=Paper=
{{Paper
|id=Vol-2843/shortpaper021
|storemode=property
|title=Digital technologies Industry 4.0 (short paper)
|pdfUrl=https://ceur-ws.org/Vol-2843/shortpaper021.pdf
|volume=Vol-2843
|authors=Dmitry A Kurasov
}}
==Digital technologies Industry 4.0 (short paper)==
https://ceur-ws.org/Vol-2843/shortpaper021.pdf
Digital technologies Industry 4.0*
Dmitry A Kurasov
Kurgan State University, Kurgan, Kurgan region, 640020, Russia
naukka@mail.ru
Abstract. Digital technologies contributed to the emergence of Industry 4.0 and
are drivers of the fourth industrial revolution. The modern principles of Industry
4.0 radically change the traditional rules of production and competition. The
paper provides an analysis of digital technologies and an assessment of their
joint impact on the transformation of industry.
Keywords: Digital, Industry 4.0, Fourth industrial revolution.
1 Introduction
Soviet digital technology Industry 4.0, variation in the work of various authors, pre-
cursors: Internet of Things, Internet of Services, mobile devices, advanced interfaces
between human and computer, 3D printing/additive manufacturing, intelligent sensors
(sensors), Data Science, Augmented Reality and Virtual Reality/wearables, cloud
services [1].
At the national level, according to national and regional industrial digitalization
initiatives (on digitizing industry), the following programmes and initiatives are being
implemented: Industrie 4.0 Oesterreich (Austria); Made different - Facts of the future
(Belgium); Prumysl 4.0 (Czech Republic); Industrie 4.0 (Germany); Manufacturing
Academy of Denmark (MADE, Дания); Industria Conectada 4.0 (Spain); Alliance
pour l'Industrie du Futur/Nouvelle France Industrielle (Франция); IPAR4.0 National
Technology Initiative (Hungary); Industria 4.0 and Fabbrica Intelligente (Italy); Digi-
tal For Industry Luxembourg; Smart Industry (Netherlands); Smart Industry (Slova-
kia); Industria 4.0 (Portugal); Smart Industry (Sweden).
2 Internet of Things and of Services, mobile devices
The Internet of Things (IoT) in figure 1 is defined as a network of physical objects
supported by the Internet, the purpose of which is to integrate each object for their
interaction through embedded systems, network communications, server computing
and applications [2]. IoT and implementation of this technology in numerous indus-
*
Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribu-
tion 4.0 International (CC BY 4.0).
tries allows objects, including intelligent sensors, machine controllers and other digi-
tal technology objects, to communicate with each other, collect and access data, as
well as interact with users, other systems and applications, creating intelligent con-
nected environments. The use of IoT significantly increases the communication capa-
bilities between system objects, allowing the implementation of more intensive and
expanded data flows. The implementation of IoT in industry can consist in the use of
application packages [3] to solve technical calculations.
Fig. 1. Internet of Things concept.
Industrial Internet of Things (IIoT) is a subset of the Internet of things which be-
longs to such heavy industries as production, power, oil, gas, agriculture, etc. The
diverse objects of the enterprise interconnected by means IoT get to generate a huge
number of data (“big data”) at high speed.
Internet of Things features: obtaining a huge amount of data; tracking the location
of things accurate calculation of the route of travel; improving the environmental
friendliness of production; remote management of mobile devices complication of
interaction with devices; guessing desires with smartphones; a revolution in data ex-
change.
Internet of Services (IoS) acts as a gateway between consumers and manufacturers
[4]. An important element of this concept is that devices and people can act as a sup-
plier and consumer, which includes the case of the supply of services by one device to
another. The service IoS applies to both information technology products and tradi-
tional products. Consumers of these products receive services provided by the manu-
facturer through the products themselves connected to the Internet. IoS extends the
range of service distribution channels and enhances communication between the
manufacturer and the consumer. For example, Tesla's innovative automotive technol-
ogy allows owners to update their car's software through overnight updates on the
Internet.
Mobile devices. One of the important properties of mobile devices is their ability to
provide communication for objects and people moving in space. This connection
creates the conditions for their integration into an industrial automation system based
on IoT technologies and human-machine interfaces IoT. Mobile devices strengthen
Industry 4.0 in manufacturing, and the use of mobile devices in production sites and
beyond is essentially the next activator of Industry 4.0 after IoT. IIoT, mobile devices
and IoS will change every sector of industry and play a huge role in it.
