Machine Learning Maximizes Manufacturing Margins

Software, data, information, communication and automation through Machine Learning (ML) and Artificial Intelligence AI) are at the core of today‘s most valuable companies in the world. Still, humans need physical goods that must be manufactured, distributed and sold in real physical supply chains. We bring these two worlds together and combine speed, power and agility of data, software and ML with professional experience and real-life operation of physical supply chains. In leading operations, many mass decisions are already automated on a super-human level. Such scalable and industrialized ML applications deliver large value and competitive advantage, especially in these times of increasing speed and uncertainty. The recipe is to optimize and largely automate standard processes to give agility and let humans concentrate on strategic steering and exception handling, ML supporting them with as much foresight as possible: 'predict and pivot' instead of 'read and react.' Michael will show concrete examples of existing and future applications of this principle in manufacturing.

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