Global experience of implementing projects in the field of the Industrial Internet of Things (IIoT). Examples of the implementation cases

December 2016

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Global experience of implementing projects in the field of the Industrial Internet of Things (IIoT). Examples of the implementation cases
Global experience of implementing projects in the field of the Industrial Internet of Things (IIoT). Examples of the implementation cases
December 2016

Global experience of implementing projects in the field of the Industrial Internet of Things (IIoT). Examples of the implementation cases

December 2016

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In the present study J'son & Partners Consulting analyze and systematize examples of the implementation of the Industrial Internet of Things by the world’s largest industrial companies in various sectors of the economy.


A team of leading analysts of J'son & Partners Consulting has collected data on the successful IIoT implementation cases in industry (60 examples) and in other sectors of the economy (over 30 examples).



Key factors, influencing the development of industrial Internet of things


One of the main directions of the strategic development of the world’s leading countries is the digitalization of all spheres, including the sphere of manufacturing industry.


The development of new generation information and communication technologies in the last decade gives unprecedented opportunities to industrial enterprises in terms of transition to a brand new level of production process efficiency.


The introduction of modern information and communication technologies in production processes contributes to the practical solution of such important tasks as:

▪       increase of production efficiency;

▪       increase of equipment efficiency;

▪       reduction of material and energy costs;

▪       optimization of labor expenditures;

▪       improvement of working conditions;

▪       improvement of the product quality;

▪       improvement of competitiveness in the global market.


Almost all leading players of the world market in the field of automation, intelligent management and Hi-Tech are focused on the development and practical testing of pilot and commercial projects in the industrial sector through: the application of modern technologies of building large-scale computer networks, the application of new methods and products for processing large amounts of data and the development of cloud solutions.



An important role in the development of this promising concept is played by the global companies like:

▪       Cisco;

▪       ABB;

▪       GE;

▪       Emerson;

▪       Siemens;

▪       Bosch;

▪       Rockwell Automation;

▪       Dell;

▪       Mitsubishi Electric and others.


In this regard, the most valuable is the analysis of best practices of the implementation of IIoT projects, as well as identification of the key areas of this technology development along with the most marketable products and services.



Global trends of transition of various economic sectors to the use of the IoT models.


World industry today stands on the threshold of the fourth technological revolution, which is related to the possibility of radical modernization of manufacturing and economy, as well as the emergence of phenomena such as digital manufacturing, so-called shared economy, collective consumption, "uberization” of the economy, cloud computing model, distributed networks, network-centric model of governance, decentralization management etc.


Industry 4.0, technologically based on the Internet of things (IoT) is a completely new form of work organization and business models of service provision. In the most advanced variant it is a fully digitized and automated manufacturing, which is driven by intelligent systems in real time, without human intervention. It is a manufacturing process which goes beyond a single enterprise and which can be unified in the global industrial network of things and services in future.


In fact it is a cloud model of a plant, in which the entire manufacturing process and product life cycle are recreated in the virtual space – from concept, project, design, to manufacturing, delivery to the end-customer, operation, maintenance and disposal.


Digital copy allows to establish (before manufacturing) an optimal production, logistic and resource chains, calculate their cost and optimize them: choose the optimal supplier, choose the shipping company, as well as the optimal materials. It becomes possible to promptly make changes in the production process at any stage, to re-equip the equipment, to conduct a flexible changeover, change the product functionality. In case of combining several companies into a single network, the efficiency and capacity of manufacturing are multiplied.


In the cloud model of manufacturing and service provision it becomes possible, instead of selling a car or tractor to a person, to sell (through subscription) only its function, when the buyer only pays for mileage, or the area of the plowed field. The maintenance, repair, fueling and other operational tasks are up to the manufacturer. Thus we can achieve a drastic reduction in the cost of ownership for the buyer and the best way of utilization of products and means of production for the manufacturer (read more in the Study).


Industrial Internet of things radically changes the whole economic model of the interaction between suppliers and customers that allows you to:

  • automate the process of monitoring and equipment lifecycle management;
  • organize effective self-optimizing chains from suppliers to companies which are end users;
  • go to the "sharing economy" and much more.

