Presentation is loading. Please wait.

Presentation is loading. Please wait.

Dipl.-Ing. Peter Binde KBE-System and Case-Library for UG-Structures EUUG Usermeeting 2003 Peter Binde C ase B ased E ngineering.

Similar presentations

Presentation on theme: "Dipl.-Ing. Peter Binde KBE-System and Case-Library for UG-Structures EUUG Usermeeting 2003 Peter Binde C ase B ased E ngineering."— Presentation transcript:

1 Dipl.-Ing. Peter Binde KBE-System and Case-Library for UG-Structures EUUG Usermeeting 2003 Peter Binde C ase B ased E ngineering

2 Dipl.-Ing. Peter Binde Content - Dr. Wallner Group - Motivation for a new Assistant System - Case Study: Automotive-Generator - Feature-Processing - Concepts of the CBE-Assistant

3 Dipl.-Ing. Peter Binde Dr. Wallner Group Service around CAD, CAE, PDM Focus on EDS-PLM Products Competences: - Process-analyses and -syntheses - Trainings and workshops - User-support and hotline - Integration-solutions and software-development

4 Dipl.-Ing. Peter Binde Dr. Wallner Group: - Simulation Focus on Design-Embedded Product-Simulation Training, Consulting, Support for CAE Projects shared by Industry & Research Software for Knowledge- Processing C ase B ased E ngineering

5 Dipl.-Ing. Peter Binde Dr. Wallner Group: - The Founder‘s Vision Jens Wallner died this year by a car accident His vision: - High Quality Service, for CAD/CAE/PDM – will continue in the four Wallner-companies, that belong to the Group.

6 Dipl.-Ing. Peter Binde Motivation for a new Assistant System

7 Dipl.-Ing. Peter Binde Present Situation More and more FEA becomes the designers daily work VDI Report about Adam Opel Project: - Designers do FEA themselves -  =71N/mm 2 u=0,4mm  = 72N/mm 2 u=0,8mm Scenario Original Scenario Bördelung Scenario Bead  =80N/mm 2 u=0,9mm Original Vergleich

8 Dipl.-Ing. Peter Binde Deficits - Often special-knowledge is necessary - Different methods for same problems are used - Knowledge stays in the heads of specialists and key users - Examples and summarised methods are only static - Databases organize data, but do not know about the content ?

9 Dipl.-Ing. Peter Binde Solution: - Store all knowledge anyone has learned in past-cases. - Reuse that knowledge Retrieval of most appropriate cases Adapting knowledge to a new Solution Storage of a new solution Case Base Method: - Case Based Reasoning (CBR) Very similar to human learning Superior to application of rules

10 Dipl.-Ing. Peter Binde All we need is: - Two new buttons in our UG-Scenario system:

11 Dipl.-Ing. Peter Binde Questions: - How to store a solution? - How to adapt knowledge from a similar solution? - How to find the most similar cases? Find Adapt Store Case Base Answers: - Extensively use feature-processing - Store the feature-structure of successfully solved cases - Find similar cases by pattern recognition of feature-structures - Let the user interpret and adapt knowledge

12 Dipl.-Ing. Peter Binde Case Study: Automotive Generator Analysis Goals: Find Characteristics, that Contain Knowledge Develop a Structure for that Knowledge

13 Dipl.-Ing. Peter Binde Centrifugal-Analysis of Fan: Characteristics, that Contain Knowledge Design-context Part for analysis & part-properties Load-type: Rotation Form-feature at result: Cutout, Blended Result-type: Stress & validation Mesh-property at result, Geometry- preparation Solver-Parameter Contact-Condition

14 Dipl.-Ing. Peter Binde Generator-Axle under Bending-Load Design-context Form-feature at result Result-type: & Validation Part for analysis & part-properties Support-Condition Mesh-property at result Solver-Parameter Contact-Condition

15 Dipl.-Ing. Peter Binde Acceleration-Analysis of Housing Design-context Part for analysis & part-properties Load-type: Acceleration & Geometry applied to Forces, that result from contacting parts Form-feature at result: Blended Result-type: Stress & validation Mesh-property at result Solver-Parameter

16 Dipl.-Ing. Peter Binde Description of the Situation and Analysis-Task by Computable Elements Effect: Acceleration Adjoining Parts - Form-feature … - Form-feature Analysis-part - Form-feature … - Form-feature Adjoining Parts - Form-feature … Stress-Validation (requested) Contact Screw (4x) Face-Face Coupling Contact Screw (4x)

17 Dipl.-Ing. Peter Binde Structure for Storage of a Task Project Analysis-scenario Part Material Form-feature Contact Solution-Group Load-Effects Part Form-featurePart Form-feature Material Property-aggregation... Form-featureFix Property-aggregation...

