Aqira, supplied by Hottinger Brüel & Kjær (HBK), reportedly improves on the previous system with a streamlined, customizable search experience and richer metadata, enabling engineers to quickly find and retrieve data in usable formats. The aim is to offer greater insight and efficiency in Ford’s next-generation engineering workflows.

Dan Clatterbuck, CAE/TEST engineer at Ford Motor Company, commented, “Aqira has been an extremely positive experience for our engineering teams. It’s a solution built by engineers, for engineers, allowing us to shape the system to fit our workflows and reducing our reliance on IT support.”

In related news, automotive Ethernet compliance simplified with Anritsu and Tektronix test solution

The Future of Automotive Testing Conference

This day of high-level content will explore various topics and provide an engaging opportunity to learn from and connect with industry peers. Situated among the exhibits, it will have a relaxing atmosphere, and visitors will be able to dip in and out at their leisure. A highlight will be ATTI’s on-stage interview with Jon Quigley, who worked for Volvo for many years and now runs his own company, Value Transformation. With his broad experience and portfolio of contacts, he’s a very good person to know. He loves sharing his thoughts, too, hence his new gig as ATTI’s regular columnist.

Read Quigley’s latest column on p36 of the September issue.

Also during the conference, Venkat Adusumalli, software engineering manager at Stellantis, will reveal how Stellantis is using AI to accelerate E/E system testing and validation workflows. Click here for a pre-show interview with him.

Innovation Showcase

The free-to-attend Innovation Showcase also provides an interactive platform for learning about new technologies. Speakers will welcome questions and discussion after their presentations, making it a great way to explore ideas together. Like the conference, it will take place within the main hall, so it will be very easy to listen in while wandering through the exhibits, or to come and go throughout the day.

Technology debuts

The industry is moving quickly and it can be a challenge to keep up. Every year there is an abundance of new technologies on display. Some are incremental improvements to existing products, others are entirely new. It’s always surprising how companies find ways around bottlenecks. Often, these developments emerge from ongoing conversations between supplier and customer, ultimately benefiting multiple companies.

Read ATTI‘s comprehensive expo preview in the September issue.

Face-to-face discussions  

It sounds obvious, but the most fruitful conversations are usually the ones that happen in person – it’s how journalists find the best stories. Year after year, exhibitors and visitors report having forged unexpected collaborations at the show, in the form of technology tie-ups or service partnerships.

Detroit’s revival 

A lot of money has been plowed into Detroit in recent years, as evidenced by the stunning renovation of Michigan Central Station, which is well worth a visit. Much of the investment has been in the tech sector. Eleven years ago – when the station was still derelict – ATTI took a tour of some of the labs at GM and what was then the FCA headquarters (see The right wave length, November 2014, Seasonal highlights, September 2015, and Powerbase, March 2015). The facilities were impressive then and are even more so now, thanks to several years of investment in innovation leading to Detroit’s resurgence as an automotive powerhouse.

Visit the Automotive Testing Expo North America website to secure your FREE pass, which will give you access to the expo, the Future of Automotive Testing Conference and the Innovation Showcase

Designed for high-performance data acquisition in compact, space-constrained environments, the ADQ3-USB brings the full capabilities of the ADQ3 platform into a standalone USB 3.2 form factor, offering up to 10GSPS (Gigasamples-per-second) sampling rate and 2GB/s sustained data transfer to a host PC.

High-speed digitizers are a critical component in analytical and sensing systems, such as lidar and automated test equipment. The demand for faster data acquisition in these fields is driven by higher resolution, faster imaging speeds and more granular real-time analysis. These generate gigabytes of data per second, demanding efficient real-time processing and high-speed data transfer. To preserve signal integrity, especially in compact and noise-sensitive environments, it is often essential to place the digitizer close to the detector within the system enclosure.

Compact design and performance

The ADQ3-USB is housed in a fanless enclosure that supports side-by-side mounting of two units in a standard 1U 19in rack. This design enables users to place the digitizer close to the detector, minimizing cable length and reducing signal reflections, optimizing analog performance in high-speed applications.

It supports continuous data streaming at up to 2 GB/s via USB 3.2, with onboard FPGA capabilities for real-time signal processing, and can handle large volumes of raw data up to 20 GB/s. By eliminating the need for PCIe slots, the ADQ3-USB enables fast and simple integration with mini-PCs and laptops, making it suitable for mobile setups, embedded systems and OEM applications.

Firmware and FPGA options

The ADQ3-USB supports multiple firmware packages tailored to specific application needs, such as FWDAQ for standard data acquisition, FWATD for waveform averaging, FWPD for pulse detection and  DEVDAQ for custom FPGA development.

