Know-how feedback based on manufacturing features (STEP-NC Server)

Transcription

1 Know-how feedback based on manufacturing features (STEP-NC Server) M.Sc. Yong Tak Hyun Laboratory for Machine Tools and Production Engineering Aachen University Germay 12. February 2003

2 Contents 1. Introduction, objective and approach 2. Acquisition, representation and reuse of the know-how 3. Prototype development and case study 4. Perspective and conclusion

3 Today: Restricted exchange of information between the planning department and the shop floor Planning department Shop floor CAD/CAM/CAPP Design and planning data NC programming Postprocessor G-Code Modification of NC programs CNC Geometry data + Technology data Toolpath simulation Suggestion for the improvement Direct conversation Notes Know-how Repeat of similar modifications F(x),... Knowledge-base (Catalogue, rules and formulas) Difficult to model the cutting process Vendor-specific catalogues Diversity of the information Missing the practical know-how Difficult to maintain Missing integration of the know-how of the machine operator Difficult to share the direct conversation with another departments or staffs Ambiguous manual notes No automated connection between technological modifications and geometry data Demand for ❶ Open, common interface between CAD/CAM systems and NC controllers ❶ Reuse of the shop-oriented know-how of the skilled worker

4 Objectives and requirements CAD/CAM/CAPP General knowledge of the NC programmer Objectives of the development ❶ Acquisition of the experience data from the daily NC machining process ❶ Reuse of the know-how of the machine operator for the new NC programming How to compromise Practical knowledge of the NC operator NC machine Requirements ❶ Complete data model ❶ Easy integration in the CAD/CAM/CNC process chain ❶ Simplified acquisition of the know-how ❶ Transparency in solution finding ❶ User-friendliness: support of user interaction ❶ Possibility for evaluation ❶ Low effort for maintenance

5 Approaches Data model CAD/CAM/CNC integration Simplified know-how acquisition Transparent solution finding User-oriented Evaluation possibility Easy maintenance Know-how acquisition Know-how representation Know-how reproduction Know-how maintenance ❶ STEP-NC data model as a bi-directional interface + Version/variant management + Data model for the rule base ❶ Acquisition of the know-how - Analysis of the modifications in the STEP-NC file - Which machining parameters were changed and what was the effect? ❶ Storage and representation of the know-how - Object-oriented handling of the STEP-NC data elements - The manufacturing feature DB as a container of the experience data - Shop-oriented rules: clustering the experience data to groups ❶ Reuse of the know-how for further NC programming - Similarity principle: search for similar manufacturing feature cases - Application of shop-oriented rules - Case-based Decision Support System: proposals for the user ❶ Automated adaption of shop-oriented rules - Feedback of the violated rules - Attachment and branching of the rules - User-defined problem area

6 Manufacturing feature database for the storage of the experience data Project Manufacuring feature database (STEP-NC server) Workplan Workingstep Workpiece Material properties Geometrical surroundings Pocket Round_ hole Manufacturing_feature Operation STEP-NC file Form / shape Tolerance Surface condition Machine function Cutting strategy Cutting parameter Cutting tool ❶ The manufacturing feature defined in STEP-NC comprises all parameters for describing the experience data of the machine operator. ❶ Object-oriented structure of STEP-NC enables to build an object-oriented database easily.

7 Principle design of a STEP-NC server Closed loop between the planning department and the shop floor for the integration of the know-how of the machine operator Planning department CAD/CAM/CAPP STEP-NC Server Case-based Decision Support System Shop floor CNC Geometry data Material data Tolerance data Technology / operation data Manufacturing CAM-planned NC programs feature database Variant management of NC Programs including their objects + Know-how Reproduction of the know-how Import optimised Objects (e.g. operations) + Experience data Acquisition of the know-how of the machine operator same? No Actualisation of the rule base Shop-oriented rule base F(x) Optimised NC programs Representation of the know-how Optimised NC programs + Acquisition of the know-how Phenomena, effect & environment

8 Contents 1. Introduction, objective and approach 2. Acquisition, representation and reuse of the know-how 3. Prototype development and case study 4. Perspective and conclusion

9 Analysis of the trouble shooting process of the NC program CAM-planned NC program Raw material Constraints (constant parameters) - Workpiece geometry and material - Quality requirements - Performance of the machine Machining parameters (modifiable parameters) - Tool selection - Operation sequence - Cutting parameters - Cutting strategies + Machining process Environment (dynamic parameters) - Temperature - State of the machine... Finished part (qualified) Phenomena and effect - Surface condition - Geometrical accuracy - Tool breakage - Heavy burr... Optimised NC program Statement of the experience Change of the modifiable parameters For a given constraint A, the parameter B was changed to improve the phenomena C (to achieve the effect C) under the environment D. Know-how of the machine operator

