[Editor's Note] Park Han-goo, Honorary Chairman of the Korea Industry 4.0 Association, presents a method for 'a great transformation to a digital economy centered on small and medium-sized enterprises over the next 50 years.' Small and medium-sized enterprises should practice digital transformation by collecting and storing data in a data format based on international standards and creating value through interconnection between companies and countries based on this. We shared a plan to establish a utilization system that stores data generated by companies and enables data communication and sales between companies.


Park Han-goo, Honorary Chairman of the Korea Industry 4.0 Association, argues that a standardized data model for each device is needed to create value based on stored data.


In order to achieve net zero in the future, the global economy is moving towards a trend where digital product passports must be issued in a certain data format when exporting and importing between countries, thereby providing connections and information between national systems.

■ Why Europe Issued a Digital Product Passport (DPP)

Each country cannot ignore the environmental issues linked to the socio-economic issues. Massive investments are being made to reduce greenhouse gas emissions and prevent global warming.

While there are many countries that follow the policy well, there are also many countries that export products that are made by emitting a large amount of greenhouse gases at low production prices. In countries that are practicing greenhouse gas emission reduction, products made in compliance with domestic laws are at a disadvantage in sales due to high manufacturing costs, being pushed out by imported products.

For example, if producing a product in Korea produces 100 tons of carbon emissions, the carbon tax would be 1,600,000 won, as the carbon emission trading price per ton is currently around 16,000 won. However, if the same product is produced in Europe, the carbon tax would be 12,400,000 won, or 84 euros (124,000 won) per ton. In this reality, factories in Europe will try to relocate to countries with lower carbon emissions prices to remain competitive, ultimately making it difficult to achieve carbon neutrality.

Accordingly, the European Union created the Carbon Board Adjustment Mechanism (CBAM) to impose a carbon tax equivalent to the difference in carbon emission prices when importing products between countries.

Furthermore, even if the companies that produce the finished product pay carbon taxes equivalent to the amount of carbon emissions per product, global warming cannot be prevented if the companies that mine, transport, refine, and process raw materials do not pay the carbon taxes they generate.
In an effort to prevent this, the European Union has established a system to calculate the total carbon emissions of a product by linking all the companies in the value chain from the mining of raw materials to the production of the finished product. This information is contained in the ‘Digital Product Passport’ (DPP).

DPP requires the provision of total carbon emissions, traceability of origin, decomposition methods for reuse and recycling, and resource recycling information. There is also the 'Eco design for Sustainable Products Regulation (ESPR)' that aims to increase recycling rates. Companies must design products that are efficient for consumers with recycling in mind.

Even our export-oriented country cannot avoid it. Korean manufacturing companies that import raw materials and materials and export intermediate goods and finished products will also have to pay carbon taxes in the above manner to be able to import. Carbon emissions generated by each component processing company and transportation company at stages 1 to N of the value chain must be additionally calculated, and digital information must be provided to companies exporting products.

A digital transformation of import and export trade is expected, with information stored in digital product passports and data provided to computer systems across countries.

■ How to calculate and measure carbon emissions and create DDP

The Greenhouse Gas Regulation (GHG Protocol) guides companies to calculate carbon emissions by classifying them into Scope 1, 2, and 3. △Scope 1 refers to the total amount of carbon directly emitted when producing products within a company. △Scope 2 refers to the total amount of carbon indirectly emitted when using electricity, gas, etc. within a company. △Scope 3 refers to the amount of carbon emitted during the production and transportation process from suppliers and transportation companies when a company receives raw materials and materials to produce a product. This information is received by linking computer systems into a digital product passport.

Although many regulatory measures will be introduced by national certification agencies in the future, companies should manage carbon emissions accurately by calculating or measuring them according to regulations. There are also predictions that there will be an advantage in terms of facility efficiency, as many facilities in our country are less than 50 years old.

IoT technology of the 4th industrial revolution can track and manage all statuses throughout the product life cycle. Digital twin technology makes it possible to create, exchange, and utilize data by making all things virtual assets.

