Let us consider the main four stages in which the concept of DO evolved. For some time, the digital object was used independently of the physical object, rather, as a model necessary to develop and create the physical object. As quality and accuracy of the models grew, it turned out that studying and testing digital objects was considerably cheaper and faster (as examples of the automotive industry replacing full-scale tests with virtual ones indicate). This way, the DO began to complement and enrich the physical object. An example is the development of heavy-duty turbines by Siemens. Furthermore, digital technologies made it possible to find critical points in the object; the so-called smart digital twins that can be constantly trained appeared(Bolshakov, Badenko, Volkova, et al. 2020). This made it possible to model not only the object and its operating modes but also its entire lifecycle with a trainable smart DO constantly accompanying it. Thus, a new virtual object containing data on the physical object appeared. The DO is inextricably linked with the PO; using DO allows significantly (in some cases by an order of magnitude) shorten the time for decision-making, and greatly reduce the risks, both technical and financial.
It can be argued that the digital object adds value to the physical object throughout the entire life cycle of a process, system, or organization. DOs (DTs) start creating value at the stage of design. The relationship between capital expenditures and the phases of operating expenditures allows to assess this value created.
A digital object can be considered from the point of view of economic theory, structuring three layers of the product:
-
product by design, the main benefit; augmented product - after-sales service;
-
ready physical product:
-
and the product marketing shell.
3.1. Properties of digital object as a commodity:
According to Lionel Robbins, economics is defined as "the science which studies human behavior as a relationship between ends and scarce means which have alternative uses"(Robbins 1934).Robbins' rationale for focusing on the isolated individual could be treated as the starting point for economics (Oliveira and Suprinyak 2018). The three basic postulates of the Robbins’ Essay − 1) that individuals can order their preferences, 2) that there exists more than one factor of production, and 3) that there is uncertainty about future scarcities – only needed “to be stated to be recognized as obvious”, and there was no need for controlled experiments to validate them. These basic postulates were not, however, self-contained principles, and subsidiary postulates were required to apply them. Since these subsidiary postulates were not known a priori, Robbins wrote, “before we apply our general theory to the interpretation of the particular situation we must be sure of the facts”.In view of this, economics can be regarded as the science of rational choice made by calculating maximized results provided with minimal funds. At the same time, economic science is dedicated to the issue of consumption, i.e., how people allocate their funds between different types of goods and services, how they make a choice between competing goods and services, how manufacturers inform/manipulate consumers to sell their goods. Thus, the concept of a product is the first of the economic categories to be considered. Economics usually considers three layers of a product. Figure 2 shows a schematic representation for the layers of a product.
Let us consider the DO in terms of a product category. Let us suggest a classical categorization of the concept of the product into three layers: the main benefit; the ready product; augmented product (Fig. 2).
Figure 2. Product levels (layers) from the standpoint of economic theory.
The following categories can be proposed to describe the DO:
Layer 1 of the digital object of the product is the main benefit.
Properties of a digital object forming a product designed, aimed at satisfying a need (Guttenbrunner and Rauber 2012; Park, Yang, and Noh 2020; Fuller et al. 2020; Minerva, Lee, and Crespi 2020):
-
information about all characteristics and parameters of the physical object: information completeness;
-
ability to simulate the behavior of an object, its nodes and elements in various conditions, predict changes in the parameters of the processes and characteristics of the physical object: predictability;
-
ability to contain all nodes and elements of the object together, considering all hierarchical layers up to each individual element: hierarchical integrity;
-
digital object represents the physical object with a high degree of accuracy;
-
ability to train, integrating all the data obtained during the operation of the object;
-
ability to be easily integrated into higher-level objects.
Layer 2 of the digital twin of the product is the real physical product.
A digital object has consumer properties; as the components of the digital object, they can also be represented as the information disseminated for advertising purposes (Damjanovic-Behrendt and Behrendt 2019; McKenzie 2020):
-
DO can form the augmented reality (AR) and the virtual reality (VR) environments for visualizing the physical object for the purposes of object management, marketing, personnel training, etc.;
-
DO allows to predict with high accuracy the costs of maintaining/operating an object throughout the entire lifecycle;
-
DO allows to simulate maintenance and repairs of the physical object throughout the entire lifecycle;
-
DO allows to simulate the process of object management (decision-making) in normal and emergency situations, ensuring safety including in case of emergencies;
-
DO allows to create a range of solutions to quickly change the style, design and some consumer characteristics of the object.
Layer 3 of the digital twin of the product: augmented product.
The following characteristics of a digital object are related to post-sales services, for example, adding information.
Virtualization has the ability to: make heterogeneous objects interoperable through the use of semantic descriptions; enable them to acquire, analyze and interpret information about their context in order to take relevant decision and act upon the virtual objects. Moreover, it enhances the existing functions offered by the IoT, supporting the discovery and mash up of services, promoting the creation of new addressing schemes, improving the objects mobility management efficiency, as well as addressing accounting and authentication issues (Nitti et al. 2016; Björkdahl 2020; Immonen et al. 2016):
-
automated object management based on elements of the Internet of Things (IoT), distributed and remote control of the object;
-
solutions can be scaled quickly;
-
financial and technical transparency of operation process (lending/insurance).