In the most advanced cases, the industrial Internet of things allows us not only to improve the quality of technical support of the equipment using developed means of telemetry, but also to ensure the transition to the new business models when the equipment is paid by the customer upon use.



The global IIoT market prospects in industries


Many specialists of international analytical agencies forecast a wide application of the IoT concept of the in various industries.


The company Ovum predicts that the total volume of connected devices used in various segments of the global economy, will reach about 530 million units in 2019, with the greatest number of such devices in the field of energy and utilities, transport, manufacturing industry, health and trade.


Source: Ovum, Machina Research, Nokia, 201


The continuing reduction of prices for sensors and equipment, communication services, data processing and system integration will be the the first key growth driver, while the reduction of costs and increase of revenues in enterprises, which implement innovative solutions, will be the second (see interview with Alexander Anufrienko: «Industrial Internet in Russia»).


According to Machina Research and Nokia, the of the global IIoT market revenues will reach 484 billion euros in 2025, and the main represented sectors will be transport, manufacturing industry, housing, healthcare and smart home applications. The overall assessment of both customer and corporate IoT market in the world are estimated by Machina Research and Cisco at 4.3 trillion dollars in 2025.



Typical results of the IIoT projects


Generalization of the results analysed in the study of IoT projects shows that one important result achieved by its introduction is the opportunity to fundamentally change the entire economic model of the interaction "supplier – consumer".


First, the use of sensors monitoring the equipment with access to the Network allows the equipment manufacturer to remotely control its operation, to carry out maintenance work, to predict accidents and to conduct preventive maintenance or to prepare in advance all the necessary replacement parts, etc. So we're claiming that the Internet of things is an effective tool for managing the product life cycle.


Secondly, the knowledge about the actual and planned utilization of equipment connected to the Network, allows to organize an automatic network of orders between different industries in the long chain, from suppliers to consumers of final products. This is accomplished by connecting all locations to one software platform, and its members may be legally different companies. This model radically streamlines the transaction costs in cooperative chains, which become self-optimizing. In other words, the application of the IoT concept allows you to maximize cooperation for the whole chain of participating enterprises to achieve the most cost effective result for end users.


Thirdly, it concerns the transition from selling devices and equipment, which are measured in figures of the delivered equipment, to the model of selling functionality (usage results) of devices and equipment "on demand". For example, when a company sells not just compressors but compressed air with clearly defined and guaranteed parameters. Thus, in the most advanced cases, we talk not just about a brand new hardware support quality level (with the use of developed means of telemetry), but about different business models of its operation, when the equipment does not transmit the property of the customer  and the only thing they pay for is the use of its functions. This principle can be seen at:


  • the largest provider of industrial compressors Kaeser – compressor equipment payments are taken according to the volume of produced compressed air;
  • manufacturer of agricultural machinery John Deere – you pay for the actual time of use of agricultural machinery (tractors);
  • many other leading manufacturers of industrial equipment and consumer technics described in the report.


It is important to note that selling "on-demand" is a key characteristic of cloud services. Internet of things acts as the necessary technical component for the cloud model expansion beyond the information and communications industry. In those industries, where ICT equipment is not a final product, and computing and communications systems are used as accessory (to computerize control over other types of equipment and devices, so called embedded systems), the cloud computing model becomes the life cycle contract, that is, a brand new model of relationships between suppliers and consumer.



A typical result of an IoT project is a multiple increase in the efficiency of all participants of the IoT ecosystem, not only in the field of ICT and finance, where the product can be created and consumed entirely in digital form, but in the material production sectors. Moreover, while the scale of such ecosystems grows, their efficiency is growing too, in contrast to the traditional cooperative chains, where the expenditures grow exponentially to the number of employees.


The consequence of such typical results of IoT projects is increase of the competitiveness of all the IoT ecosystem participants in terms of labor division and increase of their shareholder value, when a "traditional" company which is undergoing the IoT transformation, achieves the efficiency level comparable with "technology" companies, and starts being evaluated by investors as a cloud/technology companies such as Google, Amazon, and other.


