Smart Manufacturing in Automotive
|出版日期||內容資訊||英文 27 Pages, 2 Tables, 2 Charts, 1 Figure
|汽車產業的智慧製造業 Smart Manufacturing in Automotive|
|出版日期: 2018年11月15日||內容資訊: 英文 27 Pages, 2 Tables, 2 Charts, 1 Figure||
The automotive industry faces many of the same challenges as other industries such as bridging the gap between IT and OT and providing low-code or no-code tools for content creation, app development, and logic configuration. 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 down-time in automotive can cost tens of thousands of US dollars.
Automotive manufacturing deals with relatively high-value, high-volume and high-complexity products. OEMs in this industry generally design the vehicles, then outsource the production of many of the systems, sub-systems, and parts before assembling, painting, finishing and testing the final products themselves. Also, most vehicles now have options and extras that require slight alterations or reconfigurations to the assembly processes as well as the supply chain, and every new option, part or feature requires test cars for the production team to practice building it into the vehicles and for functionality testing.
Additionally, automotive OEMs tend to have fragmented internal organizations with few branches of management that take a holistic view of applying technology or innovation across the enterprise. This makes maintaining digital threads and digital twins from design through production to final products more complicated than most other industries.
How can Smart Manufacturing technology vendors tackle not only the vast number of problems that they solve in every industry but also take on the additional challenges that come with automotive? To do this, they need to go in with an understanding of the challenges, solutions with obvious business cases and a stakeholder management strategy for all the parties involved, from the factory floor workers and their unions to the OEMs' executives, IT departments and all the suppliers. Most of the OEMs and their suppliers know they need to transform. Competition will spur them onward, but each new technology needs to make business sense and not burn bridges with stakeholders.
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 US and 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. Even AR companies have started to work their way onto automotive production lines.
While automotive manufacturing may venture forth as a pioneer in scaling these technologies, it demands guaranteed or proven ROI before doing so. This holds true in the US more than most countries. 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.
The "Company profiles" section contains analysis of the positioning, strengths, and weaknesses of several technology vendors. This report examines the drivers, barriers, and potential of Smart Manufacturing in Automotive.