Stone crushers face tougher working conditions than most construction machines. Moreover, their owners and operators need to count on them performing with power and durability at all times. An engine failure in a mine or quarry will not only disrupt production, but also potentially put operators at risk. So, how can engines be optimized to ensure stone crusher performance and uptime in demanding applications?
Ensuring excellent stone crusher performance and uptime over time
Stone crushers need engines with a correctly specified torque curve and an ability to handle both heavy and light loads effortlessly. The engine needs to run at a high capacity, and do so steadily without losing speed when handling heavy stones and rocks, or high volumes of sand or gravel.
Some operators are used to engines failing, and may even expect having to restart them from time to time. This practice should be a thing of the past. Your work is much too valuable for you to waste time and resources on engines that cannot do the job.
Additionally, your engines should have long service intervals. 250-hour service intervals are relatively common, but that essentially means that those maintenance breaks that disrupt your uptime are relatively common too. This is partly why Volvo Penta’s engines come with 1,000-hour service intervals. Long service intervals allow you to focus on your operations, without frequent interruptions.
Close cooperation contributes to better engines for stone crushers and other heavy machinery
Engine manufacturers and OEMs should ideally work in close cooperation. Doing so will foster solutions that are even better at serving the varying needs of their customers. By getting a better understanding of a particular application or work environment, factors like engine performance, engine maintenance, and fuel consumption, can be improved further.
Attentiveness and innovation is a key combination when it comes to engine optimization and development. All of our Volvo Penta engines can run on HVO 100, for example. This is a much appreciated feature, not least among customers who want to phase out fossil fuels from their production. There is also a growing interest in diesel-electric solutions for stone crushers. It is a very interesting concept, and could be a step towards an increased electromobility portfolio.
A concrete example of stone crusher engine optimization
At Volvo Penta, we work with our customers out in the field (including down in the mines and quarries) to ensure that our engines always perform as they should, whatever the application.
A good example of this involved a quarrying project north of Stockholm, Sweden. One of their stone crushers was in fact overpowered for its workload and application. As a result, we decided to shift from the D8 engine to a D5 engine. We also changed the hydraulic pumps and reduced the rpm by half. This did not in any way affect the stone crusher’s performance or uptime negatively. Instead, we managed to cut fuel consumption by more than a third. Not only is that highly beneficial in terms of significantly reduced total cost of ownership (TCO); it is certainly better for the environment, too. Lowered costs, without any compromise in terms of productivity or quality, in other words.
In-house tests and field tests further improve engine performance and uptime
In order to verify an engine’s durability, reliability and performance, you have to test it and test it and then test it some more. As for our Volvo Penta engines, they undergo in-house testing in test cells, as well as field tests. In these field tests, we install the engines in customers’ machines, and test them in actual operations. This way, we can see how the engines work in – and respond to – certain applications, climates and environments.
This rigorous testing process makes it easier to adjust and fine-tune the engines, and make sure they come with the right torque response, power, emission requirements, etcetera. Our ambition is to test our engines in as many applications as we can, in order to make them the best and most well-adapted engines possible.
Advanced analytics and machine learning take engine optimization to the next level
Advanced analytics can be used to study individual engines and components, as well as stone crushers and other machines in their entirety. The purpose is to get an even better, deeper understanding of how they work. And, occasionally, why something may not work quite as intended.
Through advanced analytics, more specifically machine learning, you can create a virtual machine that receives and processes data from a physical engine, or a stone crusher, for example. The virtual machine learns from this data, gaining insights that would be difficult to get otherwise. This information is highly valuable in terms of product development. Positive features can be improved, and flaws can be detected, fixed and prevented.
Data analytics is already a key part of our engine development projects. The next step is to use more advanced analytics on our data. That is now used as a proof of concept but will be the next key part of product and solution development. For example, we have used advanced analytics on data from our customers’ production engines; for predictive maintenance, and in order to learn more and further improve our engines.
How OEMs benefit from working closely with Volvo Penta
Volvo Penta is currently working with OEMs in order to create state-of-the-art energy propulsion systems. However, it is our belief and experience that we should collaborate even more closely. Doing so allows us to better support OEMs in terms of quality and maintenance, and to continue to meet customers’ requirements as these emerge and develop over time. Moreover, it will put us on a common path towards better sustainability solutions for stone crushers and screeners.
If this topic is of interest to you, I recommend that you also read about how we work together with one of our long-term customers, quarrying and recycling company Dalby Maskin. Feel free to contact andreas.nyman@volvo.com if you want to know more about what we can do to optimize performance and uptime for your machines.