Outlining the benefits of AI and the associated opportunities to reinvent its own products with digital technologies.2. Develop a vision on how existing offers can be complemented by AI.3. Provide the resources needed to develop AI-based products.4. Implementing their vision and concrete initiatives to enable December 2018 Calendar Spanish large-scale digital reinvention of products. If the companies studied are classified by industry and up-to-date for use in specific clusters, the level of maturity in the Artificial Intelligence industry is demonstrated to industry is very different.
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Automotive companies are more likely to be able to vigorously pursue and implement AI initiatives than others. After all, nine percent of the companies in the automotive industry already achieve the third and five percent even the fourth development stage. By contrast, manufacturers of industrial machinery are not yet ready. Only seven or three percent reach the third stage here. Only one percent is at Level 4, the highest stage of AI maturity.
The AI avant-gardists have one thing in common – that they work closely with ecosystem partners to identify the AI applications that are most beneficial to them bring the customer. Most companies rely on AI solutions such as machine vision (73 percent), deep learning (64 percent) and robot-controlled process automation (64 percent). In order to provide additional momentum especially for machine learning, the mechanical engineering association VDMA recently launched the working group ” Machine Learning “.
The VDMA Competence Center Future Business had already explored the topic extensively in 2017 with the study “Machine Learning 2030 – Future Images for Mechanical and Plant Engineering”. At the decision of the board of the Software and Digitalization Association, the VDMA should now present the topic in the new working group.
The user and provider bring together, continue to push “Currently 375 members in the VDMA Software and Digitalization Association show clearly the importance of digitization in mechanical engineering,” emphasizes Matthias Dietel, IBM Germany Lab and member of the board of directors of the association. VDMA Quick Guide: What can you do with AI Mechanical engineering companies that want to use machine learning, fra… be retrofitted in the short term, says the scientist.
A planning software from the same institute acts as a virtual operator that schedules, assigns, controls and monitors the entire manufacturing process. The concept of the system can also be transferred to other fields of application. Among others, FORTISS focuses on textile production. In the future, customers should be able to design their own clothing in the online shop. The order is then handled directly by the convertible factory.
Automotive: Deep Learning and AI in Engine DevelopmentThe German Research Center for Artificial Intelligence (DFKI), the world’s largest nonprofit research center for AI, and IAV, December 2018 Calendar Spanish one of the leading development partners to the automotive industry, are launching common “research laboratory learning from test data” (FLaP). In the new test environment at the DFKI in Kaiserslautern, special analysis methods of artificial intelligence for use in test procedures in automotive development are being researched and developed. Machine learning technologies, including deep learning and time series analysis, are used.