The shareholder value dynamics is the main financial result of the transition to business models based on the principles of IoT.



Priority sectors for implementation of IIoT decisions


The report deals with the practical results of the IIoT projects abroad. The study also includes examples of successful IIoT projects in key sectors such as:

▪       mining;

▪       oil and gas industry;

▪       chemical industry;

▪       metallurgical industry;

▪       pulp and paper industry;

▪       food industry;

▪       furniture industry;

▪       pharmaceutical industry;

▪       microelectronics industry;

▪       construction materials industry;

▪       car manufacturing;

▪       engineering.


The analysis of the best global practices shows that the main fields of application of IIoT solutions are industrial facilities, characterized by the presence of one or more of the following important conditions:

▪       manufacturing of a wide range of products with use of a significant list of components;

▪       the need to improve product quality and reduce scrap;

▪       the need to ensure effective service maintenance of delivered products;

▪       the need to reduce operating costs of production;

▪       considerable energy intensity of production;

▪       difficult production conditions;

▪       the need for operational diagnostics of malfunctions of the technology equipment to reduce unplanned production stops;

▪       the need for high staff performance;

▪       the need for staff security;

▪       the need for a system integration of wide range of process equipment from different manufacturers within a single production complex.


Special attention in the research was paid to the analysis of practical results of the projects in the field of industrial Internet, obtained at the enterprises of the largest multinational companies. In particular, the authors discussed in detail the results of the implementation of these technologies at the enterprises of global corporations, such as:

▪      Akzo Nobel;

▪      BASF;

▪      Boliden;

▪      Bosch;

▪      British Petroleum;

▪      Coca-Cola;

▪      Daimler;

▪      General Electric;

▪      Goldcorp;

▪      Honda;

▪      Intel;

▪      Konecranes;

▪      Nestle;

▪      Osram;

▪      Potash Corporation;

▪      Pirelli;

▪      SKF;

▪      SEAT;

▪      Siemens;

▪      The Anglo Platinum Group and others.



Implementation of the best world practices in the field of IoT projects in Russia


Technological systems and equipment of the industrialized countries are intelligent and united. Enterprises are integrated in global industrial networks to combine the network of production resources and global applications.


Modern industrial leaders abroad have already digitized, connected to the network and robotic equipment, provided with sensors and IT-systems. Over the past 10-20 years in the conditions of the production process transformation, many companies have been mastering new ways of managing, analyzing and applying of received data (Big Data) to achieve higher efficiency. Currently, global manufacturers are moving in the direction of scaling and implementation of artificial intelligence in manufacturing which can completely exclude human beings from routine processes. Use of new digital control models goes far beyond the information and communications industry, and IoT becomes a necessary technical component for implementing IoT projects in various sectors of the economy.


State innovation and industrial development programs in many countries rest on the notion that innovative industrial technologies can strengthen all sectors of the economy.


In this regard, for the domestic industry there appear new opportunities and threats: the exponential gap of efficiency and production quality can be added to the lag in the transition to new principles of the chain "supplier – consumer". This can lead to fundamental inability to compete with leading international industrial corporations, both in the cost of production and order execution speed.


The main challenge in the medium term in the absence of adequate measures for Russia is the threat of loss of competitiveness on the global markets and the growing gap in terms of productivity from the U.S., from the fourfold in 2015 to more than tenfold in 2023; in the long term the prospects are even sadder. The can emerge an almost insurmountable technological barrier between Russia and the leading technological states, which implement efficient technologies and service deployment models, and which try to combine the ICT infrastructure and software applications such as network functions virtualization and automated software management. This can lead to technological isolation and degradation of the Russian Federation.


In the optimistic scenario, the emergence and rapid implementation of innovative business and service models in the IoT ideology, with state support and accompanied by research and development, and the ability to create an open and competitive economy, by technical means based on a fundamental change in the role of ICT in the management of production enterprises, will be the key point of growth of the industry and economy of Russia for the next three years.


