Auto Makers Lead Smart Manufacturing Advances with close to 50% Automation
LONDON, UNITED KINGDOM – The adoption of smart manufacturing technologies is growing in almost all industries within the leading manufacturing countries such as the United States, Japan, and Germany, and the automotive industry has been a pioneer for most technologies in each of them, finds ABI Research, a market-foresight advisory firm providing strategic guidance on the most compelling transformative technologies.
“The automotive industry has been a pioneer in adopting many transformative technologies because it has more of a need and a demand to increase flexibility and agility,” explained Pierce Owen, Principal Analyst at ABI Research. These technologies include Additive Manufacturing (AM), Artificial Intelligence (AI) and Machine Learning (ML), Augmented Reality (AR), and Collaborative Robotics (cobots), as well as Industrial Internet of Things (IIoT) platforms. Some of the leading automotive Original Equipment Manufacturers (OEMs) including Audi, Volkswagen (VW), Ford, Honda, Daimler, and BMW have at least piloted and, in some cases, have scaled these technologies.
In terms of overall automation, while most industries have automated 20% to 30% of their operations, the automotive industry has automated closer to 50% of operations. This has resulted in more real-time operational data made available to automotive OEMs and their suppliers. Some of the OEMs use the 3D printers for customized or low-volume production parts, a trend in-line with demand for more customized, low-volume batches.
Smart manufacturing vendors targeting automotive have already seen a surprising amount of progress. Dassault Systèmes has Honda North America using DELMIA to design and simulate its plant floors before building them and works with Cummins on the execution side. Telit also works with Honda North America, connecting its equipment. In addition, Telit works with BMW as a client in its factories in Africa and the United States and has Ford as a client with factories spread around the globe. EOS sells 3D printers to BMW, Audi, and Daimler, and Universal Robots sells cobots to 90% of all the OEMs, and even more to suppliers.
But, to meet and exceed the complex demands of the automotive industry and scale adoption, smart manufacturing technology vendors need to understand the unique automotive industry challenges, offer solutions with obvious business cases, and have a stakeholder management strategy for all involved parties. “As in many other industries, automotive manufacturing faces the challenges of bridging the gap between IT and OT and providing low-code or no-code tools for content creation, app development, and logic configuration,” Owen explained. “Technology vendors targeting the automotive manufacturing industry need to understand that while automotive shares many challenges with other industries, it often takes them to extremes. For example, while all industries struggle right now to deploy new technologies and integrate them with current processes, the magnitude and complexity in automotive manufacturing present greater risks. One minute of downtime in automotive can cost tens of thousands of U.S. dollars.”
If smart manufacturing vendors hope to scale their solutions and platforms in automotive, they must guarantee and prove that they can provide value. “Automotive manufacturing deals with relatively high-value, high-volume and high-complexity products. Neither automotive OEMs nor their suppliers will take gambles on unproven technologies when it comes to their production lines. Vendors must define, prioritize, prove and present their business case before approaching this sector. If they can do so and show potential automotive clients exactly how to implement and integrate their technology without disrupting production, this market will adopt and scale the solution,” Owen concluded.
These findings are from ABI Research’s Smart Manufacturing in Automotive report. This report is part of the company’s Smart Manufacturing service and Smart Mobility & Automotive, both of which include research, data, and Executive Foresights.