The open FPGA architecture enables users to implement application-specific algorithms directly on the digitizer, reducing the need for post-processing and enabling real-time decision-making.

OEM integration and model variants

Teledyne SP Devices positions the ADQ3-USB for OEM integration, with ISO-certified production, global support and tailored engineering services for hardware and firmware modifications.

The ADQ3-USB is compatible with a wide range of digitizer models within the ADQ3 series – the ADQ30, ADQ32, ADQ33 and ADQ35. Each model offers different sampling rates, bandwidths and channel configurations.

In related news, high-force, compact 100kN tabletop testing system from Instron targets metals and composites

Test benches have long played a critical role in research and development. In highly controlled lab environments, engineers can measure performance with extraordinary precision. They can simulate stresses, observe failures and capture data with forensic detail. However, the transition from lab to production is rarely straightforward. The requirements of real-world manufacturing – cost, durability, speed and flexibility – demand a different approach to testing. Increasingly, businesses need systems that can bridge both worlds.

This is especially true in sectors where quality and safety are non-negotiable. Aerospace manufacturers, for instance, are often required to store performance data for a decade or more. Automotive OEMs need to verify critical systems like suspension or braking, not just once but continuously, across thousands of units. Pharmaceutical companies must validate devices under strict regulatory conditions, with traceable, repeatable results. In each case, the testing solution must start as a precise tool for experimentation and evolve into something robust enough for the factory floor.

What’s emerging is a shift in mindset – from thinking of test benches as bespoke lab rigs to viewing them as integrated test systems that can be adapted, replicated and scaled. This is changing how machine builders approach design. Rather than building entirely new setups for each test scenario, there’s a move toward modular, reconfigurable architectures that can be tailored to the task, whether it’s analyzing torque in a robotic arm or checking the pressure tolerance of a safety valve.

Data driven

Data is at the heart of this shift. Capturing accurate, high-frequency data enables teams to spot anomalies, understand failure points and refine products before they reach market. However, in production environments, data acquisition faces new hurdles like electrical noise, temperature fluctuations or physical vibration. The test system has to be able to withstand all of this and still deliver clean, usable data.

One of the more significant developments in recent years has been the ability to record data at very high sampling rates – tens of thousands of data points per second – and do so reliably on the factory floor. In high-speed or high-risk applications, where a single missed signal could mean a costly failure, this can make a measurable difference to reliability.

Another important consideration is how scalable a testing solution is. A setup that works for one prototype may not be viable for high-volume production. Flexibility is key. Machine builders are increasingly looking for systems that can be easily expanded or adapted without the need to start from scratch. For example, being able to add extra inputs or change how data is logged, without ripping out and replacing entire systems, can make testing more responsive to shifting needs.

There’s also a growing awareness that the value of a test system extends beyond the testing itself. Once validated, the same configuration can often be packaged and sold as a standalone product. We’ve seen examples in industries from automotive to medical devices where a test setup built for internal use has become a marketable solution. What begins as a custom bench in R&D ends up as a repeatable, sellable machine – industrialized and ready for deployment.

This evolution is shaping how engineers think about testing, not just as a stage in development but as a strategic capability. By investing in systems that are both precise and production-ready, businesses can accelerate the path from prototype to product.

As the boundary between lab and line continues to blur, the tools and thinking around testing are adapting. The challenge now is not just how to test thoroughly, but how to do it smarter, faster and in the environments where it counts.

Read our interview with Mehdi Ferhan, Volvo Group’s senior vice president for powertrain engineering, in which we discuss legislation, sustainability and Volvo’s future vehicle development 

“The implementation of Siemens’ Teamcenter software represents a major technological shift for Tatra Trucks and will provide the company with a significant competitive advantage on the global market. Digitization will enable us to respond more efficiently to the specific requirements of each customer and faster order processing. We anticipate more flexible development, faster technological preparation of production and more timely deliveries of the required quality,” said Jakub Pončík, technical director, Tatra Trucks.

The use of Teamcenter will help Tatra Trucks achieve synchronization and effective data management, from business communication and development through vehicle production to spare parts catalogs or warranty and post-warranty service, by bringing together its PLM system for product development and management with its enterprise resource planning (ERP) system for economics and production.

These systems will become key pillars of digitalization, enabling the company to unify previously fragmented systems, simplify processes and enable faster and more efficient collaboration between departments. The implementation also includes Siemens’ Mendix low-code platform, which allows for the quick creation of applications to reach data from information systems such as ERP and customer relationship management (CRM) and connect it to the Teamcenter digital thread backbone.

