Manufacturing of the Physical Product

The manufacture of the physical product can be planned based on the experiences and recommendations of the users of the virtual product. User experiences related to the dynamics of the simulation model are added by means of actuators, controls, and sensors. The physical model may contain hydraulics, electrics, pneumatic and mechanical actuators, and tires to execute requests made by users of the multibody model in the immersive environment. Sensors can collect physical product data and input it into the simulation model. This model can be used in the service stage of the forklift, as shown in Figure 12.1, where the virtual replica of a physical 3W, 2.0-ton, EVOLT 48 forklift in a VR environment is presented. User experiences in the physical version of the forklift can also be tracked in the reference link (EDiA, 2019).

Real-Time Communication Between the Physical and Virtual Spaces of the Digital Twin

Before the release of a new product that has been developed based on user experiences, the physical and virtual spaces need to be interconnected so that digital twin information can be used in different phases of the product lifecycle as needed by end users and customer. Network communication, cloud computing, and network security are the key enabling technologies for transmitting data back and forth between the physical and virtual twins. Physical product sensor data is stored in data cloud storage using network technologies such as quick response (QR) code, radio frequency identification (RFID), barcodes, wireless fidelity (Wi-Fi), Bluetooth, etc. The data can be accessed via the 4G network. The multibody model enables end users and customers to monitor, coordinate, and control the real world of the digital twin. This data communication must be secured for successful management of product lifecycle related services.

Product Life Management Data

The multibody-based digital twin generates big data during the service and end of life phases, and this data can spur development of new product-related services. The data can include product component data, product-environment interaction data, environment data, product user data, and control data. As mentioned earlier, the data can be used in the real-world counterpart with the aid of sensors and IoT services in real time. By using VR/AR immersive technologies, the multibody-based digital twin enables users to predict, optimize, simulate, and experience the states of the physical space with contact and collisions in the environment during the products life. For instance, product component data can notify stakeholders of the need to take actions related to predictive maintenance of the product. Similarly, using product state data, more precise decisions about the reuse or retiring of a product can be taken. Additionally, industry can utilize user experience history from the lifecycle of previous multibody-based digital twins in future products and other projects to gain competitive advantage.

Enhancement of Measured Data

Due to integration of the equations of motion with a state observer estimator, the multibody simulation can provide information about the internal states of the system based on a smaller amount of sensor data from the physical system (Sanjurjo, 2016). In this way, the multibody-based digital twin can provide detailed information about the state of the physical system, which in some cases can reduce sensor costs. The multibody-based digital twin can reduce the cost of management of many digital product processes compared to conventional digital twin technologies. For instance, it is possible to predict the wear and tear of tires from accurate information about vehicle tire friction.

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