A digital twin is a digital representation of real-world instruments, the main principle for all participating organizations during their life cycle is to create a digital twin, processes or even individuals also called a “digital shadow”. The digital twin gathers and connects all knowledge about the state and use of physical entities to knowledge about the status of their counterparts and provides an assistive response to changes, thus improving their use. The digital twin is an active simulation aimed at running a physical, economic, socio-technical, or business system “real” in parallel and interacting with them.

Digital Twin Development

One of the applications for technical advances used in the industry is the digital twin process. With the assistance of computer software, the digital twin can be defined as the development of physical asset reflection. With the simultaneous upload of financial and non-financial information about the organization and its owners, the profit from the audit will improve.

In 2001, the “digital twin” concept, one of the first to use “Michael Grieves” “Product Lifecycle Management” digital twin model as noted in the book are three main factors to speculate on a structure, the first digital media device to be formed in twin tools and equipment or factory. Secondly; to provide the digitized data must be obtained. The physical environment of some data to move to digital platforms should be poured on mathematics and must be translated into the 1’s and 0 digits in some computer coding language information.

It is possible that contact sensors. data from sensors, and integrated with corresponding systems previously generated and combined with data previously transferred to the digital medium is made ready digital modeling. The third and final stage; a mirror is formed in the digital environment. At this stage the simulation, the rise estimation algorithms and methods utilized in computer science such as artificial intelligence. Digital twins who are in constant communication with the physical, data removing process and results in different scenarios but also the physical environment of the future should there be any real data from real information from the kidnapping and basing updating.

Special digital models defined as digital twins offer advances in technology is one of the advantages. In the traditional process; identifying problems, increasing productivity studies, decision-making mechanisms, a real machine, tools and people in the physical environment based on data. While most businesses have limited access to detailed data on these issues, smart decision making to establish data-based methods and misconception it may decrease. For this reason, the system is prepared in a detailed, timely and tailored systematic. Need to be installed. Because unlike an analysis environment where the entire ecosystem can be seen studies are conducted on data focused on some points. Along with the digital twin, a specific it is possible to move the medium or machine (even the entire factory) to digital media. In the real world, the data generated (in the physical field) will also be reflected and generated on the digital platform, and this will be different. It will allow producing and working on scenarios.

The road map published in 2010 by the concept of digital twin NASA and was heard for the first time by the public. The digital twin is defined as dynamic software model of a physical object or a system. In other words, digital media is the twin of the real-life twins. Digital twin analyzes real-world conditions, simulating, respond to changes, be used to improve operations. Within a few years, billions of objects to be met with a digital twin, a physical object or system, will be represented by a dynamic software model. The digital twin of physical assets, people with a digital representation of the facilities and environment, between businesses and simulation processes, by creating a real-world analysis and control system will provide a more detailed way in the digital representation. Business, digital twin “discharging a live model, which is a consequence of business” as characterized. Do not use the digital twins and that it should be an economic rationale or justification for an optimization or cost reduction is a combination of these reasons. The turbine power plant in a digital twin corrected by forming irregularities detected by this digital turbine is provided and twelve million dollars in savings.

Billions of objects soon are expected to be represented by a digital twin. For example, the digital twin is monitored about 500 thousand in a general electric plant in turkey. In different environmental conditions of the object to determine how it reacts to how it works and the resulting reaction that occurs in the real world with physical data and comparisons can be detected using the sensor results. According to this comparison result; digital twin performing analysis and simulation of real-world conditions, create and respond to change operations can be used to make it better .

Factors, cities, countries have digital twins, as well as individuals, have digital twins, which will reduce the risk of illness. The use of smart machines and robotic surgery are preliminary studies of the digital twin application, which will be a breakthrough in the medical world. The Da Vinci robot, used today as a surgical robot in medicine, was drawn by Leonardo Da Vinci in 1492. With the drawing he named as Vitrivius Man, Da Vinci determined the ideal measurements of the human and tried to make the most accurate copy.

In the literature, Da Vinci’s self-driving car was named the first robotic vehicle and the robot knight was named the first humanoid robot. Using the anatomy, Da Vinci observed how muscle work gives strength to bones and designed a humanoid machine that can work on the same principles. Due to the inability to produce this invention, which is different from Da Vinci’s other discoveries, it remained a robotic knight for entertainment purposes. In 2002, robotic expert Mark Rosheim produced a simulation of this system that works with rollers and wheels. Later, Rosheim used some of these designs as NASA’s robots. In medicine, working with a cadaver to understand the human body can also be compared to an analog twin.