“The decision to implement solutions from Siemens Xcelerator at Tatra Trucks demonstrates its key role in optimizing the company’s digital processes. Teamcenter enables the effective use of digital twins and artificial intelligence to innovate products and manufacturing processes, helping to ensure long-term competitiveness. We are glad that Tatra Trucks has chosen our solution and we look forward to our journey together,” said René Zahradník, managing director for Czech Republic, Siemens Digital Industries Software.

The software solution integrates all key PLM processes into a single database. Teamcenter manages all customer requirements, which will be managed in real time through program and project management, including process quality across the entire company. All changes and requests will be recorded and managed within Teamcenter change management. The PLM system enables the creation and management of complete bills of materials and helps Tatra Trucks to more efficiently develop innovative products; improve information sharing between production, service and maintenance; achieve its sustainability goals of carbon footprint reduction; and meet regulatory requirements.

In related news, Siemens Digital Industries Software announced it is introducing new versions of its Teamcenter X software so that organizations of all sizes can access SaaS Product Lifecycle Management (PLM). Click here to read the full story

It builds on its precursor Marple Cloud, with the ability to read databases – rather than ‘drag and drop’ files – and thus caters to larger teams or infrastructures than its precursor. 

MarpleDB, another development, is a high-performance database designed to store and query time-series data, and complements Marple Insights by vertically integrating into the cloud tool, with the ability to be the database should a transition from a file model to a database model occur. 

The automotive industry is seeing a huge leap forward regarding data, which is moving from local files to a database model, meaning an increasing demand for large, smart cloud data storage. However, a disconnect between IT and engineering is often an issue seen in the industry. 

Most visualization and analysis tools are for business intelligence, requiring an engineer to download the data to jump into a local script, or there is no database process adopted in the first place. This reduces productivity as the data is not in a database, accessible to everyone, in real time. MarpleDB and Marple Insights are designed to address these issues. 

For example, MarpleDB can be the first stage in the data pipeline, ingesting real-time data efficiently. Marple Insights can be used to make a project where many different visualizations (maps, FFTs, time-series, scatter plots) and KPIs (histograms, formatted labels, tables) are presented to each team member independent of their location. 

This data can be further enriched with Marple’s tooling, such as custom math channels, data overlays, live-data support and other industry-specific items such as distance-based plotting for motorsport users. 

Marple has been introduced to a number of large motorsport teams, and has been employed at the IMSA 24 at Daytona, among other races. 

In related news, Automotive Testing Technology International magazine will be hosting a free-to-attend interactive panel session at Automotive Testing Expo Europe 2025 in Stuttgart, Germany, in May to provide a roadmap for not just surviving but thriving amid the headwinds of potential international trade tariffs and challenging net zero timelines. Click here to read the full story.

The collaboration will connect Altair’s RapidMiner, a tool for data preparation, AI development, orchestration and automation, with the Databricks Data Intelligence Platform to amplify data science and machine learning capabilities. This will enable customers to access and analyze data housed in Databricks, without data duplication, while applying Altair’s suite of tools to drive decision-making, build AI automation and modernize data operations.

Altair’s AI capabilities include low-code AutoML to sophisticated MLOps, agent frameworks and high-speed visualization.

“We are thrilled to partner with Databricks to empower our customers to stay ahead of the competition by achieving faster, smarter and more efficient outcomes,” said Sam Mahalingam, chief technology officer at Altair. “Through this collaboration, we are helping customers not just to analyze their data but to truly activate it, transforming fragmented data into intelligent systems that can learn, reason and act. Together, Altair and Databricks are redefining the future of data science and analytics.”

“We’ve been impressed by Altair’s innovative approach to data preparation and machine learning,” said Databricks’ director of strategic technology partners, Ariel Amster. “Our partnership will leverage the benefits of Altair RapidMiner and the Databricks Data Intelligence Platform to help customers explore, analyze and take action on data at scale.”

Altair RapidMiner also offers native support for SAS language execution, one of only two platforms in the world with this capability, aiding customers in preserving and extending the value of their existing analytics investments while modernizing their workflows.

Knowledge graphs and data fabrics

The collaboration also utilizes Altair RapidMiner’s massively parallel processing (MPP) knowledge graph technology, purpose-built to support knowledge graph creation, data fabrics and ontology modeling at enterprise scale.

By integrating with Databricks, customers can access the Altair RapidMiner knowledge graph engine to connect, contextualize and activate all types of data: structured, unstructured and streaming.

In related news, the data analysis software jBEAM Lab from Kistler recently updated to offer functions that enable more efficient analyses. Click here to read the full story. 

Without proper data analysis tools, there is no clear way for automotive companies to turn the data they collect into actionable insights that can help shape the next generation of vehicles, which means innovation in the industry is at real risk of stalling.

