Automotive Testing in the Digital Era: Efficiency and Safety Trends

1. What prominent industry trends are currently shaping the future of testing procedures in the automotive sector, particularly in terms of ensuring global market access and overall safety compliance?
   
   

   Testing procedures are an integral aspect of all industrial manufacturing. In particular reference to the rapidly evolving automotive sector, testing procedures can make or break a vehicle. Here are some key trends that are expected to expand exponentially –

   Autonomous and Connected Vehicle Testing – autonomous vehicles are gaining momentum despite roadblocks and challenges. Testing of autonomous and connected vehicles is of utmost importance as it validates performance and safety. Ensuring the reliability and security of these vehicles is a priority for companies.

   ADAS Testing – The Advanced Driver Assistance Systems integration and testing is another key trend that is expected to advance significantly in the coming years. Features like adaptive cruise control, lane departure warnings, emergency braking, and so on will ensure better safety and reliability of vehicles.

   EV Testing – The Electric Vehicle boom is surely good for companies and markets worldwide. At the same time, EV testing is crucial, especially about batteries and miles coverage. Range validation, charging infrastructure, and battery testing are crucial areas for EVs and companies will continue to research and invest in the same.

   Cybersecurity Testing – Vehicles today are smart and connected. While this has a huge advantage, it also brings in vulnerabilities. Running cybersecurity testing of in-vehicle systems will be another vital trend we will see in the coming years.
   
   

2. In the context of automotive component testing during development, how does early fault discovery contribute to averting costly product recalls and achieving cost savings?
   
   

   Product recalls can be very expensive and result in a waste of valuable time and resources, not to mention the reputational damage of a brand. Early discovery of faults has several benefits –

   Preventing Spreading of Issues – When we discover a fault early on, it helps in preventing the accumulation of faulty components in the production line. If a defect is caught at an early stage, manufacturers can take corrective measures to ensure that the issue does not affect a large number of units.

   Cost Saving – This in turn helps in reducing costs significantly, especially when compared to discovering them after the product has been released onto the market. Early detection of issues helps in addressing these components before they are integrated into the final product and released to the market.

   Minimizing Liability and Legal Issues – When a product is recalled from the market, it leads to several legal consequences and liabilities. When a fault is caught early on, it helps manufacturers mitigate the risk of legal action, potential fines, and the costs associated with compensating affected customers.

   Supply Chain Management – The supply chain is a crucial aspect for manufacturers, which is directly related to early fault testing. Identifying faults early in the supply chain allows manufacturers to work closely to rectify these issues. This proactive approach strengthens the overall supply chain management, reducing the likelihood of faulty components entering the production process.

   Compliance and Regulation – Like most industries, the automotive sector is subject to strict regulations and standards. When a fault is detected early on, it ensures that the final product meets regulatory requirements. It ultimately helps manufacturers to avoid penalties and potential bans.

   Reputation and Customer Satisfaction – One of the key advantages of early fault detection is preserving a brand’s reputation and customer satisfaction. Early fault detection shows a brand’s commitment to quality and safety, which leads to higher customer satisfaction and lead to repeat customers.
   
   

3. How are automation, AI, and Data Analytics being utilized to streamline testing processes and enhance coverage and speed within the automotive sector?
   
   

   The rapidly advancing automotive industry is tapping into AI, automation, and data analytics for various testing processes. These technologies are being used to automate testing frameworks that further help in faster execution of test cases, while efficiently carrying out repetitive and time-consuming tasks. Here are some ways it’s being utilized –

   AI-powered Test Execution and Analysis – Advanced AI-powered algorithms analyse test results to identify anomalies, issues, patterns, and further help in finding detects. This offers valuable insights for test optimization and speeds up the debugging process.

   Predictive Analytics for Test Planning – Data analytics plays a vital role in analysing historical testing data. The technology is further used to identify defects, predict potential issues with a timeline, and further optimize test planning. Manufacturers tap into AI and data analytics tools to allocate resources effectively and prioritize testing efforts to improve overall efficiency.

   Robotic Process Automation (RPA) – As far as automation is concerned, RPA or Robotic Process Automation is utilized. This helps in automating repetitive and rule-based tasks in the testing process. This could be mundane tasks like data entry, test script execution, result validation, and so on. Automation helps the larger testing team to focus on more complex and strategic aspects.

   Safety and Compliance Testing – Manufacturers further tap into AI tools to ensure safety and compliance testing processes meet regulatory standards. Automated systems help in the verification of safety features and compliance with industry-specific regulations.
   