Mobile devices used in the enterprise can have MES, ERP, PLM applications in-
stalled on them, etc. Such devices are useful in production conditions in such situa-
tions as the performance of construction and installation work, their monitoring and
quality control of execution at complex technical facilities. For example, installation
of equipment, pipelines, routes of ventilation systems, power supply, control and
alarm systems at shipbuilding facilities. In this case, quick receipt of working docu-
mentation at the site, the use of mobile augmented reality tools to carry out markup
and compare the actual spatial configuration of the installed physical system with the
visual reference model of technical documentation will significantly increase eco-
nomic efficiency. The modern megatrend 5G and IIoT can take Industry 4.0 to a new
level.
Advanced human-computer interfaces. As Industry 4.0 takes industry to a new
level, there is a need for new types of interfaces to ensure uninterrupted interaction of
all involved persons, improve accuracy and speed of problem resolution. New inter-
faces need to be more sophisticated to increase efficiency and remoteness of opera-
tions, especially when workers interact with technologies in difficult industrial condi-
tions. Since operators are involved in the production process, the human-machine
interface of the system should provide a way of communication in which commands
can be easily entered. Based on these requirements, new types of man-machine inter-
faces are created, which include advanced touch interfaces, voice interfaces, sign
interfaces, and AR/VR glasses.
3 Аdditive Manufacturing and intelligent sensors
Additive Manufacturing (AM) or 3D printing is the process of creating objects from
three-dimensional digital models by adding a corresponding layer of material after the
previous layer [5]. This technology minimizes raw material waste and allows the
manufacture of complex molds without tools and cutting tools. In addition, additive
manufacturing stimulates the production of personalized goods on demand, as well as
custom building strategies. Many steps, such as engineering, planning, and manufac-
turing, are required to convert raw materials into traditional products. 3D printing
qualitatively changes and reduces the number of these stages. This is most pro-
nounced in products with complex geometry. AM is currently used in a number of
industries, including aerospace, automotive, biomedical, instrumental, jewelry, food,
etc. In intelligent factories of the future, where all processes are connected by the
Internet of Things, AM will contribute to greater decentralization, flexibility and indi-
vidualization of production processes.
Existing 3D printing machines make products in various ways: chemical agent
(binder), extruder (molten yarn) or laser (sintering/melting). The use of materials
includes the use of metals, polymer composites, ceramics, wood, fibers and compos-
ites, concrete and many others [6].
The use of 3D printers and 3D scanners has opened up unique possibilities for re-
producing the most complex spatial forms, objects, engineering structures and
mechanisms in many areas of science and production - for example, in the aerospace,
automotive, oil and gas industries, aircraft engineering, instrument engineering, de-
sign, mechanical engineering, metalworking, medicine, jewelry.
Intelligent sensors. Existing sensor technologies used by measurement, control and
automation systems are mainly based on physical measurement. Shape and distance
measurements are crucial for robots; flow and temperature measurements are wide-
spread in process control. Sensors cover such areas as heating, air conditioning and
ventilation systems, refrigeration equipment, technological processes, monitoring and
forecasting maintenance of equipment, hydrostatic level in tanks and management of
raw materials, availability and quality of raw materials, frequency characteristics of
vibration, pressure drops, detection of unauthorized access, speed and acceleration of
movement, etc.
The next step in the development of sensor technology will be the creation of sen-
sors for spectral scanners of materials. The collection by such sensors of qualitative
and quantitative information on chemicals and materials and its entry into the data-
base in real time will significantly improve automatic management solutions. For
example, the use of spectral scanner sensors in pipeline collective transport systems
for liquid hydrocarbons.
The sensor platform is only one part of the industrial system. Its full potential can
be realized only when used together with IoT, cloud technologies and machine learn-
ing.
4 Big data and science, Augmented and Virtual Reality
Big data analytics. Big data science Industry 4.0 in figure 2 is the use of digital tech-
nologies for data management and analysis. Big data can be considered in four di-
mensions: volume, diversity, value and speed. Industrial big data is characterized by a
variety of composition and a high degree of distribution of sources [7], which include
a wide range of types of technical devices, product lifecycle, enterprise operation,
supply chains and external cooperation.
Big data industry analytics examines knowledge models with support for descrip-
tive or predictive and prescriptive modeling, complex event handling, alert generation
and triggers for actions, visualization of generated reports.
Fig. 2. Big data and science concept.
The modern market for big data analytics technology platforms is already unusu-
ally wide and includes products such as SAP Aleri Streamihg, Oracle Complex Event
Processing, TIBCO BusinessEvents IBM WebSphere Business Events for processing
complex events, and for creating visualization reports - IBM Watson Analytics, Fu-
sionCharts InfoSoft Global, Qlik View, etc.
Data Science professionals solve four main problems: converting the original
"raw" data into a form suitable for analysis; data analysis itself; interpretation of data;
application of data to practice.
