Operator performance drives the bottom line

With diesel prices recently up on the back of falling global oil prices, Australian quarry producers are likely to keep a vigilant eye on the bottom line. Those who have survived the past few lean years have learnt a valuable lesson: fuel is a real cost in mobile fleets. Furthermore, fuel efficiency is a key indicator of waste, or lack thereof, in one’s operations.

Fuel consumption can easily represent a quarter of the total hourly cost for a typical wheel loader running in a quarry operation. Lower fuel prices shrink this slice. But “lean thinking” teaches us that cost control is a continuous process and, increasingly, a key driver for business sustainability.

Over the past decade, equipment manufacturers have invested a great deal to reduce emissions and improve fuel efficiency. If your machine can do the same job as before while burning less fuel, the savings go direct to the bottom line.

Further, high tech solutions will bring real fuel efficiency gains some day. But technology is not the solution to everything. There is a “low tech” solution that is surprisingly effective and, most importantly, relatively cheap – good operators.

Key to cost reduction

Operators are integral to the success of any job. A good operator can make a tired machine perform; a bad one will soon destroy the best machine. Operator competence directly contributes to the quality of work and ability to get a job done on time. In addition, the operator influences downtime and running costs. Tyre wear and fuel efficiency rely a great deal on the operator.

So train your operators. Who would disagree? Yet it is easy to check the box and forget to make it useful. If the effectiveness of training could be measured, its value would be apparent and hard to overlook. But how do you do it?

{{image2-a:r-w:200}}Fuel consumption is a great proxy for the overall efficiency of machine operation. Everyone understands it. Fuel is personal and tangible; unless you are a rock star, you routinely fill your own car. It’s visible and immediate; machines are filled every day or two. You don’t need months or years to uncover trends. And it has a big impact on the overall cost (as Figure 1 shows). Taken together, this makes it a good metric to track and optimise.

When operator training is scheduled, be sure to measure or sample fuel consumption before and after the training. Experience shows that, when operators receive refresher training on how to run a machine properly, fuel consumption will go down while accomplishing the same work as before. This delta gives a tangible return on investment to any time or money invested in the training.

The US Quarry Academy annually reviews actual case studies where fuel savings in excess of $USD10,000 ($AUD14,078) per machine per year were realised due to operator training, with no loss in productivity. The reasons are various but add up to real money (see Load & Haul – Operator Efficiency below). Some are basic, but it is easy to miss the impact unless put in dollar terms. Do the maths!

Operator variability

Are all operators created equal? Like other professionals, operators strive to do their job in the best manner possible, but there are differences.

As said previously, continuous improvement is vital in all areas of aggregate operations. This is especially true with operator performance. Training must go beyond the basics and assess not only skill but also whether it is progressing in the right direction. What is needed is an ongoing training program based on measurables.

This is particularly important because perception and reality may not always coincide. An operator believed to be doing well may, in fact, have the wrong kind of impact on the performance and cost of your operations.

Recently, Volvo Construction Equipment conducted an in-depth study to quantify variability in operator skills. Seventy-three operators self-described their skill level as novice, average or professional. They then operated identical wheel loaders in three typical quarry applications:

Re-handling crushed stone (stockpiling).
Load and carry crushed stone (as if to a hopper).
Truck loading blasted rock (at the quarry face).

Extensive measurements were taken over several days’ testing. Operator performance was quantified in terms of productivity (tonnes per hour) and fuel efficiency (tonnes per litre). Looking at tonnes per litre is more indicative of operator performance than a simple fuel per hour result.

Observations from the study showed:

There was a high correlation between skill and results. Training that increases competence benefits both production and fuel efficiency.
Skill “self-evaluation” is not very reliable. The study found a significant overlap among all categories. If an operator is deemed good enough, what proof is there? The difference may be dramatic.
There were dramatically different results for novices versus professionals. While this result was expected, it is now quantified. Productivity varied up to 700 per cent among these groups, while fuel efficiency varied up to 200 per cent (see Figure 2).
Average operators had dramatically lower results than professionals. Again, productivity varied up to 300 per cent while fuel efficiency varied up to 150 per cent. This poses the question: can an “average” operator keep up – or does it cost more in fuel (or downtime)?
Among “professionals” only, results varied dramatically. Productivity varied up to 100 per cent, and fuel efficiency varied more than 70 per cent. Even among professionals, there is clearly significant scope for improvement.
Individual operators’ results varied up to ±15 per cent. Again, this should be no surprise but was quantified; we all have good days and bad days!

Some of these conclusions are obvious, but others pose interesting questions. The bottom line is simple: operator competence matters and is something to optimise, like any resource in a quarry.

{{image5-a:r-w:200}}If this were a test of machine performance rather than operator ability, how many site managers would accept a machine that performs half as well as another doing the same job? Much effort goes into squeezing five per cent more efficiency or productivity out of a machine; if similar attention is paid to the operators, the upside is significant.

Every operator is different, that will not change. But managers should realise operator development can yield both quick wins and long-term, continuous improvement.

Technology’s role

The justification is clear for a comprehensive, data-driven approach to operator training, but a larger site or organisation may seem prohibitive in terms of time and resources. Fortunately, simulators are an effective and economic supplement to conventional training methods.

For example, one large infrastructure contractor added simulators to its operator competency program and reported a strong business case compared with a conventional approach.

Quantitative results included a 62 per cent reduction in training costs (including machine use, insurance, lost production, etc), a 20 per cent reduction in training time, a four per cent increase in mechanical availability, a 10 per cent reduction in fuel consumption and a five per cent increase in productivity.

Qualitative results include improved manoeuvrability, positioning and parking, improved bucket fill factor and load distribution, and reduced emissions and energy use during training.

Win-win

Investment in operator competence is a classic win-win; implemented properly, cost savings can be quantified and substantial. At the same time, operators become more professional; by using metrics, they see their relation to the overall efficiency of the worksite and align interests. All together, this results in improved performance, safety and employee satisfaction.

David B Nus is the director of customer solutions (global key accounts management) for Volvo Construction Equipment, USA.

This article originally appeared in the March 2015 issue of Aggregates Manager (US) and reappears in Quarry with kind permission.

LOAD & HAUL – OPERATOR EFFICIENCY

To determine the financial impact of idle time, consider a typical situation for a wheel loader working in the yard at a quarry as shown in the yellow column:

Keep machine five years.
The engine runs 2000 hours per year.
Idle time is 50 per cent, perhaps waiting for work or sitting during lunch and breaks. When the machine is not working, it is idling, so the engine is still running.

Now, what if the operator cuts idle time to 25 per cent, not by working more but simply by shutting the engine down during lunch and breaks? The difference is shown in blue:

500 hours less on the engine over a five-year period.
Fewer scheduled services, saving cost.
Residual, resale, or trade-in value will be based on 7500 hours rather than 10,000.
Whatever warranty existed could cover 33 per cent more calendar days.
Less fuel is burned because the engine runs 500 hours less.

Now, quantify the difference in dollars. It’s significant (example in green column). The owner can either pocket the savings, or perhaps it becomes economic to keep the machine for a sixth year in this scenario.

Note: If idle time is reduced, one result is that the average fuel consumption per hour may actually increase. This is to be expected because the machine has the same working hours but fewer idle hours to bring the average down. Overall, however, it will consume less fuel per day, week or month.