If to consider that in terms of productivity, that is, the integral indicator of resource use efficiency, Russia is 4-5 times behind from the US and Germany, the growth potential of our country is a multiple higher than the so-called developed countries. And this potential must be used through the joint, well-coordinated efforts of the government, business players, academic and research organizations.


Different forms of cooperation between the government, science and business (manufacturing companies, in particular) have a huge importance for the exchange of knowledge, technology, ideas and the implementation of joint projects in complex ecosystems and in the need to involve partners with different specialization.


Obviously, the economic crisis will push Russian businesses to implement efficiency projects. Given that the transition to the IoT model allows to significantly increase it, with almost no capex on modernisation, we can expect that this year we will see many successful IoT projects in Russia.


Analysis of the results of the implementation of the most successful practices in the field of industrial Internet shows that the payback period of such projects in most cases does not exceed several months.


IIoT projects are implemented or planned to be implemented by almost all the leading global players in a wide range of industries. While special attention is paid to the introduction of these technologies in such key Russian economic sectors as mining and chemical industry, metallurgy, machinery, oil and gas sector.


Thus, adaptation and implementation of the most successful international practices in the field of industrial Internet for domestic enterprises are critical as it is one of the most important conditions for achieving competitiveness in domestic and foreign markets.



Examples (cases) of the implementation of projects of industrial Internet


Case 1: Akzo Nobel


Company, country

Akzo Nobel

Chemical enterprises in various countries around the world


Improving the efficiency of the Akzo Nobel enterprises


The company Akzo Nobel is one of the world's largest manufacturers of a wide range of chemical products.

The company has over 200 production sites in more than 80 countries, the total number of the employees is about 50 thousand people.

Due to the broad geographical presence of the company, the optimization of its labor resources and ensuring effective interaction between its subsidiaries in different countries play an important role,.

The essence of the project, description of the implemented functionality

To improve the efficiency of business operation, the company implemented cloud technologies for collecting, storing and analyzing data.

Description of the applied technologies and solutions

The enterprises of Akzo Nobel operate GE intelligent platforms and its software called Proficy, as well as a number of products from such vendors as Accenture and SAP to develop the corporate Program to manage information processes of the company (EPI – Enterprise Process Information Connected Program).

Implementation of the program allows to place all data in one Central cloud-based server located in Amsterdam, instead of using 4-5 servers at each plant.

In particular, the EPI Program is used by Akzo Nobel for remote management of an enterprise for the production of hydrogen peroxide located in Norway, from Sweden.

These technologies allowed to partially abandon the constant presence of personnel. The plant operates continuously 24/7 and on weekdays is controlled remotely from the office in Sweden on a distance of 500 km The staff is at the factory only during the weekends.

The number of connected IoT devices and volume of data they generate

The EPI program has been implemented in more than 100 enterprises of the company Akzo Nobel.

The total number of users connected to the software exceeds 2000, and the daily number of transactions of data transfer is several billion.

The project results and economic effect

During the project implementation the following results were achieved:

▪      the cost of labor production significantly reduced due to the staff reduction;

▪      the costs of functioning of the company’s informational infrastructure significantly reduced due to the transition to the cloud model and eliminating use of a significant number of local servers in enterprises;

▪      technology processes optimized.

Plans for the development of the project

Cloud solutions are implemented at 30 production sites of the company Akzo Nobel.

In the near future these technologies can be implemented in 10 more enterprises of the company.



Case 2: General Electric


Company, country

General Electric, Atlanta, USA

Remote monitoring and data analysis center


Monitoring of gas turbines located around the world, in continuous mode


One of the key challenges while operating complex technical equipment is to prevent unplanned stops, as well as receiving timely data about its condition in real time.

It requires expensive software products, technologies of data collection and processing, and the availability of highly qualified specialists.

The essence of the project, description of the implemented functionality

To reduce the costs of clients who operate gas turbines worldwide, GE introduced and tested in practice a system for remote turbine condition monitoring.