   

4. Can you elaborate on the advantages of a cloud-driven test ecosystem in terms of infrastructure utilization, consistency, and efficiency in automotive testing?
   
   

   An OEM or Tier one will have multiple test benches having different: test equipment, devices under test, levels of testing (Models, Software, Hardware) across the globe. Decentralized control of these test benches results in certain issues like: lack of visibility, non-scalability, test benches not utilized efficiently, each team working in separation, no provision for left shifting of validation, separate test artefacts being developed for each test bench, repeating the same tasks for each test bench etc. Cloud-driven test ecosystem provides a cloud based control and maintenance of multiple test infrastructures across the globe. This provides the advantages of better test infrastructure utilization, cost and time-savings as elaborated below:

   Optimum use of Test Infrastructure – Cloud Driven Test Ecosystem brings all these benches under one umbrella, so that one can remotely schedule tests to be executed in specific test benches. Thus one could utilize the existing test infrastructure efficiently.Reusability of Test Cases across test levels and similar devices under test – Cloud Driven Test Ecosystem provides an option for the test engineer to write the same test case for different levels of testing. This saves the huge effort involved in conventional testing process, where separate test cases are written for different test levels / test equipment. These test cases can be written using key word driven technology where plain English is used for test case authoring. Thus, the test engineer need not know any programming / scripting language. Converting the common test cases to execution scripts as per the target test bench is taken care by this platform. This saves the effort and time required for complex test scripting/programming.

   Cloud Based Test Automation, Test Scheduling and Execution – A central control of test execution, automation provides flexibility and scalability. One could execute more test cases within the same time frame due to the centralized control from cloud. Certain test cases at software level can be executed in the cloud infrastructure itself. The scalability, resilience, elasticity of cloud can enable numerous instances of testing to be executed concurrently. This can save the cost involved in costly on premise test infrastructure.

   AI-enabled test solutions such as Automated test case creation, Smart regression test case selection, and Smart triaging​ – These value additions part of this test ecosystem, brings in the power of AI to the testing domain. Conventionally these tasks are done with intensive manual effort. Application of AI to these testing tasks, can automate the process up to a great extent, saving effort, time and this cost.

   Centralized dashboard view for test execution status, failures reports, Software maturity – A centralized cloud based visualization of test artefacts gives better to visibility of software maturity to all the relevant stakeholders in real time. By looking at the relevant KPIs, the team can informed decisions at correct time. This saves the time usually lost in transferring the test results offline from test infrastructure to relevant stakeholder.

   ECU Virtualization: This allows the embedded software binary to be executed and tested in a simulation environment, even before the target hardware is available. This enables left shifting of the validation procedure, saving the time and cost incurred in finding and fixing issues much later in the product development lifecycle.
   
   

5. What does the concept of “Left Shifting the Process” entail, and how does it result in measurable time and cost savings in the automotive testing domain?
   
   

   The testing landscape has evolved to keep up with growing expectations. ‘Left Shifting’ is a context in the testing environment where certain activities that are traditionally performed later in the development & validation lifecycle are moved to an earlier stage. The concept is closely associated with the shift-left testing approach, which identifies and addresses issues as early as possible. Left Shifting brings several advantages to the overall development cycle.

   Early Detection – One of the key advantages of Left-Shifting is its ability to detect any anomaly in the early stages. The method helps the overall team to catch and identify any defects.

   Time-Saving – With early detection, Left-Shifting also helps in saving time. As defects and possible anomalies are identified in the early stages, it provides the team more time to rectify the issue. The same would have been a waste of time and resources if detected in the later stages of the development process.

   Cost-Saving – More importantly, the Left-Shifting process helps in cutting down costs. Since defects or issues have already been identified, addressed, and rectified, it helps in cutting down costs significantly. It also helps in improving the overall development process, allowing manufacturers to release more products in a shorter period.
   
   

6. Could you provide examples of how Tata Elxsi has applied its expertise to establish XIL (X – Model, Software or Hardware) infrastructures and facilitate effective validation in the automotive industry, especially through collaborations with industry partners?
   
   

   Tata Elxsi is a key player when it comes to testing solutions in a diverse field, including automotive testing. Some of the testing services offered include EV testing services, telematics testing, infotainment testing, autonomous driving & ADAS testing, and cloud-driven test ecosystem. Tata Elxsi have setup, maintained multiple Hardware In Loop (HIL), Model In Loop (MIL), and Software In Loop (SIL) test benches for component, system and vehicle level testing for various domains. Our close tie up with dSPACE, NI, VECTOR acts as a catalyst for preferential engagement.

Spokesperson: Preejesh M R, Practice Head, Automation & Validation