Digital Twin

Use Cases Digital Twin

	Digital Twin

Overview	The digital twin is a digital replica of a living or non-living physical entity. Digital twin refers to a digital replica of potential and actual physical assets (physical twin), processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an object operates throughout its lifecycle. Definitions of digital twin technology emphasize two important characteristics. Firstly, each definition emphasizes the connection between the physical model and the corresponding virtual model. Secondly, this connection is established by generating real-time data using sensors to provide an evolving perspective into the current status of the physical object. The concept of the digital twin can be compared to other concepts such as cross-reality environments or co-spaces and mirror models, which aim to, by and large, synchronise part of the physical world with its cyber representation. Read More
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Overview

The digital twin is a digital replica of a living or non-living physical entity. Digital twin refers to a digital replica of potential and actual physical assets (physical twin), processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an object operates throughout its lifecycle. Definitions of digital twin technology emphasize two important characteristics. Firstly, each definition emphasizes the connection between the physical model and the corresponding virtual model. Secondly, this connection is established by generating real-time data using sensors to provide an evolving perspective into the current status of the physical object. The concept of the digital twin can be compared to other concepts such as cross-reality environments or co-spaces and mirror models, which aim to, by and large, synchronise part of the physical world with its cyber representation.

	Battery manufacturer Industrial Digital Twin For optimum control of product quality, Banner relies on a high production depth. Its 560 production employees produce nearly all the components in¬-house that they need to make finished batteries on Banner’s six assembly lines. This includes the plastic parts for the battery cases as well as the paste-filled lead oxide grids. Their production involves two to five¬ days rest in maturing chambers to create optimum current absorption and storage capacity. Banner’s ongoing success was accompanied by a continuous, organic growth of the production facilities, adding or extending hall after hall until the complex filled the site that had seemed ever so spacious when the company moved here from a smaller place in 1959. These developments led to a heterogeneous production environment. “This confronts us with significant challenges, particularly concerning intra¬logistics issues, such as scheduling for the maturing chambers,” says Franz Dorninger, technical director at Banner. “We contemplated various ways to overcome this problem, including relocating to new premises.”
	ThyssenKrupp employs Visual Rules BRM ThyssenKrupp Steel Europe found itself in the position of needing to replace, step by step, the models it had programmed itself to manage the production of various grades of steel with a solution equipped to face the demands of the future. The solution had to be easy to integrate and designed to be rolled out step by step. ThyssenKrupp Steel Europe uses its automation systems to manage the whole production process at its company steel plants. This is done using clever algorithms that map the functional relationships across all stages of the steel production process. However, there are still a host of other changeable factors that influence the quality of the product obtained, and these also need to be factored in in the form of rules or formulae. What ThyssenKrupp Steel Europe was looking for was a suitable piece of software to fulfill this rule-based management function.
	K-Engine's On-site Design & Cost Estimation Benefits Using AR In the housing industry, around 60,000 small to midsize housing builders are creating images and calculating the estimated cost of each project based on the requirements of home owners. Due to the huge selection of products and options, it usually takes around one week and cost for users to create images using CAD tools in addition to picking out products from multiple vendor product catalogs.

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Overview

Digital Twin

Case Studies