Hi everyone. Today we will talk about the challenges that manufacturing industry faces, what are disruptive technologies that help in addressing those challenges, and how these technologies are changing the entire science and technology landscape, business models, and even the mindsets of people involved in the process. Disruption technologies became a buzzword over the last decade. When we hear it, we always think of something very innovative that brings many changes, but what exactly does it mean? Innovations can be sustaining and disruptive. Sustaining innovations don't affect existing markets. They can be evolutionary which means improvement of existing products and technologies, and revolutionary which is about something that occurs unexpectedly, like a new product or a solution for example, but also it doesn't affect existing markets. Disrupting innovations on the other hand, creates a new market by providing a different set of values and rules of the game which ultimately and unexpectedly overtakes an existing market. There are many examples of disruption in the history of mankind; book printing, telephone succeeding telegraph in the communication market which succeeded postal delivery earlier. Cars changing the approach to transportation, which is also true for railways and airplanes, and of course personal computers and Internet. Today, the list of technologies which are called disruptive varies among different research groups, consulting agencies, and business entities such as for example, McKinsey, Deloitte, Gardner, Amazon, MIT, and many many others. Some of them focus on socially significant innovations such as life extension and gene screening. Others focus on computer technologies, Cloud and quantum computing, and some emphasize on manufacturing technologies, for example, robotics and 3D printing. Here you can see the list of 12 disruptive technologies from McKinsey. As you see, these technologies are quite diverse; mobile Internet, genomics, 3D printing, oil exploration. For now, let's focus on those which are particularly important for manufacturing and have a closer look at them. At present, manufacturing is facing a need of continuous improvement. Quality requirements increase with the demand for personalization and customization of end products and services. Globalization adds even more pressure here. All this leads to a drastic increase in product variety and manufacturing complexity, but at the same time, safety has to be maintained at the same or even higher level. To respond adequately to these challenges, manufacturing systems have to be updated to an intelligent level and lead to flexible, smart, and re-configurable manufacturing processes. The essential element of smart factories are industrial Internet or things, and machine to machine communication, when manufacturing equipment can exchange data about current processes, delays and breakdowns, and even make decisions based on this information. For instance, to switch off the broken machine and assign its task to another machine while this one is getting repaired. The degree of automation increases even more with the use of cobalts and unmanned vehicles. Need for processing and analyzing enormous volumes of data inevitably means applications of MES, SCADA, ERP , PLM, PDM, and other information systems to ensure quick and transparent data-flows throughout the whole value chain and all product development stages. The manufacturer is not only responsible for providing a product, but also for it's stable performance throughout its entire life cycle. Not only to ensure stable performance in present, but also forecasts the performance in future in different situations and use cases. All this is becoming possible with the concept of digital twins; virtual representation of a physical product or a process used to understand and predict the physical counterparts performance characteristics. The real object is equipped with sensors that provide real-time data about its performance, which is then sorted and analyzed. Digital twins are used throughout the product life cycle to simulate, predict, and optimize the product, and the whole production system, and processes before investing in physical prototypes and other assets. Digital twin is not about one particular technology, but rather a whole set of technologies including multiphysics simulation, big data analytics, sensors, machine learning, artificial intelligence, and even augmented reality. One of the essential elements of this intelligent manufacturing environments is additive manufacturing. The term additive manufacturing can be defined as the process of joining materials to make objects from 3D model data, usually layer upon layer as opposed to subtractive manufacturing methods. Synonyms include additive fabrication, additive processes, additive technologies, additive layer manufacturing, and many others. Key advantages of additive technologies is the ability to create sophisticated objects with advanced properties, new materials or shapes, whatever, which could not be manufactured before and allow for example, substantial mass and weight reduction. Additive technologies are already used in various industries such as airspace and medicine. For example last year, General Electric claim to have used an additively manufactured bracket on a commercial airplane engine. Brackets on those engines which power the Boeing 747, were milled a solid block of metal resulting in approximately 50 percent of material waste. With an improved design and using metal 3D printing in cobalt-chrome, the waste has been reduced by 90 percent and the weight reduced by 10 percent. Another crucial technology for a smart manufacturing plant is advanced automation and advanced robotics. Automation is actually nothing new to manufacturing world and it's widely used for decades. However smart factories go beyond simple automation compared with conventional robots. Advanced robots have superior perception, ability to integration and adaptation, and of course, mobility. These improvements allow faster setup, commissioning, and reconfiguration, as well as more efficient and stable operations. A deep analysis by Boston Consulting Group shows that using advanced robots can reduce conversion costs by up to 15 percent, and combining advanced robotics with other technologies, process enhancements, and structural layer changes can yield savings up to 40 percent. Thanks for now, and see you next time.