Description of the applied technologies and solutions

For collecting and analyzing data on technical condition of turbines the company uses its own system called Enterprise Historian System.

The obtained data on the turbine operation get to the GE data center, where a team of more than 20 professionals monitors them and makes operational decisions in case of a need to service or repair.

The Enterprise Historian System solutions are protected by 15 patents.

The number of connected IoT devices and volume of data they generate

The total number of continuously monitored gas turbines is 1,600 units.

The total volume of information processed with use of the Big Data technology includes different parameters obtained under 100 million hours of turbine work.

The project results and economic effect

During the project implementation the following results were achieved:

▪      the transition from batch to continuous data transmission;

▪      significantly reduced labor costs for collection and analysis of data;

▪      the required server capacity for data storage is reduced by 10 times;

▪      the cost of development and operation of databases was reduced four times;

▪      the cost for unloading and use of data is 10 times reduced;

▪      the flexibility and efficiency of labour resources increased. Total savings of the staff salaries are estimated at 9 million USD per year;

▪      the cost of software development by third-party developers reduced by 3 million USD;

▪      cumulative benefits for the users of these turbines are estimated at 100 million USD per year.

Plans for the development of the project

This system can be successfully scaled for a much larger number of turbines, issued by GE and operating worldwide.



Case 3: Sierra Gorda


Company, country

Sierra Gorda, Chile

Mine production of copper and molybdenum ores


Improving the mine performance, increase of safety of working conditions, staff cost reduction


The Sierra Gorda project is a joint venture of KGHM International Ltd., Sumitomo Metal Mining and Sumitomo Corp.

Total investment in the development of the mine amounted about 3.9 billion USD, the number of employees is more than 2000 people.

An important condition of the company is ensuring the smooth operation of the wireless network. Given the fact that the exploitation is carried out in difficult conditions (high temperatures, vibration and dust), the construction of a united high-performance network was a challenge.

The essence of the project, description of the implemented functionality

Sierra Gorda, together with Cisco implemented a project to build a unified information infrastructure of the mine with the transition to the IoT principles.

Description of the applied technologies and solutions

The company has implemented the following Cisco products:

  • Cisco® Connected Mining platform;
  • wireless access points Cisco Aironet 1500;
  • wireless network controllers Cisco 5508 Series Wireless LAN;
  • switches Cisco Catalyst 3750X and 3560X.

Cisco products allowed to resolve the following important tasks of the enterprise:

  • effective communication with all staff located in the field, through use of handheld mobile devices;
  • use of the Cisco® Connected Mining platform has allowed to integrate all information flows into a single reliable multiservice IP network ensuring uninterrupted access to IT from any working device in each period of time;
  • reliable communication channels man-to-man, man-to-machine, machine-to-machine are set.

The number of connected IoT devices and volume of data they generate


The total number of connected employees is 2000.

Also several dozen pieces of mining equipment are monitored.

The project results and its economic effect

During the project implementation the following results were achieved:

  • monthly savings of labor costs through optimized use of labor resources of one brigade, numbering 20 people, is about 720 man-hours;
  • reliable communication with all staff;
  • gathering and analysis of operational information about all the production processes of the field;
  • operational efficiency increased.

Plans for the development of the project

Similar solutions can be successfully applied at other enterprises in the mining sector.



Comments from the market participants


24 November 2016 the Internet Initiatives Development Fund (IIDF) held a forum on advanced technologies "How the Internet of things and Big data create new markets". Here are some views of its members:


I would like to draw our attention to such a thing as the industrial Internet. Industrial Internet of things in particular will be a massive thing and it will be able to create quite a large new market. If we look at the microelectronics industry in its global scale, we will see that the analysts say that the next revenue growth of all microelectronic companies in the world will be based on developments associated with the Internet of things and it will be more than $ 100 billion in the next five-year forecast. If to compare it with the previous two revolutions: the advent of mobile phones and later smartphones and tablets, you can see that this growth correlates with the same values of the previous two eras.


