Transportation is changing. And so is maintenance.
Today’s world is extremely competitive. Companies face new competitors and a constant threat from industry players with roots in other regions, as almost every field is becoming part of a global market. Competitiveness is no longer just a determining factor for profitability, it also defines which businesses survive and thrive, as well as the ones that won’t ́t be able to keep up the relentless pace of the modern world.
New technologies and artificial intelligence have opened a window of opportunity for a new maintenance approach that is far more efficient and effective than the traditional scheduled and time or mileage-based maintenance. We call it Predictive Intelligence and it leads the way towards Automated Maintenance.
It leverages artificial intelligence and allows operators not to guess or estimate, but rather know, based on factual data, what’s wrong, which components need to be replaced, when to act, what stock to keep, and how to avoid disruptions and eliminate downtime.
The demanding nature of a transport operation, usually running non-stop around the clock, inherently drives maintenance to be one of the major budget line items. Consequently, these improvements in the operational efficiency of maintenance have the ability to drive immediate upside on companies’ competitiveness and bottom line.
Nevertheless, change is not easy. It never is. We have been fortunate enough to have supported some of the most innovative transport operators embracing it. In this paper we will be exploring our learnings from industry front-runners – starting with the five most common misconceptions about leveraging artificial intelligence to automate maintenance.
MISCONCEPTION 1: A new technology means disruption
Until very recently there were basically two options for fleet operators in terms of chosen approach to maintenance. It was either reactive, taking measures after a vehicle breaks down, or preventive, building on the common knowledge and statistics to estimate how long components and consumables would last, and replacing them on the basis of scheduled mileage or using a time-based approach.
The preventive approach is obviously already an enhancement over the reactive, and while self-employed truck owners may still take mostly the reactive road, it continuously drives high default rates, it is not sustainable, and competitive businesses can no longer afford it.
Information systems were critical in the transition from reactive to preventive practices providing the tools for fleets to control the timelines and mileage records necessary for its implementation. Today those tools are the industry standard for good practices.
Nevertheless, technological breakthroughs are rapidly overtaken by later developments, leaving all new inventions outdated in a matter of years. And technological breakthroughs have now caught up with preventive maintenance.
By leveraging Artificial Intelligence, a new predictive and factual data approach that ultimately enables a fully automated maintenance is already taking place as the standard best practice.The reason for this is that with the legacy approach of preventive maintenance you always end up replacing components either too soon or too late, creating inefficiencies. And acting too late means downtime, thus creating disruption in operations.
This is a rather unique situation in which the new approach is the one avoiding disruption, and not the other way around. In fact, a new artificial intelligence based predictive approach does not replace (disrupt) the previous approach. It builds on top of it. Using factual data and relying on mathematics, physics and overall science to know exactly how to act, doesn’t mean one will act without a schedule or a plan.
It means those plans and schedules become dynamic and automated, and that your engineers are not caught up by surprise. They know what is happening, what actions they need to take, and when to take them. The result is that your vehicles are kept on the road, and goods and people are delivered from point A to point B.
No surprises, no disruptions. That is the future ahead of us, and the businesses embracing it are the ones that will outperform its competitors and lead the markets of tomorrow.
MISCONCEPTION 2: I need an analyst or a team looking at the data
A common misconception is that because artificial intelligence uses large volumes of data, you need to have people available to look at all the data and make sense of it, so that you can have informed decisions.
Contrariwise, the primary reason for using artificial intelligence is to automate this process, and avoid having people allocated to the manual and repetitive work of data analysis. The principle is that there is nothing humans cannot solve. Enough people looking into a problem can solve it, regardless of the complexity. Humans are great at creativity, but computers are much more efficient at repetitive tasks.
Looking through multidimensional and large volumes of data collected from vehicles is one of those repetitive tasks, and mimicking the human brain to detect patterns and anomalies, together with enough computational power, enables an AI based computer program to run the analysis and give you what you need – actionable data.
In practical terms, analysis are automatically performed and you are provided with reports of detected anomalies and faults, as well as with the context to interpret them.For example in your fleet of 100 vehicles operating in region A, there is 1 vehicle with a cylinder compression issue, 3 with starter batteries that need to be replaced, “x” with engine power loss problems, and so on.
Each individual problem then has additional information that supports and provides context to the person receiving the report, so he or she can understand why the automated analysis generated each suggestion.
The goal is for you not to have the need to hire and allocate more people to new tasks, but rather to leverage your existing team to reach new levels of productivity, by giving them access to information they did not have before.
MISCONCEPTION 3: I am not ready to make operational changes
Using AI to advance maintenance practices does not require changes to the day-to-day responsibilities of your team.
Their roles will continue to be centered in the overall control of the fleet’s condition, on the scheduling of work orders, and the execution of the repairs. The value Stratio brings lies on the new information and insights, not previously available to the people making these decisions and executing the work, shedding light over areas that were blind to your organisation.
Whilst maintenance is still scheduled, and work orders and repairs still performed, companies now have the ability to rely on a product that captures large volumes of data that were not being captured and stored before, and to run complex calculations in real-time, to provide suggested actions, allowing for more informed decisions to be taken sooner, faster and with little or no risk.
That is why, in the case of predictive and automated maintenance, disruption is not brought by the introduction of a new technology, and also why we have seen such fast and effective adoption from customers once they experience change. Once teams start working better, and add more value to the business, it is difficult to even imagine going back.
MISCONCEPTION 4: Technology saves me money
It is important to remember that technology is simply a means to an end.
It is not artificial intelligence in itself that improves your efficiency and bottom line. Only you and your team’s actions have the ability to do that.
This is why we give so much importance to building trust in each report and prediction.
By giving you all the metrics and key performance indicators, together with the suggested actions, you can better understand why we are recommending a repair or a replacement.
We know that once you trust the information we are providing, you will act. And by acting, you will give purpose to our technology. And as in any business, your success determines ours.
MISCONCEPTION 5: Avoiding vendor lock-in
If you are unable to use another vendor without substantial switching costs, you are in a vendor lock-in situation.
We do not believe in vendor lock-in. We believe in performance and pace as the criteria for a successful and long term relationship with our customers. The same performance and pace are of the essence for us to accomplish our mission to support the industry frontrunners driving a zero downtime future. That is why we provide our customers full ownership over the data being acquired from the vehicles.
We rely on our competitiveness, on our ability to do better research, to build better machine learning and artificial intelligence models, great features and better products for our customers to succeed. Hence, if our customers believe that we are no longer the best provider, they have full freedom to move all of their data elsewhere.
For the same reasons, we support integration of Stratio’s products with other existing products and services our customers use, optimizing their previous investments to avoid disruption of tailor made processes already in place.
Why move now?
As new technologies emerge, so do opportunities for doing things in a better way. No organization can remain successful without being more efficient than its competitors, or stand to be at a disadvantage. Stratio allows for a predictive and automated maintenance approach that is far more efficient and effective than the traditional scheduled and time or mileage-based maintenance.
When technology changes, markets get redesigned. In that process some companies adopt change earlier than this and build competitive gaps. In an extremely competitive field those are the defining factors determining success or failure. Delaying the adoption of a new technology comes at the cost of giving your competitors time to build an advantage over your business.
Eliminating downtime is also beyond just saving costs. It is about ensuring that people and goods move without disruption, that the purpose of your business is achieved to its full extent, and that your happy customers leverage all the possibilities of a predictable and reliable tomorrow.
If you’re interested in learning more about how we can support you and in our view for the future of automotive maintenance, check our website and book your demo.
- 5 Misconceptions about the future of automotive maintenance - February 2, 2021