The number of components that produce data and applications that consume it is steadily growing in the manufacturing environment. More and more frequently the stream of data does not stop at plant boundaries: IIoT software developers and machine manufacturers are just as interested in production data as machine operators on site. A common basis is essential in order to ease communication within this growing ecosystem of hardware, software and people.
The Digital Twin System addresses the needs of all those involved through comprehensive semantic data homogenization and by conveying manufacturing data along with contextual information. The principle behind the DigitalTwin System is to link raw data to context. A single digital twin is a digital replica of a physical asset, such as a machine. The Digital Twin System groups the data produced by this asset into generally comprehensible information based on aspects, i.e. information groups such as machine faults or condition data. Authorized users can easily find and use the underlying semantic models, the digital twins themselves or parts of them. This also allows external machine manufacturers or programmers to access the relevant production data. The Digital Twin System thus forms the basis for comprehensive digitization of production and logistics. This leads to new opportunities to increase efficiency in production: data can be compared and used by different systems, since the required context is always included; every recipient receives precisely the information he or she needs.
Once production is digitized using the Digital Twin System, it is possible to exchange contextualized information about the state of entire production lines. The external machine manufacturer or software developer can offer innovative services or develop new solutions without having to be on site. The Digital Twin System not only helps to optimize production processes, but also creates synergies across plant boundaries.
“The Digital Twin System enables the communication and semantic data exchange between all different stakeholders across the life cycle of a product” Ulrich Wolters, Head of Product Area Foundation, Bosch Connected Industry.
Data Homogenization With The Digital Twin System
To meet the requirements of all parties, we need as system that provides comprehensive semantic data homogenization, conveys contextual information and arranges data into specific categories, such as warning or status messages, while also providing full access control to each data package.
Bosch Connected Industry, the business unit established by Bosch for Industry 4.0, has developed Nexeed, a comprehensive portfolio of software solutions. As a leading user and provider of Industry 4.0 solutions, Bosch understands the individual challenges that developers, manufacturers and operators face with regard to data homogeneity.
Measures bundled under the Nexeed Open Integration project facilitate communication between people, software and machines. The Digital Twin System is currently being developed to remove ‘language barriers’ and to provide an easier way of finding and accessing data. This system ensures that the data of each physical object in production or logistics is presented in a way that can be understood by everyone and found quickly. Hence, it addresses the aforementioned needs of machine operators, machine manufacturers and IIoT developers.
The term “digital twin” is not precisely defined and is currently interpreted in different ways in industry. It is primarily used to describe the digital replica of an asset such as a tooling machine, with all the information relevant for a specific application, e.g. the simulation of exceptional loads or as a component in a digital plant design. The Bosch approach goes much further: the Digital Twin System from Bosch Connected Industry forms the basis for comprehensive digitization of production and logistics by gradually creating consistent data homogeneity and interoperability. Each asset has a digital representation with consistent semantics and contextual information: the underlying semantic models (aspect models), the digital twins themselves, as well as parts of them (aspects, information packages clustered by category) are independent of each other and can be used and found by the specific user.
The Industrial Ecosystem and Data Requirements
The idea of comprehensive connectivity is not new. As early as the beginning of the 1990s, the Purdue model1 developed by Theodore J. Williams led to different levels of industrial connectivity; from individual components to business operations. Communication and the exchange of data between different parties and levels was already a huge issue. Almost 30 years later, the complexity and ‘scope’ of this network, as well as the speed at which physical assets and software have to be implemented and new ideas have to be put into practice, have increased massively.
Today, more than just a few applications and people in the immediate operating environment must be able to understand and interpret data. Industry 4.0 transforms data into a valuable asset or currency, that can be easily exchanged between the stakeholders. Everyone should be able to identify what is relevant to them at a glance. However, even within a single company or plant, this can be a major challenge: the number of software applications in use is tremendous, and components transmit data in different formats and in different degrees of detail. Process understanding and contextual knowledge decrease quickly as the ‘distance. from production increases.
Components of the Digital Twin System
Bosch has been addressing the challenge of data homogenization and utilization across machines, systems, software and enterprises for a long time. Now, individual solutions and implementation approaches are consolidated, harmonized and expanded under the same roof of the Digital Twin System for the first time. The principle elements of the Digital Twin System are:
Aspect Model To generate a semantic model for an aspect of a digital twin, a concise yet powerful modeling language is needed. Bosch has developed the Bosch Aspect Meta Model (BAMM), which is based on a preexisting, proven modeling framework for precisely this use. BAMM defines which information particular runtime data contains.
Tenant Relation Management With the Tenant Relation Management application, the aspect model offers a tool for assigning access rights securely. The machine operator has full control over the data and can access all aspects of an asset as well as all aspect models.
Digital Twin Cockpit The success of every solution depends on its user-friendliness and intuitive accessibility of the available information. The Digital Twin Cockpit, which is the central management point for digital twins, is therefore designed to be as clear and uncomplicated as possible. A web-based application makes it easy to set up digital twins in combination with the aspect models, aspect implementation and choice of data sources.
Digital Twin Registry The Digital Twin Registry is the ‘telephone book’ of digital twins. All digital twins and their aspects are listed here, together with basic information about the underlying asset, asset manufacturer and access options. As soon as a new digital twin and its associated aspects have been set up in the Digital Twin Cockpit, this information is transferred automatically to the Digital Twin Registry.
Digital Twin Catalog The Digital Twin Catalog is the ‘semantics and context’ database of the Digital Twin System. It contains the BAMM as well as all aspect models, selected aspect implementations, information about solutions for specific requirements and reference information
Machine Twin Service
The Machine Twin Service provides convenient access to a variety of aspects of a machine, as well as aspect implementations for typical core aspects. Hence, the Machine Twin Service offers a fast, easy and proven starting point for integrating machine data.
The above article is an extract from a white paper that can be downloaded.
For more information: www.bosch-connected-industry.com