Thus, we can conclude that the DO can be regarded as a product, since it carries a clear economic benefit. In this case, the DO forms a number of new qualities that were not previously available for most physical objects. This can be compared to the transition to another dimension, from linear to planar and, further, to volumetric. The combination of physical and digital assets produces new qualitative characteristics that change the concept of the product as a merely physical object.
It can be concluded that the divisibility of the DO is manifested in cooperation, in the ability of different economic agents to unite in order to achieve joint benefits. At the same time, the benefit of each participant and the multiplicative benefit are not commensurable. Integrity allows to satisfy all consumer needs at once. This raises the question of the contribution of each participant to the creation of the product. An obvious conclusion is that it is not the investor/customer who becomes the key figure but the integrator of the process who decomposes the consumer qualities of the product into technical requirements, down to the level of subsystems and elements. There is an analogy with the physical product, as the integrator obtains the maximum profit due to satisfying the customer's needs.
While the integrator previously assumed all the risks of integrating a system element into an object during the production of goods, a new entity has now evolved for this function: a digital platform for creating a new product. The main goal of the digital platform is to generate conditions for the most effective integration of individual elements into a single whole.
A system integration method has been developed in industrial production, which in economic language can be called cooperation. This method offers a different outlook on the basic principle of competition. The requirement of cooperation brings to the fore the principle of integral benefit, when a product (or its element) is compared not by its actual properties but by an integral characteristic that ensures the satisfaction of the consumer's needs.
MBSE (Model Based System Engineering) is one of the most common methodologies used in modern systems engineering(Borchani et al. 2019; Oztemel and Gursev 2020b). As a concept, MBSE has been discussed since the late 1990s, and since 2006 as an initiative of INCOSE40; its modern interpretation was forged at the international conference on MBSE which took place in 2010.
3.2. Changing the division of labor
Manufacturing is the backbone of almost any economic activity. Manufacturing changes are the most powerful sources of social transformation. Industrial revolutions serve as an example of this. The modern world is created as a result of changes in technology and work organization systems. Digital technologies have a significant impact on the systems of division of labor. It is evident that new factors of production other than land, labor and capital are evolving.
In traditional manufacturing, the design phase makes up about 10–20% of the total cost of creating a product. The main costs, up to 80–90%, are spent on manufacturing, testing and fine-tuning the prototype. This proportion is changed with the DT technology, drastically reducing the product launch times. For example, the launch times of new products in the automotive industry are only 3–4 months, since the DTs of products and processes are already created(Weyer et al. 2016). Conceptually, this is explained by the fact that knowledge always appears with experience, which is born from experiments. Experience in human history has always taken long to accumulate and/or has been expensive to gain. The DO allows to transform experimentation as a necessary function for creating the product from long and expensive to cheap and fast. This is thanks to computing speed, and the software product embodying the knowledge that took millions of person-years to obtain. Apparently, the DT technology allows to gain new knowledge quickly and cheaply, thanks to the ultra-low transaction costs for product development.
All of this points to a change in the distribution of labor in the digital economy. The center of gravity in creating goods, products and services is transferred to the stage of design/creation. The production process becomes purely technological. All requirements for it and all operations are already established at the design stage. This suggests that the stage of production becomes subordinate to the stage of design. The stage of using a product/service is also modeled at the stage of design. Even though there is potential for creativity in client relations, all possible scenarios for product consumption are worked out at the design stage. This makes a significant contribution to reversing the roles of participants in the labor distribution system. The manufacturer of the goods/products is increasingly shifting towards providing services using the product replacing the traditional system of selling goods to the market. An example of this is General Electric's concept of transition to the power generation market, with gradual withdrawal from the power equipment supply market. A similar approach is demonstrated by car manufacturers entering into alliances with car-sharing companies (Volkswagen-Audi and Uber). Thus, it can be argued that digital technologies significantly affect the division of labor, replacing the competition of goods with the competition of services and transforming the competition of solutions into cooperation of solutions, generating a new factor of cooperation, and, in fact, industrial production that is the digital platform.
Consider the basic provisions of economics proposed by Adam Smith, monopoly and oligopoly. Today, the unique offer that the company offers is a benefit rather than a problem for a huge number of people in the world. Companies such as Amazon, Walmart, Google, Microsoft, Tesla, and others sometimes determine what will be produced and where, what people will buy, and who will profit from it, often in which amount.
3.3. Digital platforms
Since the development of a new product based on digital technologies is now becoming central to the division of labor, the task at hand are the measures that need to be taken to ensure this. Given the multidisciplinary nature of the product, it becomes unprofitable for one company to keep an entire staff of specialists from different fields. An additional question concerns the accumulation and preservation of the manufacturer's knowledge base about the product. As a consequence, digital platforms based on the MBSE system appeared on the market. MBSE is one of the most common methodologies used in modern systems engineering. The new business model for creating the product is cooperation/association of knowledge-bearing groups. This association exists only during the time required to create a product or a part of a product. This is a new matrix structure.
