Why and why the transition to digital technology is needed

Never since the First industrial revolution in the eighteenth century have technology played such an important role in people’s lives and economic activities. The latest wave of new digital technologies includes the Internet of things, artificial intelligence, digital immersive environment, cloud computing, cybersecurity, big data Analytics and machine learning.

Proposed in 2010 by the German government, the term “industry 4.0” — or the fourth industrial revolution — means the most advanced tools with advanced logic and automated methods for creating, storing and using data that hold tremendous opportunities to improve the efficiency of industrial and economic activities. Let’s take a closer look at some examples of such technologies and how they help to optimize production processes.

Environment immersion: fostering cooperation and reducing the risks

Given the very close entry into the market of products such as Oculus Rift from Facebook and Holo-lens from Microsoft, as well as Apple’s announcement of the beginning of intensive work on virtual reality technologies, the method of immersion environment has every chance to become the next largest technology platform. Operations services can interact with a programmable model that will respond to conditions in the same way as their object, thus enabling organizations to test high-risk scenarios and understand how to mitigate risks without jeopardizing the real object.

Virtual models are very useful for companies that have several simultaneously functioning objects, as they allow teams on these objects to cooperate with each other remotely with greater efficiency. In organizations with high reliability requirements, the area of risk is personnel training — immersion environments completely transform the process of instructing employees before they enter the high-risk area, and thus significantly reduce the risk of serious injury and industrial accident.

Artificial intelligence: the liberation of the people

120 300x135 - Why and why the transition to digital technology is neededWhat is artificial intelligence? In simple words, the term “artificial intelligence” refers to the machines, able to perform tasks which usually previously required human intervention, for example, decision-making, taking into account all available information. However, instead of displacing people, artificial intelligence is more likely to free people, increasing overall efficiency and allowing them to move on to other, more interesting tasks.

For example, Siemens has an automated factory where the lights are turned off completely at night. But much less media coverage of the fact that to support the operations of the plant used the work of more than 1,000 employees. So, instead of being a normal addition, “reasonable” automation today fundamentally changes our understanding of the structure of it systems. More and more tools are being created that, by serving as a new foundational layer of it architecture, increase the complexity of machine intelligence in learning and decision making.

Machine learning: new approaches to data organization

What can you say about an advanced machine learning? This is where deep neural networks (STS, a set of algorithms that mimic human recognition of sensory data sets) far surpass the classical computational process and information management techniques to create systems capable of self-learning and knowledge of the world. Due to the rapid increase in data sources in the industrial environment and the high level of complexity of the information obtained, manual classification and analysis become impractical and more costly. STS automate these tasks and address the most significant issues related to the development of the “Internet of everything”.

The Internet of everything: data becomes meaningful

Today, the world has moved from the Internet of things to the “Internet of everything”: everything that produces, uses and transmits information on an electronic network. In addition to text, sound and visual data, the Internet will be enriched with sensory and contextual information. The “Internet of everything” refers to this information flow through strategies and technologies that link data from different sources. But what is the main benefit? If this information existed before, it was fragmented, incomplete, inaccessible, or incomprehensible, making it useless. Progress in the use of semantic tools such as graph databases and other advanced data classification models and information analysis technologies will make it possible to extract more sense from the stunning information flows.

Energy-saving technologies: growth of economy from year to year

In the industrial sector, energy accounts for about 15 per cent of current expenditure. Optimization of performance can reduce this parameter by 10-20 percent, while investments in energy-saving technologies can reduce it by almost half, which is already a significant saving. For example, the cost of environmental controls in clean production facilities can be reduced by 20-50 percent of the original energy consumption. Most of these technologies are already available — now it’s up to companies to understand which ones are best suited for their business, how to implement them correctly and how to ensure their continuous development to continuously increase savings. These technologies include inter-industry systems for monitoring and controlling energy consumption, smart grids and in-depth data analysis, as well as special technologies such as evaporative cooling systems in advanced industries used to control air humidity.

What to consider before investing in digital technology

Before you decide which technologies will give a greater return on investment, you should think about this:

Technology, however advanced, has its limitations. It is very important to critically assess the limits of technological capabilities in order to set high but realistic goals.
First, perform a deep statistical analysis, and then make a decision; estimate the ratio between such components as the result, energy consumption and environmental impact.
A combination of factors such as changes in thinking, behaviour and management systems will provide the best possible effect from the application of the technology.