Automotive companies have been trying their best with the tools available to them. They know that their data could be incredibly powerful. That’s why they’ve continued to collect it wherever they can – from traditional sources such as DAQ hardware, but also in the form of digital data collected by IoT sensors, ADAS and a whole range of communication buses.

However, collecting data is much easier than actually using it. Let alone unlocking its full value.

Right now, automotive engineers are still left working with data analysis tools that are inefficient, that can’t handle their data, and that can’t support their preferred analysis processes.

It’s time for that to change.

The three barriers to automotive data analysis

There are three key flaws in most data analysis tools that stop automotive companies using their data effectively.

The first barrier is data overload. There’s simply too much data to grapple with – most of it unstructured and almost impossible for most tools to analyze in an efficient way. Most platforms require that data is carefully sorted and processed before it can be analyzed, which makes it almost impossible to extract useful real-time insights.

The second barrier is quality and integration issues. The most valuable data today is digital bus data, which tends to be inconsistent, full of gaps and confusing values that most analysis tools struggle to work with. Not to mention that most platforms can’t easily integrate data that comes from different sources – such as sensors, in-car electronics and manufacturing machinery – making it difficult to see the full picture of a vehicle’s performance.

The final barrier is, arguably, the most frustrating one for engineers: their tools aren’t built for the automotive industry. Most platforms can’t extract many of the insights that automotive engineers need most, or follow their most common processes. As a result, engineers are forced to ‘make do’, creating their own Python or custom scripts to adapt existing tools, or even building their own tools from scratch so that they can create workflows that suit their needs.

Building and maintaining these customizations takes up a staggering amount of engineering time. It’s become such a normal part of the testing and development process that most automotive companies don’t even notice how much time their people are wasting on coding. That’s time that could be used to drive innovation and win the company a new competitive advantage.

Not to mention that, with turnover in the automotive industry being so high, these custom scripts carry an added risk: when the person who built or customized the tool moves on to another opportunity, they take all their knowledge and documentation with them, leaving their engineering team with a tool that’s impossible to maintain or use effectively.

These barriers might seem difficult to overcome – but automotive companies don’t have to accept this status quo.

Changing the face of the industry

The first companies that manage to upgrade their data analysis will have a huge competitive advantage.

Their innovation cycles will accelerate and being able to understand real-world usage of their vehicles will enable them to constantly enhance their designs. They’ll minimize guesswork, which means they’ll be able to create new products that make a real difference to drivers’ safety or quality of life.

Their products will become more reliable. They’ll be able to deliver enhanced predictive maintenance, reducing downtime and creating better experiences for customers.

Analyzing driver behavior and system performance will allow them to build more advanced ADAS, adapt to different driving styles, and allow each driver to create their own customised experience.

For example, a major automotive company was struggling to process and use the immense amount of data that its fleet of cars was collecting – just like all of its competitors. In the past, the company’s engineers only needed to process the relatively small amount of data gathered in their labs during testing and development.

But its quest for innovation had left it drowning in data. By the time it spoke to its solution provider, its connected vehicles were sending a deluge of data – every day, every hour, or even every minute. The data center was filling up, but the analysis systems weren’t built to process all of the data being collected.

There was plenty that the company wanted to know. How could it reduce failures in its vehicles and make them more durable? How were customers really using the products? But it had no idea how to extract that information from its data.

The company was searching carefully for the right solution. And it needed something fast; it was already wasting time trying to process and store all this data, so it didn’t need to waste more time coding its own analysis platform from scratch.

Luckily, HBK was able to supply a complete off-the-shelf tool – and, in the process, provide easy access to insights that are now revolutionizing the company’s R&D process.

It’s time automotive companies put their data to work

The future belongs to automotive companies that can make their data work harder for them – using it to shape strategies and fuel innovation, instead of leaving it languishing in a data lake. By harnessing the full potential of their data, they’ll not only develop new products faster, but also deliver safer, more reliable vehicles that redefine the driving experience. However, the industry’s future depends on robust, flexible, efficient data analysis tools. In other words, automotive data has changed – and it’s time that automotive data analysis tools caught up.

Read more about HBK here 

In today’s fast-paced commercial and mobility sectors, businesses are increasingly faced with the challenge of doing more with less. As industries continue to grow and evolve, the need for efficient, scalable solutions has never been more crucial. One area where this need is particularly evident is in data management, where companies must handle vast amounts of information quickly, accurately and with minimal overhead.