In the Internet of things there is no projects purely in microelectronics, projects in this field also include big data analytics, communication infrastructure, integration with enterprise systems, ERP, etc. That is we talk about more complicated solutions. So we need to find a way to sell vertical solutions and close the entire project at once. We will not realize the IoT project, as it is only one element of the ecosystem. The complexity of Internet of things market is that a large number of various participants need to combine efforts to sell the same end product.



The Internet of things is not about connected devices, and it's not about meters, not about sensors, it's not about operator networks, types of communication or communication technologies. In fact, the Internet of things is about information and analysis. Whether it is in the cloud or not, in local or public storage, it is important to understand what business problem we want to solve.


For example, the problem of the Amsterdam city is that we need fewer garbage trucks to collect a greater amount of trash and make sure that it is not very noticeable to residents, we don’t want to make any traffic jams. This requires information about the current status of all the trash cans, and, based on these requirements, the technical director of Amsterdam is looking for the best meters, sensors, communication technologies, information analysis system – that is, choosing the technical solution and partner that will provide the city with all required information and analysis. This information is sent to the companies which are engaged in garbage collection – thus Amsterdam optimizes its costs as the city to take trash out of town.


In this context, there is a certain understanding of the business ecosystem: device manufacturers, network companies (including "MegaFon"), data analysis, vertical solutions. The key competence of the operator is to be the integrator of communication networks and the company that creates the necessary infrastructure. It is unlikely that we will be an Internet developer or will compete with companies that focus on specific vertical business problems. We look at several horizontal layers of the IoT:

  1. Communication technologies. We are competent in understanding the fundamental differences between the LPWAN networks, satellite networks, GSM networks and the rest. We know how to build them most effectively, how to choose the most appropriate set for every specific use-case. In some cases it should be satellite communications (for container transportation, for example) LoRa can be better for some other.
  2. Management of SIM cards, connected devices and so on. Together with "Peter-Service" MegaFon has been developing an M2M platform for several years, now it is being transitioned to a new level.
  3. Analytics. Any operator has a large amount of information. Not everyone is able to work with it, and the operator’s competence is to perform the information from the meters and sensors and provide the clients with all the necessary analysis.


Partner ecosystem center. The role of partners can be played by both equipment manufacturers and IoT companies (such as Siemens, for example). In particular, in 2016 "MegaFon" has accelerated the billing integration of its partners from several months to several days.



Some major companies have been already using the Internet of things for a while. It started 5-7 years ago, when the suppliers of technological equipment already built sensors that collected information. Now it is all combined into a single network. Though the technological revolution is not happening now, in my opinion. I think it will happen in three years, when we have serious analytical solutions and all this information is transformed into a finished product. To achieve this, we are now creating within the Bank a kind of concept of the platforms we will have to build by this moment, so that we will be able to use these systems and maybe even become leaders in this area.


Sometimes there is some misunderstanding, there are different languages: technical and economic. As a banker, I used to always proceed from the demand, needs, problems, from what can help you earn in the end. And when I communicate with people from technical spheres, they look at this in terms of technology: here we have a wonderful technology, then they very long and extensively explain me all the details using very complex terms. But my question is - where is the money? And here is the gap in the pattern: people don't know how much they can earn with this technology, what the market is like, who the competitors are and how the technology could be upgraded to earn more. Therefore, if these two worlds (economic and technical) will now begin to interact more systematically, we will move to a qualitatively new level of business and business models that will let us take a completely different look at the models that are available in the economy.


There is a thesis by German Gref that the oil of the future is information. We now understand it very well, and once we learn how to work with information, the revenues we have now, will be many times multiplied. Now the world’s largest banks are working on it. And the one who first will solve this problem at a new level, will be the leader of the process. In short, the bank of the future is a digital bank.



You can find all full length comments of these and other forum participants on the website JSON.TV:


Gulnara Hakimova, JSC "Mikron"



Alexander Bashmakov, OJSC "MegaFon"



Sergei Polikanov, Sberbank CIB




Detailed results of the research presented in the full version of the report:

«Global experience of implementing projects in the field of the Industrial Internet of Things (IIoT). Examples of the implementation cases»


The report volume is not less than 120 pages, including ~90 examples.




