Plugging into data is the only way to make winning EVs

Despite high levels of satisfaction from electric vehicle (EV) drivers, early adoption continues to be fuelled by brand lure and environmental aspirations. Manufacturers reeling from the rapid pivot to electrification are challenged with remaining profitable while delivering new models with range, infrastructure and — crucially— a price tag that attracts consumers. 

Hexagon’s industry survey of 416 global automotive professionals reveals that most respondents believe that EVs won’t reach price parity with ICEs until 2026-28 at the earliest. In Europe and the Americas, 36% do not believe prices will match until beyond 2028 despite 47% confirming that costs are the greatest threat to consumer adoption and that not meeting the necessary price point is a significant obstacle to transitioning from fossil-fuelled cars.

Improved range (84%) and price reduction goals (60%) dominate EV design objectives, but how is the automotive industry balancing conflicting consumer demands between improved range and lower costs? Longer EV range means using more of better batteries, the most efficient systems and in some cases more exotic and expensive materials to lightweight.

The 60% increasing investment in EV price reduction (see Figure 1) is paying off and automakers are gaining ground, though prolonged market uncertainty due to the COVID-19 pandemic and low production volumes keeps costs high. The survey also revealed that range anxiety remains a barrier to adoption, yet easing that anxiety entails producing longer-range batteries that contribute significantly to vehicle cost. 

Carmakers must also balance the imperative to reduce price with the need to improve profitability, as respondents cited either ‘reduced profit margins’ or ‘not meeting the price point for customers’ as among the biggest risks to transitioning from ICE to EV. This conundrum is echoed by independent analysts who found that most OEMs are only now seeing the potential for profit from EVs due to the higher cost of development. The only way to resolve conflicting demands for price reduction, profit increase and longer range is through greater manufacturing innovation and efficiencies across the sector.

This manufacturing Catch-22 is the result of steep car prices reducing demand, which in turn keeps prices high; the findings reveal that buyers are unable to negotiate economies of scale and suppliers are unable to achieve economies of scale due to low EV order volumes. 

Increasing efficiency in the manufacturing of yesteryear meant bigger and faster high-volume production, which remains fundamental to large OEMs. But today manufacturing efficiency must begin before components are produced to achieve productivity gains and cut time to market — which means that smart manufacturing, or using data to drive decision making and propel production, must begin in development. 

The manufacturing costing function has sat in OEM design teams for many years, with design-for-manufacturing techniques, including process-simulation, evolving from computer-aided-design (CAD) model preparation to predicting and mitigating the hard realities of the shop floor. We’re now seeing the need to truly connect development with production and assembly, and for more agile and collaborative teams to innovate and quickly resolve issues using trusted data-driven insights.

Today’s successful automotive manufacturers are demonstrating the value of virtual prototyping as their innovation cycles shrink by successfully reducing time from design to production using a simulation-intensive approach. This foresight helps to reduce vehicle costs while anticipating and eliminating potential defects early to avoid costs and delays. 

An ideal example of this principle in action is Valeo, which collaborated with Hexagon to develop a new electric drive unit that won an PACE award. Using our software, Valeo engineers quickly explored different design concepts to make optimal use of existing components. The result was an award-winning belt drive mechanism that reduced cost, with a now-patented modular design that suits multiple applications from e-scooters and e-bikes to passenger vehicles. This approach reduced development time by 7-9 months and reduced time-to-market for the Citroen AMI One from 24 months to 18 months. 

Gains made by tearing down departmental walls are numerous, most notably more integrated system development and production, but doing so requires increasing supply chain collaboration and vertically-integrated manufacturing.

While the term ‘smart manufacturing’ is used to describe any manufacturing process that makes better use of data, using data-driven insights to enable greater autonomy in decision-making and robotic production entails first breaking down the silos between development, production, and assembly.

Take transmission design and manufacture, for example. Gear development time can be reduced by using quality data to confirm that parts can actually be manufactured before the chips start flying, and performing statistical process control on real-time production data can prevent tolerance issues before they occur. When problems inevitably do occur, a digital thread lays the groundwork for tracing individual parts at the touch of a button — back to the material, operator, machine tool, cutting tool, etc., that was the root of the problem. Eliminating a physical paper trail also means that there is less risk of human error, as data is transferred digitally to machine tools and inspection devices.

Using simulation to predict issues, and statistical analysis or machine learning to reconcile it with production helps close the gap between design intent and manufacturing quality.

Unlocking the advances that more collaborative engineering can bring to new EV products is now crucial in levelling up automakers as new players make headway. For instance, Lucid Motors overhauled how its motor and transmission systems are designed by combining previously siloed departments into a holistic system-level approach. By analysing the electric drive unit as a single system and combining engineering talent across disciplines, the company created the smallest, lightest, and most efficient units on the market. Its compact electric drive unit comprises the motor, transmission and differential and invertor into a 73 kilo 500 kW drive unit with market-leading performance. 

Beyond development, Arrival is pioneering vertically-integrated component production and robotic assembly to realise highly automated micro-factories – the polar opposite of traditional production lines. Rapid change in the automotive manufacturing ecosystem requires suppliers to utilise a different skill set and participate in a process that’s more vertically integrated and involves more agile ideas, such as continuous improvement and deployment that are more familiar to software companies.

In the past, a design or programming problem that reared its ugly head during production would previously result in the job being passed between departments to get a fix identified, designed, approved, tested, and sent back to the shop floor. Resolving such problems could take days, weeks, or months and — while this still happens — new players are fixing issues with more dynamic and often automated methods.
A few years ago, you’d never here the phrase ‘We’re building the place whilst flying it’, but when you consider the pace of change its more apt in the eMobility era.

Greater flexibility is another requirement for success in modern automotive manufacturing. The perfect storm of the pandemic, supply chain disruption, and the EV pivot has taught us that change is the new normal, and we see large OEMs address this shift in many ways.  

Changes in product designs that result in changes to production and inspection needs are easier to reconcile with flexible manufacturing and quality processes that can be quickly reconfigured and honed offline. This new paradigm ensures rapid time to market without sacrificing quality or requiring additional labour. 

This flexibility can be seen at ŠKODA AUTO, which collaborated with Hexagon to reduce the time required to program robotic inspection from several days to just four hours using a new breed of robotic programming and control software. HxGN Robotic Automation software enables manufacturers to equip greenfield factories or retrofit existing production lines with autonomous inspection. The software bolsters Industry 4.0 operations by intelligently designing inspection routines for vehicle components, such as doors — which typically requires significant input from both metrology and robotics professionals — in a single step. ŠKODA AUTO currently uses the software to deploy quality inspection cells faster to the production line so they’re ready and waiting to gather quality and production data as soon as a new vehicle goes into production.

One of the challenges to building EV production platforms is the need to retrofit, reskill and future-proof brownfield manufacturing facilities for the divergent manufacturing requirements of EVs. Because an EV is an integrated ‘system of systems’ encompassing software and electronics, it follows that it requires equally integrated and holistic manufacturing processes. 

It follows that digitally-isolated shop-floor machinery and closed industrial IoT networks must be retrofitted to create collaborative, connected manufacturing processes, and linear assembly lines replaced with agile systems capable of rapidly integrating new platforms or parts. Manufacturing robots and metrology systems must be able to communicate so that faults are swiftly detected and corrected.

The challenges faced by automakers who’s battle to get ahead in the EV world order are as much internal as they are external. The need to make EVs more affordable at current order volumes, coupled with delivering greater choice, means traditional high-volume manufacturing lines must be replaced by more agile manufacturing, built around speed to market. Read more: https://go.hexagonmi.com/EVPivot-ANE