In the most general terms, MBSE is engineering based on a single consistent model of the system to be designed, combining all the data and properties about this system. This is a concept for applying formalized modeling to generate the requirements for support, design, analysis, verification and validation of the system at all phases of its lifecycle.
Analysis of systemic disasters revealed a number of problems related to designing complex multi-component objects, including insufficient communication (especially during transitions between different models), outdated specifications or incomplete product requirements, weak control over the configuration, insufficient quality of testing for errors, and inability to ensure smooth degradation of the system in case of failure.
The MBSE concept is a response to these challenges and is intended for generalizing the knowledge models, improving communication provided by the models; generating a more accurate assessment of the models for their consistency, completeness and correctness; improving analysis of the consequences of changes in the system; improving methods for overcoming complexity and improving the quality of the system created; improving knowledge extraction and reuse (resulting in shorter cycle times and lower maintenance costs), and minimizing knowledge loss after team members leave(Peak et al. 2007).
Developing a product that is a DO based on the DT technology, developers go through several scenarios, often obtaining important secondary solutions. Thus, a large number of people/companies are involved in product development. However, the modern legal framework does not take into account the rights for DO. There is no such object in today's legal field, and there are no rights to it; the new division of labor needs a description of this object. This is especially important for describing the roles of the participants cooperating to create the DO. The key factor in creating the DO is the question of who accumulates the entire knowledge base of the product. Today, all leading companies use their digital platforms to both integrate solutions and build a knowledge base that is a repository of different local problem-solving scenarios. As the example of the automotive industry proves, the capacity for integration is key in creating a new product.
3.4. Consumer as participant in the process of creating the product
Complex technical objects are always created by those who accumulated experience in technology. This often happens in different climatic conditions, with slightly different raw materials, and significantly different production culture. Moreover, such products are often created by local companies, which have different production cultures. Therefore, the launching and fine-tuning processes take a lot of time and money. At the same time, providers of technology and solutions want to protect their know-how, enshrining it in different operating modes and restrictions. The DO technology allows to consider the entire lifecycle of the object with all the aspects characterizing its creation and operation. DT technologies are a basis for controlling the lifecycle of a product. Thus, the consumer becomes a contributor in creating an object. This approach has engendered a paradigm shift for product manufacturers. Understanding how their products works throughout the entire lifecycle of the DO, and understanding all the costs, the manufacturers of the products become service providers (e.g., General Electric with electric energy, Audi/Volkswagen with car sharing). All of this changes the requirements for the product and its manufacturing, for example, management of the resources of the elements and the whole product. The DO becomes the pivotal object. All parties want to gain access to it. What are the conditions? Who makes which contribution? Where are the limits of each participant's contributions? There is no product without cooperation, so the key to creating a product is the principle of cooperation/collaboration. How should it be implemented? If the consumer is involved in cooperation, where is the competition? It becomes a competition of consumer properties: the consumers decide what they need, creating the products for themselves.
A significant factor today is the customer's participation in creation of the product. While previously the role of the client consisted of forming the consumer qualities of the product, now the digital platform is a tool allowing to model/predict the entire lifecycle of the product, making decisions about the requirements for the product elements, based on the entire lifecycle. Before, the client ordering the product took all of these risks. Including the operating organization in developing the product along with the manufacturer allows to combine all types of knowledge about the product, which were previously dispersed in time and space. All this has a consequence that a new division of labor is emerging, transforming from a linear (sequential) system into a matrix one (where everyone interacts with everyone). This is possible only when the principle of trust is in effect, and this is what the DO provides.
To quote Cicero, cui bono? Who benefits from this? It turns out that the DO is becoming beneficial to almost all participants of the labor division system. The DO is based on the principle of transparency, allowing each participant to contribute to the maximum satisfaction of the needs of the buyer/consumer, especially since the latter takes an active part in creating a product/service.
3.5. Autonomous technologies
Mankind has always tried to facilitate labor-intensive operations, in particular calculations. This is how the abacus, arithmometer, and computer appeared. With the rise of digital technology, it has become possible not only to perform computations but also to choose from a set of possible scenarios. AI algorithms, or, more precisely, intelligent assistants have appeared that can quickly suggest possible options and calculate them. They greatly speed up experimentation. At times and orders of magnitude. However, the computer cannot think. Therefore, people should shift towards creativity, developing creative thinking and leaving abilities to experiment for the computers, which earlier only nature has been doing for years, millennia.
Given the opportunity to simulate the entire lifecycle of the product, it is possible to model the system for controlling the object/product. This is the path to autonomous technologies. The DO allows modeling/forecasting scenarios, which allows automating most of the decisions made by transferring the monitoring function to any location via the Internet of Things. This contributes greatly to developing concepts for factories of the future, when the production and logistics component is maximally technologized and automated, with transferring the main contribution to product development according to customer requirements and interaction with the consumers of the product/service in order to fully satisfy their needs and expectations.