Electronic systems generate gigabytes of data that are increasingly being used to improve efficiency at many levels, from field operations to maintenance and even vehicle design. A range of equipment and service providers continue to find new ways to use vehicle information to further enhance productivity. Telematic systems link vehicles to the cloud, giving data centers huge files that can be mined.
System designers are helping customers get data from more electronic control units (ECUs) and sensors, and they’re building ecosystems of partners that can help customers turn this data into meaningful information. “We try to take away the pain points customers may face,” said Jose Ogara, TTControl’s senior product manager for smart IoT. “We have knowledge of the whole vehicle architecture, connecting to our devices or other controllers and sensors. We work with several partners that have expertise in different areas.”
Design and testing programs are also being transformed by the wealth of data. Design tool providers are among those who are helping engineers manage the huge volumes of data needed to create safety and autonomous systems. “Testing and validating automated-driving systems require huge amounts of test data to be processed,” said Martin Schleicher, executive vice president, business management at Elektrobit. “For this, we offer the EB Assist Test Lab data management platform. This cloud-based platform makes data accessible and usable to worldwide distributed development teams and furthermore enables data socialization beyond department or even company borders.”
Partnering to maximize data
Maximizing this data for a range of different design steps requires using several tools and working with partners who have many different skill sets. Companies are forging partnerships that let different collaborators work closely to ensure that all tools and processes mesh together well. The complexity of these ecosystems is underscored by the links related to cloud services alone. Volvo Trucks works closely with telematics provider Geotab. Danfoss uses Apache Cassandra database for storage, deploying data in the Microsoft Azure cloud in a Kubernetes cluster. Elektrobit’s partners include Amazon Web Services and Zonar, a sister company within Continental.
OEMs play a central role in making all these connections work together efficiently. “Some of our partners include familiar names in the tech and communications industry, including Microsoft, Amazon, and AT&T,” said Fred Rio, digital and technology product manager, Caterpillar Construction Industries. “While we leverage industry partners to host our cloud, the validation, security, normalization and processing of the data is done by our proprietary algorithms.”
The number of partners that work together to store and analyze data is matched by the disparity of customers who can use this data to improve operations. The vast amounts of available data in the cloud means different things to different groups. Many stakeholder groups can benefit from the collected data.
“A machine operator, for example, could use the data to optimize machine use, achieving better productivity and greater efficiency,” said Ivan Teplyakov, development manager of connected solutions at Danfoss Power Solutions. “A fleet manager could use maintenance data to ensure reliability and reduce downtime throughout the fleet. And an OEM could use productivity, maintenance and use data for engineering evaluations, ensuring optimal design specification.”
The ability to update software remotely is another significant advance enabled by connectivity and big data. Equipment makers can analyze field data to spot issues that can be fixed using software. When that occurs, operators and owners can receive patches over the air. “The data collected from Remote Diagnostics helps our engineers to stay ahead of issues related to the powertrain by releasing the appropriate software that will help prevent issues from appearing in the first place,” said Ash Makki, product marketing manager, Volvo Trucks North America.
OEMs can also use big data to help them tweak vehicles in the field as well as improving products that are still being designed. The ability to monitor operator interactions with the human-machine interface (HMI) can help engineers see how various user segments interact with the machine. That information can be used to modify the HMI so operations can be performed more efficiently.
“Our customers get great value and see how their machines are being used,” Ogara said. “We also work with customers to get information on usage, seeing usage patterns on our display, seeing what functions are used more or less. Once we see how they’re being used, we can customize displays to ensure that users get to the right information with fewer clicks.”
Reductions in downtime are one of the biggest benefits of collecting and analyzing data. OEMs are employing numerous techniques that let them quickly analyze fault codes to determine what’s wrong with a vehicle and prepare everything needed for repairs. In the future, engineers will be able to predict failures before they occur. In the near term, a growing number of companies are improving uptime by updating software remotely.
Software plays a central role in vehicle productivity, so keeping it up to date has become an important aspect of equipment maintenance. Companies like Volvo are offering over-the-air updates so maintenance personnel don’t need to access vehicles. Eliminating trips to repair centers provides huge increases in vehicle availability.
“Remote Programming software and parameter updates are some of our latest cutting-edge telematics services that offer our customers a tremendous increase in uptime,” Makki said. “On average we are saving 2.3 days of downtime with software and parameter updates done remotely, over-the-air. Our customers are able to maintain a healthy fleet updated with the latest software based on the data collected and analyzed by our experts.”
Product developers hope to expand the benefits of software updates by predicting problems before failures occur. The time savings associated with software updates can be augmented by analyzing parameters that foretell pending failures. Predictive diagnostics has been discussed for years, but creating an effective strategy requires accurate analysis of data that comes before breakdowns. “Predictive analytics is where things are headed,” Ogara said. “Solutions out there today are mostly for simpler things. The first challenge is that we need a lot of data to create reliable models.”
Input for these models must come from a range of component and material providers. Before design teams begin collecting data, they must determine which projects can provide the most benefits to vehicle operators. Many parts on modern vehicles operate for years without problems, so it’s more effective to focus on those that break down more often.
“We are individually building predictive maintenance algorithms for each component,” Teplyakov said. “Some components have a very low failure rate while others have higher rate of failure under specific conditions. We try to focus more on the complex, expensive components that fail under specific conditions than cheaper components or the components that have low failure rates.”
Commercial-vehicle owners and operators gain many benefits from sharing data with partners who can help them improve efficiency, but they’re also concerned about maintaining privacy and safeguarding information. Vendors say that good communication is one of the tools that help build confidence that data will be used judiciously.
“Our customers are generally open to Caterpillar having visibility to the data,” said Rio. “We open communications with customers about what data we collect and what we do with that data. Customers recognize that the value Caterpillar gets from using the data – to build better and more reliable products and to anticipate their needs – will benefit them as well.”
Most companies failing to protect customer data can alienate customers and harm their brand’s reputation. Those that decide to cut corners and bend privacy policies may also have to deal with regulators that can impose penalties. “After the EU General Data Protection Regulation (GDPR) came into effect, the first violations became public with the corresponding consequences,” said Schleicher. “Obviously, our customers are very concerned with privacy protection. OEMs are actively looking for solutions that enable them to collect and store data in compliance with data-protection regulations.”
Security is also needed to protect privacy. Suppliers at all levels are focused on preventing breaches. Layers of protective schemes are typically baked into designs from the start of the development cycle. “Privacy and security are keys to success in this market,” said Ogara. “We do things like providing user access control and making sure there are no openings for attacks. We use private gateways to the cloud – security is an end-to-end concept.”
OEMs can use customer data to see how features and functions are used, as well as how parts wear over time. But before this data is seen by design engineers, many companies protect privacy by removing any information about users. “Access to individual customer data is restricted,” Rio said. “However, our engineers have access to a vast quantity of anonymized and aggregated data, which is used to understand machine loads, duty cycles, and how the machines react in real-world applications. This in turn is used to influence product design.”Continue reading »