The German Federal Ministry for Economic Affairs, Climate and Energy, which is leading Industry 4.0, created a three-dimensional Industry 4.0 Reference Architecture Model (RAMI 4.0) and mapped all international standards established to date. As a result, it was discovered that there was no international standard for expressing physical objects as digital twin objects with identical physicochemical properties in a virtual computer space, so it created the Asset Administration Shell (AAS) and applied for IEC international standardization in 2019. It is currently being established as IEC CD 63278 and is scheduled to be completed this year.

The European Union has created the Gaia-X organization to create and publish the DATASPACE rules so that companies and countries using different global cloud service providers can perform interconnection and operation economically and operate with data sovereignty. The Eclipse DATASPACE Connector (EDC) is provided as an open program as a data exchange and interoperability rule.

The Global Battery Alliance (GBA), a subsidiary of the World Economic Forum (WEF), has completed a pilot test to create a battery passport using the AAS data model to create, exchange, and utilize data between companies and countries, and is providing specific guidance to companies on how to do so. Since 2020, Korea's Smart Manufacturing Innovation Promotion Team has been verifying a system for collecting and storing manufacturing raw data in real time by modeling equipment based on AAS in cooperation with the German platform Industry 4.0 (PI4.0), and has been providing related software as an open source program and supplying it free of charge to domestic SI companies.

The AAS data model is a language of communication that is mutually understood and utilized by data sellers and buyers to achieve mutual benefits through true data transactions. The AAS data model is in the form of four areas. △Area for defining data ID names △Operation Technology (OT) area for entering operation data △Engineering Technology (ET) area for entering when designing and manufacturing equipment △Document area required for operating, manufacturing, using, servicing, and disposing of equipment.

■ AAS data model as a national standard
Data should be collected and stored in the cloud using AAS-based data model standards by industry, business, and equipment, making it easy to create and exchange data between different facilities, systems, companies, and countries, and to economically exchange and utilize data between data sellers and buyers. National standards should be established and companies should be encouraged to comply with the standards.

If AAS is made mandatory, SI solution providers are expected to face opposition as they will have to invest manpower in redeveloping solutions. Many equipment manufacturers reverse engineer overseas equipment to make copies, and in order to be price competitive, they often install only the essential sensors and supply them domestically. However, the global association related to equipment manufacturing, or the OPC Foundation, provides information model standards. If the equipment importing company knows that the number of sensors for the equipment must be 100, it can raise the issue of why only 50 sensors are supplied at the time of purchase. Ultimately, if all 100 are supplied, there may be concerns that the price will increase and competitiveness compared to foreign equipment will decrease.

Manufacturing companies have difficulty analyzing and utilizing data due to the small number of sensors attached to their equipment, so SI companies are solving the problem of reduced data analysis accuracy by adding sensors and collecting them. If manufacturing companies demand that the equipment they need be supplied according to the data reference model when purchasing equipment, the price will increase, and in this case, they can purchase high-quality overseas products. In addition, there is an advantage of being able to create economic value by selling high-quality data that has been systematically collected and stored directly to data buyers.

Data buyers who want to purchase data to develop solutions or AI algorithms, etc., can exchange data themselves without paying money to the SI supplier that built the DB, so they have the advantage of using it economically and quickly. Domestic global companies such as Hyundai Motor Company, Samsung Semiconductor, and Shipbuilding tend to pursue their own standard Defacto standard in order to dominate the global market. They can create a data model and request it from the supplier. In this case, small and medium-sized companies may face the uneconomical problem of providing data according to the standards of various large companies. Startups that provide AI and Big Data solutions can quickly develop and launch solutions through machine learning by preprocessing data collected and stored using a standard data model without relying on SI companies for data analysis and utilization.

In conclusion, the government needs to jointly recognize the need for data standardization, select internationally accepted standards, and develop a national strategy to lead the future era of data capitalism by accumulating data that companies and countries can communicate and trust in one direction.

※ author

Park Han-gu, Honorary Chairman of the Korea Industry 4.0 Association, Former Head of the Smart Manufacturing Innovation Promotion Team