autonomous haulage system costs

This article models the costs (in $AUD) and benefits of implementing an AHS at a theoretical medium-scale open pit mining operation to demonstrate the benefit and payback period for the conversion of an existing mine fleet. It is assumed that a fleet of ten trucks, each with a payload capacity of 180 t, is required.

The analysis in this article explains the benefit of an AHS implementation in a single context: converting an existing mining fleet from manned trucks to autonomous (ie retrofitting existing equipment at an operating mine).

The implementation of an AHS includes a number of fixed and variable costs. Fixed costs apply to the site for installation, while variable costs apply according to the workforce and number of vehicles installed with the system.

The total cost to install an AHS is therefore determined by the scale of implementation. The cost areas that
apply include:

  • project planning – representing planning, documentation and regulatory approval
  • AHS truck cost – the cost of the system componentry, installation and commissioning on a per truck basis
  • AHS ancillary equipment – the cost of the GPS location and communication devices on a per vehicle (heavy mining equipment and light vehicle) basis
  • AHS software – the cost to initially license and set-up the user interface
  • AHS software configuration – incorporating fleet management, mine planning and other data into the AHS control software
  • control room – software and communications for vehicle interaction facilities
  • communications upgrades – potential additional infrastructure for a wi-fi or LTE/4G site communications network
  • physical infrastructure – site-based control systems and boom gate trailers
  • implementation services – services that cover change management, operating and emergency procedures and other documentation
  • contingency – proviso costs that may apply to an AHS installation.

The costs in Table 1 represent actual installation costs for a modern medium-scale mine site in an easily accessible area. Additional costs would apply in a mine site that is located in a very remote region. All costs used in this analysis are a centered weighted average and would realistically be ranged based.

Mobile equipment costs (variable)

The truck component costs are inclusive of the custom and commercial components of an AHS, including LiDAR, multiple radars, an inertial monitoring unit, vehicle controls (steering, braking, throttle), control computers, high-precision GPS, cameras and communications devices. The trucks require several days of installation activity, testing and commissioning. These costs are not included here as they are indirect costs and not cash costs. The ancillary vehicle cost includes the required tracking and communications equipment, and although dig units require additional sensory devices for truck parking proximity, these costs are not materially extra. The ancillary equipment list for this hypothetical mine includes three digging units, two track dozers, one front end loader, one grader, one water cart, one blast products wagon, one service truck and four light vehicles.

The retrofitting of AHS equipment is applicable to the majority of mine site equipment types, but can also vary based on the age of the fleet. Heavy machinery manufactured after 2000 is usually commanded by some form of electronic messaging system and is thus somewhat technically easier to automate than older machinery.

Fixed equipment costs

The control room costs are for commercially available computers, screens, communications devices and furniture. The communications network is dependent on the terrain and layout at the mine site, and upgrades could potentially cost more than the modelled figure used in this article.

Physical infrastructure includes reporting screens used in crew rooms and additional interactive devices used in fieldwork and boom gate trailers that act as physical barriers to site entry in autonomous operating zones.

Cost summary

The cost estimate assumes that a modern mine site with offices, vehicle workshop and tooling, computers, internet access, communications systems, power and other basic infrastructure already exists and these costs will not be borne by an AHS. Reasonable internal corporate costs from internal company personnel resources are included, but these could be considerably higher.

The key cost element not modelled in this simplified analysis is the ramp-up period. It is a relatively straightforward process to render a vehicle autonomous and then have that vehicle undertake basic tasking. However, it is a more complicated to apply vehicle autonomy to a fleet of units and then safely integrate it with human operators. While the existing AHS products are mature, the ramp-up period still applies as the people and processes will take some time to adjust to the new normal.

In the author’s experience, this ramp-up period for the trucks to operate on par with manned equipment is likely to take six to 12 months.

Assuming that the mine site has ten trucks and 14 ancillary/support vehicles engaged in the AHS, the total estimated cost to undertake the exercise of converting the haulage fleet for this example is approximately A$18.5 million.

Autonomous haulage system benefits

The implementation of an AHS is principally a capital cost to operating cost trade-off analysis, with incremental additional benefits in safety, productivity, tyre life, maintenance, personnel management and environmental stewardship.

Modelled benefits

All six existing commercial implementations of an AHS have been deployed at new operations. The opportunity to retrofit existing haul trucks at operating mines is likely to have a considerable financial benefit to projects that have existing trucking fleets.