1. Mining industry

1.1. Goldcorp, Eleonore mine, Quebec, Canada

Mine production of gold concentrate.

1.2. Dundee precious metals, Chelopech, Bulgaria

Mine production of gold, copper and silver concentrate.

1.3. Sierra gorda, Chile

Mine production of copper and molybdenum ores.

1.4. The Anglo Platinum Group, South Africa

Plant for the production of precious metals.

1.5. Potash Corporation, Aurora, North Carolina; White Springs, FL.

1.6. Boliden, Garpenberg, Sweden.

Lead, silver and zinc mine.

1.7. Akara Resources, Chatri, Thailand.

Mine production of gold concentrates.

1.8. CMDIC, Collahuasi, Chile.

Mine production of copper ore.

1.9. Iron mine

1.10. Joy Global


2. Oil and gas industry

2.1. British Petroleum, UK.

Global oil and gas company.

2.2. Ergon Refining, Vicksburg, USA.

2.3. RasGas, RAS Laffan, Qatar.

Enterprise for the production of liquefied natural gas (LNG).


3. Metallurgy

3.1. Karl Casper, Germany.

Metallurgical plant.

3.2. Bharat Forge Ltd, Pune, India.

Metallurgical plant for the production of forgings.


4. Chemical industry

4.1. BASF, Ludwigshafen, Germany

Enterprise for the production of polymers

4.2. Akzo Nobel

Enterprises for the production of chemical products in different countries around the world.

4.3. Pirelli, Breuberg, Odenwald, Germany.

Enterprise for the production of tires.

4.4. Blaser Swisslube, Emmental, Switzerland

Enterprise for the production of cutting fluids


5. Mechanical engineering

5.1. General Electric, Atlanta, USA.

Center for remote monitoring and data analysis of the GE company.

5.2. SKF, Schweinfurt, Germany.

Enterprise for the production of bearings.

5.3. Bosch (Case 1), Homburg, Germany.

Enterprise for the production of throttles.

5.4. Bosch (Case 2), Suzhou, China.

Enterprise for the production of car electronics.

5.5. Konecranes, Finland.

Enterprise for the production of lifting equipment.

5.6. Lordan, Israel.

Enterprise for the production of heating and refrigerating equipment.

5.7. Servomax, Hyderabad, India.

Enterprise for the production of electrical equipment.

5.8. Pumping equipment manufacturer

Multinational pump manufacturer

5.9. ThyssenKrupp Elevator

Manufacturer of ThyssenKrupp elevators

5.10. FESTO (prototype)

Automated assembly production created on the concept of "industry 4.0".

5.11. Rolls-Royce

Reducing the number of missed flights


6. Motor industry

6.1. Honda, Tokyo, Yorii, Japan.

New еnterprise for the production of cars.

6.2. Daimler (Case 1), Rastatt, Germany.

Enterprise for production of Mercedes-Benz cars.

6.3. Daimler (Case 2), Kassel, Germany.

Enterprise for the production of axles for commercial Mercedes-Benz vehicles.

6.4. SEAT (Case 1), Martorell, Spain.

Enterprise for the production of passenger cars, SEAT and Audi.

6.5. SEAT (Case 2), Martorell, Spain.

Enterprise for the production of passenger cars, SEAT and Audi.

6.6. Kuka Systems, Ohio, USA.


Enterprise for the production of automotive components.

6.7. Harley Davidson

Implementation of the model of individualized mass production.

6.8. Manufacturer of automotive components


7. Food industry

7.1. Coca-Cola

70 enterprises producing soft drinks around the world.

7.2. Nestle, businesses in South Africa.

Food industry.

7.3. Hobsons Brewery, UK.

Micro-brewery producing craft beer

7.4. Danish Crown, Denmark.

Enterprise for slaughtering pigs.