18 Dipl.-Ing. Peter Binde Description of a Solution by Computable Elements A solution contains idealization-methods and the result Idealization of face-coupling Restriction of DOFs Idealization of adjoining parts Acceleration-Force on contacting faces Mesh-property in critical area Number, quality, type of elements Idealization of acceleration To be neglected Idealization of screw-connections Neglected pre-load Rigid Type, … Idealization of material Isotropic, linear Geometry-Idealization Small feature removal Solver-Parameter Result: -location, -type, - validation and -consequence

19 Dipl.-Ing. Peter Binde Feature-Processing

20 Dipl.-Ing. Peter Binde Features Model Design Characteristics A Feature is a Container for a Design Characteristic Example Feature Weld point: included information: - Group of involved elements - Connectivity to geometry - Strength requirements - Tolerances - Costs - Manufacturing processes... Advantage: Weld point can be processed as a „weld point“.

21 Dipl.-Ing. Peter Binde Knowledge Management using Semantics and Features We try to build up models only by use of features This method automatically captures our knowledge and provides standard-solutions CAD Features: (1) Sketch (2) Revolved (3) Pocket (4) Pocket (5) Hole (6) Threads FEM Features: Fixed Face Centrifugal Load Concentrated Mass Stress Calculation Fatigue Calculation rot

22 Dipl.-Ing. Peter Binde Feature-Processing: Simple Example Which feature-description of a hole is preferred This, Because the hole can be recognized automatically by all following processes ??

23 Dipl.-Ing. Peter Binde Extensive Usage of Feature-Processing -The user builds a clear, short feature-structure -The user inserts further knowledge by assigning names, groups, descriptions, comments, …. Insert as much knowledge as possible to the model. Manually definition of features is also possible. Knowledge is captured automatically Knowledge is captured manually

24 Dipl.-Ing. Peter Binde Concepts of the CBE-Assistant C ase B ased E ngineering

25 Dipl.-Ing. Peter Binde Feature Recognition Extracts and classifies all available feature-information to an extended feature-navigator:

26 Dipl.-Ing. Peter Binde Transparency Example: Part-connections are shown completely: “Fan” is connected to “Rotator”. The involved form-features as well as contact properties are shown.

27 Dipl.-Ing. Peter Binde Feature-Attributes Properties of features can be edited

28 Dipl.-Ing. Peter Binde Manual Feature Definition Features, not supported by UG-scenario can be added: Stress-Results are validated on a Blend Form-Feature of the “Fan”. This feature is “extra” inserted by the user.

29 Dipl.-Ing. Peter Binde Tasks / Solutions are Separated CBE feature-information merely includes task (situation) -descriptions Corresponding solutions are given in the found cases Problem-Description: Search for non-linear contact Search for contacting parts, that can separate Meets the “designers language”

30 Dipl.-Ing. Peter Binde Storage of Successful Solved Cases The feature-Information is stored in a xml database Analysis Case Case Libary CBE-System prtxml CAD/FEM-System

31 Dipl.-Ing. Peter Binde Definition of a Problem: Two Possibilities Advantage: All existing features are used automatically 1. Build up features in the CAD/FEM-system 2. Start CBE-system 3. Optional insert further knowledge 4. Start search 1. Build up features in the CBE-system 2. Start search Advantage: This method can be used with any CAD/FEM-system

32 Dipl.-Ing. Peter Binde Similarity-Measurements: Method A: Find “Similar Features” Incremental ranking of a requested feature-class based on a user-weighted “Manhattan-Distance”: Example: Requested feature-class: Part n=10 Attributes + Weights Example: Number of requested results: 6

33 Dipl.-Ing. Peter Binde Similarity-Measurements: Method B: Find “Similar Feature-Structures” Exact sub-graph matching algorithm Developed by:Dennis Shasha, Courant Institute,New York University& Rosalba Giugno, Math & Computer Science, University Catania

34 Dipl.-Ing. Peter Binde Example P Task-pattern: A Test-pattern: Stress-analysis on a sheet-metal-bead containedIn(P,A) = true

35 Dipl.-Ing. Peter Binde

Download ppt "Dipl.-Ing. Peter Binde KBE-System and Case-Library for UG-Structures EUUG Usermeeting 2003 Peter Binde C ase B ased E ngineering."

Similar presentations

Ads by Google