Production benefit

The benefits have been modelled based on operational experience at AHS sites. The principal benefit is increased production due to increased equipment utilisation. Typically, haul trucks in an open pit mine are scheduled for approximately 5500 to 6000 engine hours per year. AHS sites achieve significantly higher utilisations, resulting in higher annual engine hours. AHS sites are known to schedule up to 7000 hours per year, an increase of around 16-18 per cent. It is therefore a conservative assumption to model an annual increased utilisation metric of 1000 hours.

A simplified benefit of an increase in operating hours of 1000 hours per year for a single haul truck is outlined below, and it is noted that this increase in operating hours modelled is congruent with actual annual hour increases from mine sites that are currently operating an AHS (Rio Tinto, 2015; Fortescue Metals Group, 2015).

The following applies to the calculation of the production benefit:

  • the production time gain is 1000 hours per year per truck
  • average cycle time is 30 minutes (ie 2000 cycles per year)
  • the truck payload is 180 t
  • the strip ratio is 3:1 (ie one in four truck loads is ore)
  • ore has a value per tonne of A$25.

The incremental additional trucked ore per annum is 900 000 t, with an incremental annual production benefit
of A$22.5 million. This is a revenue benefit that is discussed contextually later in this article.

Wage impact benefit

Adopting autonomous haulage will impact the production workforce wage bill. The wage change calculation assumes that the mine site:

  • operates a two-weeks-on and one-week-off roster
  • each truck utilises 3.5 truck drivers (per the roster)
  • upon changing to an AHS, there would be two staff in the control room per shift (with a spare staff member to cross crews)
  • the site would have two field staff per shift (with an additional role to cross crews)
  • truck operators have an all-in cost of $150 000 per annum, while control room and technicians have an all-in cost of $180 000 per annum (after Bellamy and Pravica, 2010).

The modelled net wage reduction in the adoption of an AHS is A$2.73 million per annum.

Tyre life benefit

Mine sites that utilise an AHS typically achieve significantly longer tyre life. Tyres typically last approximately 5000 hours at manned fleet mining operations, while autonomous mining operations can budget on a 7500-hour tyre life. The tyre life benefit is derived from several critical changes at sites that utilise an AHS, including that the truck operates only on a programmed basis and incidents such as vehicle collision, direct impacts, tyre sidewall punctures and improper use of the truck occur less frequently and with less associated impact.

The quantifiable modelled benefit for tyre life is also calculated for the implementation of an AHS. The parameters include:

  • manned fleet tyre budget of 5000 hours versus AHS fleet tyre budget of 7500 hours
  • tyre cost of A$40 000 each
  • six tyres per truck across the fleet of ten trucks.
  • The modelled annual benefit is A$1.2 million.

Non-quantified benefits

The implementation of an AHS includes benefits that are not modelled in production factors or wage reduction.

The quest for zero harm in the workplace is never-ending, and autonomous vehicles are expected to play a significant role in improving occupational health and safety in the future. Trucks that operate autonomously can make mines safer by removing people from repetitive front-line tasking.

It is anticipated that autonomous trucks will have significant maintenance benefits. The trucks typically experience higher costs in brakes, due to the service brake being utilised in every event of obstacle detection, and in tray maintenance due to less scrutiny in loading practices. However, the trucks have considerably less maintenance costs associated with the running gear and truck frame. The running gear (mechanical) does not experience the over-revving or misuse that is sometimes seen on operator-driven trucks. The truck frame does not experience collisions or impact damage. These benefits will crystallise over the years once AHS trucks complete a full life cycle. At present, AHS trucks have been in continuous operations for around nine years, which is not yet a full life cycle of an off-highway heavy haul truck.

There is also an apparent increase in motivation across the general workforce at operations that utilise an AHS. The lack of truck drivers means that staff are trained on more interactive equipment (digging units, dozers, loaders, graders, water carts and specialist equipment) and are not waiting to progress from the haulage fleet and be promoted to working in more sophisticated roles.

Discussion

Utility of increased production

A number of key issues exist that impact cost-benefit analysis work undertaken by mine operators on the potential implementation of automation. A critical question to answer is whether the mine operator will make use of the additional tonnes or instead retire underutilised equipment. In the example modelled in this article, the trucks produce an extra 15 per cent in tonnage. If the process plant was limited in size and these tonnes were stockpiled, the net present value (NPV) of the AHS may not be realised. The actual benefit of an AHS implementation in this situation would be to retire an operating truck (or sell that unit of equipment) and lower the cost per tonne for a similar number of delivered tonnes. The delivered tonnage would fall, but the operating costs to deliver those tonnes would also fall (by one tenth in the example used in this article) if nine trucks did the work of ten trucks and a single vehicle was withdrawn. In the instance that a vehicle is withdrawn, it may be able to offset the capital cost of the AHS installation through sale or redeployment.