7.5. King's Hawaiian, USA.

Bakery enterprise.

7.6. Premier Foods, UK.

Enterprise for the production of food.

7.7. Hillshire Brands, USA.

Enterprise for the production of sausages.


8. Pharmaceutical industry

8.1. Chengdu Rongsheng Pharmaceuticals, Chengdu, China.

Enterprise for the production of blood plasma.


9. Microelectronics

9.1. Intel (Case 1), Penang, Malaysia.

Enterprise for the production of microchips.

9.2. Intel (Case 2)

Enterprise for the production of semiconductor products.

9.3. Siemens, Amberg, Germany.

Enterprise for the production of microelectronic devices.

9.4. Osram, Germany.

Manufacture of lighting equipment and LEDs.

9.5. Amara Raja Batteries Ltd, Chittur, India.

Enterprises for the production of batteries.


10. Construction materials industry

10.1. Lehigh Cement Company, Maryland, USA.

Enterprise for the production of cement.

10.2. Spenner Zement, Germany.

Enterprise for the production of cement


11. Package production

11.1. Polibol, Spain.

Enterprise for the production of flexible packaging.


12. Pulp and paper industry

12.1. SCA, Ostrand, Sweden.

Enterprise for the production of bleached pulp.


13. Furniture industry

13.1. Steelcase, USA.

Plant for the production of furniture.

13.2. Lido Stone Works

Manufacturer of stone products on request


14. Utilities and security

14.1. Sogedo: control of resources for water utilities

14.2. City administration of San Diego: street lighting

14.3. City administration of San Jose: street lighting

14.4. City administration of Oslo: smart lighting

14.5. City administration of Rotterdam: smart lighting

14.6. Companies involved in recycling (many customers): logistics

14.7. The city of Seoul (South Korea): optimizing garbage collection

14.8. A big supermarket chain (UK): security

14.9. City administration of Buenos Aires

Reduction of the cost of city street lighting.

14.10. ComEd

Reduction of the cost of city street lighting.

14.11. The ADT Corporation

Retention of the customer base against growing competition from the new market players


15. Transport and logistics

15.1. Hitachi Rail in Great Britain

15.2. Royal Caribbean: passenger service

15.3. The municipal transport Association of San Francisco (USA): city parking lots

15.4. The municipality of Nice (France): urban parking and other services

15.5. Smoove: city bike rental in Moscow and other cities

15.6. Tesla: connected cars, OTA update

15.7. Boyaca: Newspapers and magazines

15.8. Kia: connected cars

15.9. Trenitalia: connected trains

15.10. The Port Of Hamburg

15.11. ARI (Automotive Resources International), a global company providing services of freight transport by road

Reduction of operating costs of vehicles, reducing the cost of the interaction with customers and partners and simultaneously improving the quality of the provided services.


16. Trade and finance

16.1. Diebold: ATM service

16.2. SG URALSIB: auto insurance

16.3. Unicum: connected vending machines

16.4. Whole Foods/Giant Eagle, retail network

Reducing lost profits from the lack of required purchaser of the goods to the zero level


17. Agriculture

17.1. OOO "APK-Chernozemye": monitoring the operation of agricultural machinery

17.2. Livestock farms in South Korea (many customers)

17.3. The US government: connected weather stations

17.4. Holding company "AK Bars": "electronic herd"

17.5. The collective farm "Precepts of Ilyich": pedometers

17.6. Winery/Many customers: collecting data on climatic conditions

17.7. The government of Peru: tracking climate changes

17.8. Agroholding "Kuban"

17.9. Farm Fresno County (California, USA)




This information note is prepared by J’son & Partners Consulting. We strive to provide factual and prognostic data that fully reflect the situation and are available to us before issuing the material.



The media may use any graphics, data or forecasts contained in this market review only with reference to the source of information - J'son & Partners Consulting. ™ J'son & Partners [registered trademark]  



In the present study J'son & Partners Consulting analyze and systematize examples of the implementation of the Industrial Internet of Things by the world’s largest industrial companies in various sectors of the economy.