Augmented Reality (AR) [8] creates a visual representation of the real human envi-
ronment, complementing it with a virtual one. Augmented reality works in real time
in the human environment and allows people to interact with both real and virtual
objects that are integrated in the view and connected to each other [9]. Industrial
Augmented Reality (IAR) is the application of augmented reality to support the indus-
trial process.
Today, five main areas of application of AR in industry are defined: human and
robot collaboration, maintenance, assembly, repair, training, product quality control
and structure monitoring. In the field of human and robot systems, AR is used to cre-
ate effective interfaces for interacting with industrial robots. In maintenance, assem-
bly and repair, AR improves the productivity and quality of work. During the training
process, users can find a powerful solution in AR to increase the level of their skills.
During product quality control and in monitoring of buildings and other complex
technical facilities, supervisors can notice any inconsistencies of the created ob-
ject/product to the reference electronic image using powerful and universal AR sys-
tems.
Virtual Reality [8] (VR) is an efficient technology that creates interactive 3D
worlds that exist in a given scenario and are controlled in real time. Everything in
these worlds is subject to the main rule is imitation of reality. Everything in these
worlds is subject to the main rule is imitation of reality.
When creating virtual reality programs, you need to take into account their proper-
ties [10].
Plausibility is the ability to maintain a user's sense of reality. Interactivity is user
interaction with the virtual environment. Machine generation is use high-performance
hardware. Accessibility to study is an opportunity to explore the virtual world with a
high level of detail. The effect of presence is the involvement of both the brain and
the body of the user in the process. The presence of all the listed properties in the
virtual world allows you to create a high-quality virtual reality with full immersion in
it.
There are several types of virtual reality: VR with a full immersion effect; VR with
a floor immersion effect; VR without immersion; VR with joint infrastructure; VR
based on Internet technologies.
Cloud computing. The implementation of enterprise systems in the environment of
Industry 4.0 places high demands on the resources of computer systems. The increase
in such requirements led to the emergence of the term Cloud Computing. The conven-
tional interpretation of the term cloud computing defines it as the availability on de-
mand of computer system resources, especially data warehouses and computing
power. This term is commonly used to describe data centers accessible over the Inter-
net. Big clouds often have functions spread across multiple locations. The cloud
server closest to the user in terms of connection is called an edge server.
Clouds can be limited to a single organization (enterprise cloud) or accessible to
many organizations (public cloud). The public cloud can be used under outsourcing
conditions in the following versions: software as a service (SaaS), platform as a ser-
vice (PaaS), desktop as a service (DaaS), database as a service (DBaaS), infrastructure
as a service (IaaS), data as a service (DaaS), etc.
Foggy calculations are used to reduce time delays, reduce instability, and increase
safety. Nebulous calculations refer to the processing power for analyzing data and
control functions based on large amounts of data obtained by IoT devices (IoT). The
nodes that perform such processing are typically located on the same LAN as the IoT
devices and typically have storage capacity and computing capabilities.
5 Conclusion
As a result, the following conclusions can be drawn. Digital technology products and
products currently mastered by the industry do not yet realize all the opportunities
described by the academic community. For example, the benefits of using intelligent
sensors digital spectral material scanners for the oil and gas industry can potentially
actually transform the sector of the collective oil pipeline market, but such technolo-
gies have not yet been created. Another example of a promising yet unrealized digital
technology is AR and VR for use in industrial and civil construction and shipbuilding
at the stages of design, construction of facilities, installation, assembly, monitoring of
work progress and technical acceptance.
Many of the existing digital developments are experimental and exist in the form
of research prototypes. The time required to develop digital technology from the crea-
tion of the first prototype to the launch of the product is approximately 20-25 years.
For example, the capabilities of new commercial products, such as Siemens Solid
Edge, allowing designers to create digital layouts for visual analysis of large assem-
blies that reduce the number of expensive physical prototypes, were demonstrated in
research prototypes back in the mid-1990s, in particular by the EDS virtual reality
laboratory. The digital technology products released on the market are more likely to
be the first experimental samples that solve private local problems, which are too
early to perceive as full-fledged digital blocks of Industry 4.0. Therefore, it is safe to
say that both the creation and practical implementation of full-featured digital tech-
nology products and the full-scale implementation of Industry 4.0 will take a long
time.
In the context of the transformation and transition of industry to complex produc-
tion and technological systems of Industry 4.0, the task of monitoring the state of
elements and processes of digital and production technologies is significantly compli-
cated. At the same time, there is a need to create methods and tools for conducting
large-scale integrated monitoring, diagnostics and management of the entire range of
Industry 4.0 technologies.
Industry 4.0 is slowly but surely entering our world. Industry 4.0 will make it pos-
sible to reach a new level of human development and quality of life. It will change the
attitude of people and people themselves.
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