Mine life

The mine life of the operation is another critical consideration. If an autonomous fleet moves more tonnes than a manned fleet due to significantly increased utilisations, it brings planned earthmoving schedules forward. Given the time value of money, this could be beneficial. However, if this compresses an already short timeframe (such as a five-year mine life in total), bringing forward the mine closure may not lead to additional NPV over the life of the mine. In this instance, the additional production benefit serves to front-end cash flow, but reduces the mine life accordingly. The production benefit calculated in this methodology is not an additional benefit and lies within the mine production profile regardless.

Application

Analysis has been completed on how the business case of AHS implementations is considered to scale, given that a component of the cost structure is a mix of fixed and variable. Results indicate that cut-offs for the application are presently in excess of 12 Mt/a of total earthmoving. All of the six current implementations of an AHS are based in mines that exceed this amount of total material moved. Truck count cut-off thresholds vary by payload capacity, but a minimum of six to eight trucks is generally required. In its present form, an AHS is therefore not likely to be applicable to all mines as scale is a key factor.

The orebody type does not appear to be a significant factor, and it is likely that some elements of geometry are important for the presently deployed AHSs. These include open pit crests to allow GPS data signal and site communications and open haul roads with wide haul road radii.

If a mine considering the implementation of an AHS is a ‘fly in, fly out’ (FIFO) operation, the impact of having less staff at the operation carries with it the significant on-cost of transport, accommodation and associated site services (power, water, food and pastoral care) for such staff. Additional value benefit exists if the operation has a FIFO work roster. All of the five existing AHS sites in the Pilbara employ a FIFO workforce.

Potential issues for mitigation

The implementation of an AHS has several risks that can be planned for and mitigated during the early project phases.

Haul road maintenance

The site will require an increased focus on haul road maintenance. This increased focus does not necessarily relate to increased cost, but haul roads are more important at an AHS operation than a manned one because the AHS safety system will detect oversize rocks as stationary objects and stop the truck if the roads are not graded to a high standard.

Operator training

An AHS-operated site does not benefit from bringing talent ‘up the ranks’ from a truck driver to an all-round operator. Crew members will commence on other heavy equipment because personnel are not required for the sole role of truck operator. As operators of digging units, bulldozers, loaders and graders will not be promoted into these positions from the position of truck driver, a safety and training focus on site must be paramount. From experience as an insider at AHS sites in Western Australia, there is no overall significant increase in training cost or delivery. Although training is increased, the costs remain the same as they are applied to a smaller pool of individuals given the lack of truck operators. An AHS utilises modern technology and requires an increased reliance on communication networks and higher-skilled staff members. Although the technologies that deploy an AHS are well known, the technical skills to operate and maintain it are usually of a different background to truck operators. Therefore, there is the potential for increased operational issues during the transition phase, but the benefits appear to outweigh the risks and potential negative impacts.

Conclusions

The current operators of autonomous vehicles achieve a lower unit cost due to increased productivity and lower maintenance costs and enjoy a better tyre-wear profile.

The cost to implement an AHS across a fleet of ten trucks has been modelled at a capital cost of A$18.5 million. This generates an annual employment cost saving of A$2.7 million, an annual tyre value increase of A$1.2 million and a production value increase of A$22.5 million.

This is a simplified analysis of the cost and benefits associated with operating an AHS. It demonstrates that the benefit from an increase in production is 85 per cent of the annual benefit, while the wage reduction is ten per cent of the benefit and tyre life increases by less than five per cent. These calculations validate that the economic rationale for automating trucks is primarily related to increasing production, which lowers the delivered cost per tonne, and is not solely related to the removal of truck operators.

At present, an AHS requires cut-off thresholds that limit its application to large open pit mines.

The author of this article concludes that AHS technology will become mainstream over the next decade as the benefits outweigh the costs by a factor that is generous enough to warrant attention.

At present, the apparent complexity, capital constraint (due to market forces) and a lack of general awareness serves to limit the uptake of the technology.

Acknowledgements

Mining Technicians Group Australia acknowledges its clients’ innovative strategy and investment in AHSs and acknowledges the assistance of Jack Wellington GAusIMM in providing research for this paper.

References

Bellamy D and Pravica L, 2010. Assessing the impact of driverless haul trucks in Australian surface mining, Resources Policy, 36(2):149–158.

Fortescue Metals Group, 2015. Investor briefing [online], 27 October. Available from: stocknessmonster.com/news-item?S=FMG&E=ASX&N=739263

Rio Tinto, 2015. 2015 annual report [online]. Available from: stocknessmonster.com/news-item?S=RIO&E=ASX&N=439742

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