At the heart of this challenge is the growing demand for data logging systems that can not only be deployed in minimum time but that can also manage the collection, decoding and analysis of deep data from a vehicle’s CANbus. Whether it’s in the automotive industry, where manufacturers are driving for greater performance, range and lower warranty claims, or in the mobility sector, where real-time data is critical for maintaining reliability and uptime of fleets, companies are turning to solutions that meet these demands with production grade stability and precision.

The shift to scalable solutions

One of the key drivers of efficiency in modern data logging solutions is scalability. Traditional systems often require large teams to manage and process the data generated across various features, functions, systems or even fleets. However, as companies increasingly recognize the need for greater operational efficiency, there is a growing push toward solutions that centralize resources and reduce the manpower needed to instrument and collect data.

This shift is exemplified in the move toward ‘logger light’ systems, which enable businesses to manage their data logging and analysis processes using less time for deployment, configuration and data post-processing. In essence, these solutions enable businesses to focus on what truly matters – delivering insightful data to engineers and managers so they can make informed decisions at component, vehicle or fleet level, rather than the manual processes that have traditionally been required to gather and process such data. As a result, businesses rely on their logger light systems to work harder and more efficiently across the whole product development lifecycle, from R&D, pre-pilot and production to aftermarket.

Technology working harder for industry

The integration of advanced technologies like cloud, AI and big data analytics into logger light solutions is another game-changer. These technologies play a significant role in enhancing the efficiency of big data management using centralized data storage and processing power, allowing systems to not only collect and visualize vast volumes of data but also make sense of it in real time. This has shifted expectations in industries that depend on fast decision making, such as mission-critical and safety-critical applications, where actionable insights need to be delivered instantly.

For instance, the ability to instantly access and analyze data from various remote sources – whether it’s a fleet of vehicles, a network of charge stations or globally distributed test cells – has become a key operational expectation. Where once this might have taken days or even weeks of manual data gathering and analysis, now it’s available in seconds, allowing businesses to react and adapt to changing circumstances with unprecedented speed.

Delivering consistent, reliable results

Stability and reliability remain the basis of any effective data management system. In industries that rely on precision and real-time data, the margin for error is slim. No matter how sophisticated the technology is or how fast the data can be processed, the ultimate value lies in the system’s ability to consistently deliver accurate, actionable insights.

This focus on reliability means that businesses need solutions that are both robust and dependable, ensuring that the data they rely on is always available and accurate when they need it most. It’s no longer about cutting-edge technology for the sake of innovation – it’s about making sure that the technology delivers practical, measurable results that improve operations day in and day out.

Navigating the perfect storm

The commercial and mobility sectors are currently navigating what can be described as a ‘perfect storm’ of challenges. Increased demand, limited resources and an ever-evolving compliance and technological landscape are pushing companies to find new ways to meet their objectives more efficiently. The shift toward logger light solutions, cost engineered for scale and ease of installation, administration and configuration, is one response to these pressures, allowing businesses to continue driving growth and innovation without being bogged down by the complexities of traditional systems.

As industries move toward greater sustainability and cost-efficiency, the role of data logging systems in supporting these transitions will only become more critical.

This advanced platform integrates data analytics, real-time monitoring and compliance features to deliver insights for OEMs and the entire battery ecosystem, including material suppliers, cell and module manufacturers and recyclers. These features enable better performance tracking, maintenance, and sustainability management, making Mobius+ an essential solution in the mobility ecosystem.

Minespider contributes its blockchain-based battery passport solution, enabling compliance with global regulations, including those in Europe and the USA. Meanwhile, Tata Elxsi leads the development and delivery of Mobius+ as a scalable solution for global markets and takes the lead for deployment in India.

The platform features a seamless interface for vendors to upload and manage their data, ensuring compliance and accuracy across the supply chain. For data storage, it uses a secure, cloud-based system that consolidates data for easy access and analysis by OEMs and stakeholders. Mobius+ provides valuable insights through powerful analytics features, helping companies monitor battery performance, enhance design and optimize lifecycle management.

“Our collaboration with Minespider is a commitment to drive innovation in sustainable mobility. With Mobius+, we aim to set a new benchmark for battery lifecycle management, providing customers with compliance-ready solutions, advanced tools and data-driven insights to create a more sustainable and transparent future in mobility,” said Anil Radhakrishnan, chief product officer, Tata Elxsi. 

“Partnering with Tata Elxsi enables us to bring our blockchain expertise to a comprehensive platform that supports the industry’s drive for transparency and compliance,” added Nathan Williams, founder and CEO, Minespider.

Mobius+’s global launch is taking place at the Bharat Mobility Show, where Tata Elxsi and Minespider are showcasing live demonstrations of the platform’s capabilities, including its analytics use cases and compliance features.