Advances in medicine are closely related to the digital world. The digital stethoscope, which is indispensable for doctors, has the feature of recording and storing heartbeat and breathing sounds. In the future, the stethoscope will collect large amounts of data that relate to diagnostic data and treatment information and will assist in diagnosing the doctor. Daily jobs such as learning machines, tools, speakers and hospital equipment, patient records, patient databases and preliminary examinations will be performed by smart machines in the digital environment thanks to artificial intelligence.

A digital twin is a computer program that uses real-world data to produce models that can simulate the operation of a product or process. IoT (Industry 4.0), intelligent systems, cloud services and software analysis can be integrated into these projects to increase performance. Creating this will make it possible to change patterns of strategic infrastructure, avoid the failure of costly physical things, advanced analysis, monitoring and forecasting capabilities, testing methods and resources to be used.

In the following Figure 1 appear all stages for digital twin development.

Digital twin development for a medical device such as mechanical ventilator

The digital twin can be defined as a data-rich record that lasts a lifetime of a person along with intelligent system-powered models that can “query” the data to answer clinical questions.

Healthcare system is beginning to take advantage of this strong new platform now, the first step analysis of the intelligent healthcare system creates a report using cloud-based for creating a digital twin application to get information on the cloud-based and change to digital twin model after creating system definition and simulation, the last step is testing application the using digital twin is developing intelligent healthcare system is has a lot of benefit for examples more efficient supply and delivery chains, Improved product quality, and enhanced insight into the performance of your products, in multiple real-time applications and environments, reduced risk in various areas including product availability, marketplace reputation and more, faster production times.

We are making a virtual copy of intelligent healthcare systems, e.g., mechanical ventilator, the mechanical ventilator receives real data’s, and use the real data’s for creating the digital copy, cloud system at the storage place where all data are collected, a cloud system is a storage place where all data can be accessed at any time or anywhere.

In the first stage, it is necessary to analyze in a very detailed way and understand all parameters related the mechanical ventilator, and as the second stage, the planning and design of the application were done in great detail. As the third stage, the intelligent healthcare system, namely the mechanical ventilator, makes modeling and simulation. In this stage, we can use the cloud system to use all the data from where it is collected, we use certain programs to make simulation at this stage the most popular programs. In this thesis, we use MATLAB to use this application is one of the most efficient and best programs to be very fast in MATLAB in the last stage, when there is an application in the combination of the intelligence healthcare system and cloud system used to make digital twins, this application is tested and checked if there is any problem or not.

Digital Twin Implementation Steps

The phases of the digital twin, to create a digital twin for the real object or any physical devices, it takes some stage. Figure 2 below describes the main stages of a digital twin.

The phases of digital twin

Create: The creating stage involves the adaptation of the physical process to countless sensors that quantify vital inputs from and around the physical process. Sensor measurements can be usually separated into two categories: (1) operating metrics relating to the productive asset’s physical efficiency parameters such as tensile power, shift, torque and color uniformity (including several works in progress), (2) environmental or external data, such as atmospheric temperature, barometric pressure and moisture levels, influencing the functions of the physical asset. Messages may be encoded utilizing encoders into protected digital messages and sent to the digital twin. Method related data from applications such as distribution systems, business resource planning, CAD models and supply chains systems will improve the sensor signals. The Sensors’ signals can be improved. The digital twin will then have a wide variety of data constantly modified to be used to evaluate it.

Communicate: This communication phase aims to merge the physical mechanism and the digital platform smoothly, in real-time and two-way. Radical improvements that have allowed the digital twin have been made to the network connectivity, and it has three key components: Communication interfaces, Edge processing, Edge security.

Aggregate: The aggregate stage will help data ingestion, processing and analysis into a data repository. The collection and retrieval of data may be performed on-premise or in the cloud. Over the past few years, the technical realms of power data aggregation and analysis have shifted enormously such that programmers can produce increasingly efficient and more cost-competitive, massively scalable architectures.

Analyze: Data is processed and viewed in the research process. To build iterative models that create observations and feedback and influencing decision-making, data scientists and analysts may use advanced analytics tools and technologies.

Insight: The insight into the process gives insight from analytics through the visualization panels, lights in acceptable differences in the output of the digital twin model in one or more dimensions, hence the physical world analog, that indicates areas that are undoubtedly needed to be examined and modified.

Act: The action phase is to provide the physical assets and digital process with actionable lessons from previous phases, to achieve the effect of the digital double. Insight is passed to decoders and is then conveyed to the actuators in the asset process which are responsible for movement or control mechanisms or are upgraded to backend structures that control supply chains and order actions, both subject to human intervention. The closed-loop relationship between the physical world and the digital twin is completed through this connection.