## 1 Introduction
### Theoretical Background  
#### 1.1.1 Digital Twins and Their Industrial Applications  
Since the article mainly considers virtual laboratories, it is essential to produce some brief insights into digital twins because direct correlation can be established between the concept of a visual laboratory and the concept of a digital twin [1]. A digital twin is a virtual equivalent (prototype) of a real-world object, set of objects or processes; it is a computer model that duplicates the key characteristics of a physical object and that is capable of replicating its states under different conditions. It is a complex software product developed on the basis of various data. Its functions are not limited to collecting data at the stages of developing and making a product; it also collects and analyses data during the product lifecycle, sometimes using numerous Internet of things (IoT)-sensors. Digital twins emulate the operation of real-world devices. They involve developing virtual environments that allow testing different scenarios and getting the same results, which is faster, cheaper, and, to some extent, more reliable. Basically, it is a number of mathematical formulae that describe the object itself as well as the processes running in it. The digital twin is based on developing and applying a number of complex multidisciplinary mathematical models described by 3D non-stationary nonlinear differential equations in partial derivatives. Such a twin can be developed even earlier than the physical object it is supposed to duplicate: a virtual model can be developed while the object (a building, an automobile, a device) is being designed. The technology allows simulating various situations that can arise in the workplace. Thus, the digital twin makes it possible to choose the best possible scenarios of technological processes so that failures and emergencies can be avoided. This research introduces the theoretical framework of the digital twin-driven assembly-commissioning method for high precision products with multidisciplinary coupling. A case study product was used to verify the effectiveness and feasibility of the proposed method. In our research, a digital twin is regarded as a component in a complex system that represents the whole complex of many parts or even numerous systems and which can be presented as a range of digital technologies. These technologies apply approaches based on statistical analysis, machine learning, physics, control theory, reliability engineering, the theory of waiting lines, and numerical simulation of physical processes in the materials of an object. The latter allows simulating the behavior of complex systems by dividing them into numerous components, which are small enough for their properties to be considered as homogeneous ones. It is widely used for solving problems in such areas as deformable solid mechanics, thermal exchange, hydrodynamics, electrodynamics as well as streamlining the work. Besides, CAD-models (computer-aided design/drafting and computer design aids) are widely used. They carry the information about the appearance and structure of objects, as well as the information about materials, processes, dimensions, and other parameters. FMEA (failure mode and effects analysis) models based on the analysis of system reliability are also applied. They are capable of incorporating mathematical failure modes with the statistical database of failure modes. In fact, this methodology is used for performing analysis and determining the most critical phases of manufacturing processes. Some experts divide digital twins into three types. The first one is referred to as the DTP (digital twin prototype), which is a virtual replica of a physical object available in the real world. The object contains the data required for the comprehensive description of the model, including the information about the way it was designed in real-world conditions.