The modern world is increasingly interconnected not only by trade and culture exchange, but also by active cooperation and collaboration across frontiers. Smart manufacturing is a reflection of this trend.
Smart manufacturing covers the whole value chain and life cycle of a product, from concept, research and design to production, marketing and distribution, as well as eventual retirement and recycling. It is a technology driven approach that achieves efficiencies by integrating data from multiple technical systems across domains, hierarchies and geographic boundaries.
Core technologies such as digital twins — virtual replicas of physical objects and systems – rely on an efficient exchange of data between different departments, factories and even enterprises.
Related departments and enterprises must be able to share the latest and most accurate information about the production system and its operation. This requires a common base for describing the meaning of the data.
Cost has therefore been a major challenge, as different applications have often required custom implementations in order to make it possible for them to understand and share the same data. “Traditionally, this information has been distributed in different formats, including drawings, lists and data sheets,” explains IEC expert Thomas Hadlich.
“It is presented in different structures and identified differently, for example using different denominations for the same assets or for the same data points. It means the same data must be inputted multiple times and worst of all, the latest information updated in one engineering tool is not automatically reflected in the same data in another engineering tool.”
The international standard IEC 62832, which is currently being updated, addresses these challenges by providing a common reference for the digitization of data related to production systems. The standard for the Digital Factory framework sets out common rules for utilizing data based on computer-understandable data attributes and classifications.
These annotated values facilitate the exchange of data within one production system between machines of different manufacturers or between different companies.
The Digital Factory framework is based on an existing standard, IEC 61360-2, which defines a common data dictionary (IEC CDD) providing classifications and metadata definitions for describing products in an unambiguous way. The original aim was to provide product data and to support procurement of electrotechnical products.
Companies use the definitions to provide standardized descriptions of specifications, thereby enabling interested customers to understand the characteristics of the product. Product data based on such dictionaries provides semantically rich product descriptions.
The new standard applies this approach to system engineering workflows.
The Digital Factory framework essentially describes data in a way that makes it understandable anywhere in the world. It does this by using data dictionaries as a common base for identifying and for providing semantic information for engineering data.
Defining the framework as an international standard makes it easier to develop interoperable engineering software and tools, as well as enabling multiple enterprises around the globe to use information collaboratively.
When a company provides a component to another company the first step is to exchange information about the component. With the Digital Factory framework, they are able to provide quality data, including data for monitoring the production.
Rather than simply exchanging goods, they are providing services and information about the services.
The Digital Factory framework
- IEC 62832-1:2020 PRV
Industrial-process measurement, control and automation – Digital Factory framework – Part 1: General principles
- IEC 62832-2:2020 PRV
Industrial-process measurement, control and automation – Digital Factory framework – Part 2: Model elements
- IEC 62832-3:2020 PRV
Industrial-process measurement, control and automation – Digital Factory framework – Part 3: Application of Digital Factory for life cycle management of production systems
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