CNO Datavalidation solution version 7 introduces a new, groundbreaking feature, namely the use of AI to generate validation rules based on company data. 

 The new version comes with an optional AI extension to generate checking rules based on your data. Data from parts lists, parts, materials and documents are brought together and analyzed in an AI engine. Commonalities are determined or derived from the abundance of this data. These commonalities can then be used directly to create new test rules in the CNO Validation Framework.

The basic module is extended to include further checks for document content and the comparison of data from different sources. The top priority was to make the solution easy to use in all Teamcenter applications.

The Validation Framework offers you the possibility to:

• Simplification and securing the product development process
• Ensuring data quality in the PLM system
• Avoid inconsistent data already during the creation
• Optimization of the training of new employees
• Simplification of the data collection
• Consistency checks over different systenes

A large number of extensions and improvements increase the application possibilities of our solution with the aim of optimizing your work with Teamcenter.

What’s New
Extensions to make comparison and reporting easier

• Simple creation of BOM- or Revision Compare Reports
• Report generation via Drag&Drop
• Fully integrated in the validation solution
• Embedding external sources (Mindsphere, SAP, Polarion, etc.)

Configuration Assistent

• Integration in Active Workspace and Rich Client for the creation of check rules
• Option to define post activities for automated corrections
• Usage of templates to simplify complex validations without a deep knowledge of the datamodel
• Use of a check directory for an easy reuse of checks

AI-supported check creation

Use cases:

• Determines relationships from past BOMs that serve as templates for future BOMs, e.g. dependency of a color on a customer
• Identification of patterns and best practices
• Cleanup option to remove errors in the patterns, e.g. customer name spelled incorrectly and correctly

Functionality:

• Data analysis of your data outside the PLM/ERP systems defined extracted information
• Check rules obtained can be evaluated and then directly used for the validation via an dictionary

Check Features

• Reuse of CHECK configurations depending on check results
• Simplifications when defining tests via extended templates
• Use of CHECK categories for better visualization of the results
• General availability of aliases for simplified configuration
• Improvements to accessing external sources
• Scripting optimizations
• …

Cleanup and Correction Features

• Extension for automatic creation of BOM items or for revision
• Optimized AutoFill integration
• Reporting and Compare usage option

Overview

Demo

More Infos on YouTube
Simplified release process
AutoFill and Smart Forms on Active Workspace