Automotive, Automakers, and Transformation
“The market for Automotive Data Analytics is forecast to reach $6.2 billion by 2026, growing at a CAGR of 16.75% from 2021 to 2026.”
– Automotive Data Analytics Market– Forecast (2021-2026) by IndustryARC
The automotive industry is in the midst of a futuristic transformation to accelerate fleet manufacturing at an astonishing pace with manufacturing analytics that shorten time to market, optimize production, and bring new models for revenue generation. It enables automakers and OEM manufacturers to tackle cost pressure, market competition, market dynamic shifts, globalization, volatility, and other challenges. This higher growth of data analytics is due to its extended uses in product design, product development stage, manufacturing operations, logistics sector, and aftermarket services. The ever-changing automotive landscape is adding an experience quotient in the value chain for enhancing customer experience (CX) that evolves relationships between automakers, OEMs, and customers.
Here, I’ll discuss the various aspects of data analytics for automakers to transform their manufacturing operations.
Data Analytics in the Automotive Industry
The automotive industry collects data from different sources that help in product design, development, and production. Connected car data, in-vehicle sensors data, GPS and navigation data, manufacturing unit data, and more enable vehicle performance, fuel efficiency, design competency, maintenance needs, predictive maintenance routines, etc.
Data analytics changed the way these manufacturing units of automakers work with valuable vehicle insights to drive data-driven, informed decision-making. They leverage data analytics to bring innovation into vehicle design for better safety, comfort, and fuel-efficient performance, as well as better production processes and overall quality control. Using in-vehicle sensor data, automotive manufacturers monitor and analyze engine performance, fuel efficiency, and other critical metrics with design issues to ensure higher performance. Data insights and analysis empower each development phase of the production line to identify blockages and potential issues to improve the process, minimize design flaws, and ensure safety standards.
MG Motor India, the subsidiary of SAIC Motor Corporation Limited, has introduced Insights Hub and Plant Simulation IoT data analytics to find the cause of production loss in its automotive assembly line and address the bottleneck in paint shop operations.
“We use the industrial IoT application, Insights Hub Visual Flow Creator, to build our workflow to create rules, define KPIs and perform advanced analytics. It enables us to convert the raw timeseries data into meaningful information,” as mentioned by Ravi Mittal, director of manufacturing for MG Motor India.
It collects real-time production data from the paint shop floor and analyzes it further to process with Plant Simulation (a digital twin model) to identify the root cause by replaying the production line with actual data. This helped them improve the paint shop’s performance by 15 percent. Data analytics plays a significant role in automotive manufacturing and production lines.
Intelligent (Smart) Manufacturing and Smart Factories
Going ahead with data analytics for automakers, we can’t ignore the idea of intelligent manufacturing and smart factories. Let me introduce you to Tesla’s gigafactories, the massive and futuristic manufacturing plants for advanced electromechanical technology-based vehicle development. One of these factories aims to produce 500,000 vehicles and 50 gigawatt-hours of battery capacity yearly; do you think this will be possible without data insights and innovative solutions?
The response is no; this large-scale production with optimized design and performance in these production units heavily relies on robotics, data analytics, artificial intelligence (AI), virtual reality (VR), and more. These production units process a larger amount of data to build system learning and analyze real-time data that enables them to operate without much human intervention.
Similarly, Mercedes-Benz, the luxury automaker, has its own ambitions for the digitalization of its production. They joined the fleet of intelligent manufacturing companies by introducing Cars Operations 360 (MO360). A digital ecosystem that integrates data from assembly lines, production processes, and IT systems across units to get real-time analysis, product tracking, and insights to enhance production standards, bring transparency, and slim down procedures.
“MO360 integrates the information from the main production processes and IT systems of the more than 30 Mercedes-Benz passenger car plants worldwide and brings together important software applications. It delivers significantly optimized KPI-based production control, for example. It also makes individual, needs-based information and work instructions available to each employee in real-time. Technologically, MO360 is based on the very latest IT technologies and working procedures,’ as explained by Jörg Burzer, Mercedes-Benz AG Board of Management.
Future of Production
Automakers have a clear vision of the ‘future of production for performance’ by digging deep into the data collected from the operational vehicles in real-time. Performance monitoring is one of the goals they want to achieve using digital twins and data analytics. Once again, we have Tesla as a perfect example; they create the digital twin of each of their vehicles to identify whether a car performs as desired or not. Later on, they use these data analytics to update vehicle performance.
If you think that this data collected from different sources is for production only, then you’re mistaken. We have another revenue generation model, where fleet managers, vehicle maintenance, workshops, insurance companies, and OEM manufacturers are ready to pay huge for these insights. They use these data insights and analytics to enhance fleet management and performance, predict maintenance and repair, insurance value, and spare parts demand predictions.
Final Words
The automotive manufacturing landscape has a huge amount of data across its units and segments that can be used to design and enhance the future of production. Automakers are highly using these data analytics to drive innovation, automate assembly lines, and accelerate production. Automotive companies are focusing on their sustainability goals with these smart factories by switching to renewable energy resources.
In the recent past, fuel-efficient design, lean adoption, and innovation were the key focus for automakers, who aimed to enhance overall experience, where data turned out to be a new fuel. The future of automotive manufacturing is fueled by data-led manufacturing, where automakers and OEMs leverage data across the production line to build a faster, more efficient, and high-quality fleet of futuristic vehicles. At Krish, I’m available to discuss the key enablers for automotive manufacturing production to facilitate the ‘future of production.’
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As Director - Marketing, Zenul leads the marketing and branding at Krish. He brings with him an in-depth understanding of the evolving digital ecosystem and has a proven expertise and experience in strategic planning, market and competition analysis, creating and implementing client-centered, lead-gen and brand marketing campaigns. He has a heart for technology innovation and has been a keynote speaker on various platforms.
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