Chatbots and voice consultants have firmly entered the service sector. Although I thought a few decades ago that the electronic voice that solves your problems is a story from a fantasy book. These e-advisers are getting smarter with advances in computing technology and AI training methods. I give this example as the most clear and understandable to any person. Now back to manufacturing.

The main difference between the sphere of manufacturing and, for example, the sphere of trade is costs. So in the mass market, logistics, advertising and customer service occupy the main share of all costs. In manufacturing (we are talking about large-scale manufacturing), the main costs are raw materials and equipment. Consequently, the following tasks arise that reduce costs: to use raw materials rationally, to purchase materials of optimal quality, to extend the life of equipment. Artificial intelligence is able to cope with these tasks.

Irene, please give examples of the use of artificial intelligence in manufacturing.

For example, a film production machine selects the optimal temperature regime depending on the specified output criteria (film thickness, environmental resistance) and the viscosity of the solution. This rationalizes the use of raw materials and energy resources. A large production machine has vibrations. According to the characteristic peaks of the curves that correspond to these vibrations, the engineer receives a message about the replacement of a particular part. Timely repair of the unit helps to avoid costly repairs. And it is often simply impossible to manually check the production machine due to forced downtime.

What are the most common challenges to making manufacturing smarter?

I highlight two issues. This is management and data. Often the management does not want or does not understand why they need to introduce technologies in manufacturing. It seems to them that there are more significant problems, and this will have to wait. But it is still waiting until more modern competitors are forced out of the market or the costs of manufactoring are higher than income.

The second problem, as I said, concerns the set of data. Everything is simple here. Often it just don’t exist. In order to implement technologies based on models, these models must be created. At the heart of everything is the accumulated experience, which can be digitized. That is, in addition to interviewing personnel, a system of sensors is also needed that will capture the necessary information.

Will manufacturing be smart or is it a failed strategy?

They are already smart and will get smarter in the future. I am optimistic. As practice shows, everything rests on the development of technology. Old technologies are being replaced by new ones. Technology is becoming cheaper and therefore more accessible. Yesterday there was a floppy disk, and today it’s an SSD disk. The development of wireless communications, the Internet of things, and so on contributes to the creation of smart manufacturing. The main task of a consultant in the field of digitalization of manufacturing today is to convey the need for this entire process to manufacturing management.

by Risher Panir,

CounselSenses

The post Expert opinion about Future of Smart Manufacturing appeared first on strategAI.

In 2003, Moore admitted that exponential growth was not possible in the future due to technological constraints. In 2007, he announced that the law would end soon. The number of transistors on an IC is mainly changed by decreasing their size. However, the reduction of the classical transistor leads to undesirable effects that are caused by the dimensional limits. In addition, the IC manufacturing technology also has its limitations. Device designs have to be constantly improved or breakthrough technologies have to be offered. Scientists and engineers are working on the creation of new designs, but the limit of semiconductor technology will be reached. Fundamentally new approaches are needed. For example, spin transistors are investigated, where the principle of operation is shifted from an electron charge to magnetic moment.

One of the main conclusion from this law is with an increase in processor power, the cost of computing equipment falls. Over the past 50 years, the cost of manufacturing a transistor has dropped thousands of times. Computers are now available in every home. Hence our time is called the digital era. We cannot imagine modern business without software for automating business processes. And all traditional marketing has been replaced with digital. AI, big date, remote work, all of this appeared only thanks to the development of electronics.

Moore himself refuted the work of his law in the future. Does this mean that we have reached the limit? There are many development options. For example, new materials (2D) are being actively studied by researchers around the world. Two-dimensional materials are not much more than 10 years old, and there are already a large number of solutions for electronic components based on this. New technologies and new fundamental principles of work will help to overcome this limit for sure.

¹Gordon Moore is one of the founders of Intel.

²The transistor is the main component of any electronic device. It is used for generating, switching and converting signals. Most often the transistor is made from semiconductors (semiconductor technology).

³Eugene Meieran is Intel engineer.

by Maria Baranova

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