Classification is the systematic way of organizing items into groups or categories based on recognized criteria such as geometric shapes or multiple property values.
The classification system organizes objects in a logical and orderly hierarchy, grouping them together based on their commonalities.
Difficulties in Classification
Without classification, it is just difficult to find the proper part when it is needed because parts are not reused, there are numerous duplicate parts, and searching the database takes time. Second, having more duplicate parts makes reuse more difficult. Overall, handling large amounts of data such as standard parts and other machinery parts to prevent duplication is a time-consuming and stressful job in the absence of a standard system.
Advanced Classification (CST – Classification Standard Taxonomy)
– Advanced Classification – It supports data formats and resolves previous data model limits. It is more scalable and adaptive; basic classification used to have a maximum of 200 features, but advanced classification now exceeds that. It functions similarly to simple classification, giving clients choices for smoothly coordinating their business processes. Industry-wide data interchange protocols are supported, including JSON, BMEcat, and OntoML (with AASX, PLM XML, and TCXML planned).
– ECLASS Adv. Classification – “ECLASS is a hierarchical system for categorizing materials, products, and services according to a logical framework and a level of detail that corresponds to the product-specific attributes. ECLASS helps users record a comprehensive product description. It offers clear and concise terminology for suppliers and customers to exchange data.
Basic Classification (Generic Classification)
– Basic Classification – Basic classification creates and maintains a hierarchical classification structure based on the attributes of your workspace objects. It Enables property-based attribute filtering, which uses attribute filters to reduce the number of objects. Compare the objects to make informed design choices. A maximum of 200 attributes can be defined.
– Classification Presentation Layer – The Classification Presentation layer ensures interoperability between the Rich Application Client and the select Active Workspace clients, providing users with an intuitive, visual experience that includes additional features not found in the Rich Application Client.
– Library Management – It leverages underlying classification information and allows businesses to fill purpose-based groups of parts from the classification Presentation layer depending on specific business requirements.
– Specification – Teamcenter includes a Specification Management module that uses limitations from designer tools like NX to provide only valid design data.
Implementation Strategy
To ensure successful implementation, the categorization implementation strategy goes through several steps, as depicted in the image.
Teamcenter Classification Capabilities
– User-friendly structure – It provides Comprehensive user-definable classification structures, as per specific industry requirements.
– Better Visual Navigation – Visual Navigation for browsing classification hierarchy makes it more convenient
– Resizable panels and Flexible layout – Re-sizable panel allows leveraging full functionality of the classification application when classifying the objects. Its Flexible layout allows viewing more information as per user need
– Extremely versatile search engine – It has a highly flexible search engine enabling the use of all defined attributes, Boolean operations, wild cards, and ranges Shape Search engine makes finding similar objects easy
– Shape search functionality – Shape Search engine makes finding similar objects easy. It narrows down the object search by applying attribute filters.
– Filter and compare objects – Ability to find and compare object properties which makes decision making easy.
– Integrated JT file viewer – Integrated 2D/3D viewer based on JT file format.
– ECLASS Library – ECLASS functionality establishes a common classification scheme that everyone can use. It simplifies electronic information exchange across industry segments by using standardized product terms/descriptions so that product data can be exchanged across sectors, countries, languages, and industries conveniently.
– Classify with AI – The use of AI makes the work easy by suggesting auto-classification hence resulting in time reduction.
Business Benefits
– Classification encourages the usage of standardized design components, makes them easy to identify and reuse, simplifies inventory control, and removes redundant data.
– It has been observed that classification saves 80% of the time spent on design for brand-new products with high reuse rates.
– The designer can save time and focus their efforts on creating the most viable product innovations.
– Classification lowers 30-40% of the duplication of parts given by the manufacturer because most of the parts already have adequate substitutes.
– Annual carrying cost of around $4,500 to $23,000 can be reduced by using the substitute parts
Library Management and Specification
With the help of Teamcenter’s Library Management layer, which makes use of underlying classification data, businesses can create collections of components from the Classification Presentation layer specifically tailored to meet their business requirements. Furthermore, Teamcenter includes a Specification Management module that allows designers to apply constraints from tools like NX to provide only legitimate design data.
After creating a library of parts, a user can reduce the number of acceptable components by applying a set of specification rules. For example, if the designer is selecting components for a marine industry pipeline design and has requirements such as matching a stainless-steel pipe with a 3-inch diameter and rated for a specified temperature and pressure, only components that meet those constraints will be displayed.
Classification with AI
Siemens has integrated AI and machine learning into Teamcenter’s classification module.
– Network between Teamcenter and classification data – An AI engine uses object classification in Teamcenter to create a neural network of classification knowledge.
– Prediction Accuracy – More components are classified; the neural network is gradually changed to improve prediction accuracy.
– Functional with Geolus Shape Search – The AI engine may integrate with Siemens’ Geolus shape search solution (optional; available if the ecosystem allows); for more accurate classification, a Closed Loop Weighted algorithm (patent pending) integrates meta-data and shape recommendations.
– Auto-classification – Auto-classification has built-in review processes that allow subject matter experts to confirm or modify classifications, and users can run them as background jobs.
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