10 Extraction of shop-oriented rules from the experience data Acquisition of the experience data Machine Operator Feature: Round_hole Effect Modifications Diameter Depth Surface of the roughness modification Type A - 1 B mm 40 mm 10 Ra Deformation Feedrate: 25,4 -> 20 Burr Feedrate reduction at reduction the end: 60% at the side mm/min Round hole - workpiece material: Ck45 - diameter: 20 mm - depth: 40 mm - surface roughness: 10 Ra - bottom condition: through Machine - ID: Type A-1 Machine operator -ID: B-12 Parameters and their values where to apply the experience data Planned machining parameter - cutting tool: drill 1 - feedrate: 25,4 mm/min - spindle speed: 500 rpm Effect of modifications - reduction of the burr - reduction of the workpiece deformation Optimised machining parameter - feedrate: 20 mm/min - feedrate reduction at the bottom: 60% Table no. 1 Rule 1 IF material Brinell hardness (kg/mm 2 ) about 200 Yield strength (kg/mm 2 ) about 35 Tensile strength (kg/mm 2 ) about 7 THEN Decision table no. 11 Table no. 11 Rule 1 IF Feature - Geometrical surroundings Material thickness - bottom (mm) Material thickness - side (mm) Neigboring operation code 0 about THEN Feedrate reduction 80% Feedrate reduction at the end 60% Extraction of shop-oriented rules by clustering the experience data ❶ Objective of the clustering - To bound the parameters for if-condition and their values ❶ First level of clustering is considered in the manufacturing feature defined in STEP-NC ❶ Further clustering according to the effect of the shop-floor modification e.g) burr reduction, tool breakage avoidance

11 Case-based reasoning: clustering according to the effect of the modification if-condition Full Full set setof of parameters Tolerance decision Cutting parameter modification Surface condition Rake angle Tool exit angle Yield strength of the material Tensile strength of the material Feature geometrical surroundings 10% 20% 30% 40% 50%

12 Case-based reasoning: clustering according to the effect of the modification if-condition related to decision Dominant influencing parameters Rake angle Tool exit angle Yield strength of the material Tensile strength of the material Feature geometrical surroundings Problem (Effect) Tool breakage Heavy burr Long chips Cause Wrong drill type Poor coolant condition Incorrect speed & feed Incorrect drill point Poor point grind Solution Correct drill type/size Use straight flute Use stub length Use three-flute Use slower helix Use parabolic design Increase coolant Increase mixture Reduce RPM Increase feed Increase RPM Reduce feed Repoint drill Change point style Cutting parameter modification 10% 20% 30% 40% 50% Certainty Availability Middle Literatures for machining tests High Low Middle High Analysis of Monitoring Know-how of the machine operator the NC program

13 Flow diagram for the reuse of the know-how Similarity analysis Similar features exist Planned NC program Search for similar features? Y N Import of the operation data Manufacturing feature database Update of the operation data by applying the rules Search for shop-oriented rules Y? Shop-oriented rule base Applicable rules exist N Acceptance of the planned operation data Actualisation of the shop-oriented rule base Actualisation of the manufacturing feature database Possible choices and final selection Adaption of the geometrydependent parameter Machining Optimised NC program Effect of modifications

14 Similarity analysis based on Fuzzy set theory Similarity for 2 parameters case Similarity representation based on Fuzzy set theory Parameter Y Y new Y 0 Similarity Similarity Membership identical 1 very similar similar barely similar not similar X 0 X new Traditional group technology Parameter X 0 X 0 T A T B T C T D X new Parameter value Parameter for an experience case = (X 0, Y 0 ) Parameter for a new case = (X new, Y new ) Existing manufacturing feature Geometrical surroundings Tolerance & surface condition Metal removal volume Workpiece material property New manufacturing feature Global similarity value

15 Automated attachment and branching of the shop-oriented rules Planned NC program Modification to achieve effect A Optimised NC program Parameter Y Y 0 Rule set A Rule A-1 X 0 Parameter X New planned NC program Application of rule set A Updated NC program Parameter Y Rule set A Rule A-1 Rule A-11 Branched rule New planned NC program Application of rule set A New problem area Case-based rule for a case that depends on parameters X and Y Modification to achieve effect A Optimised NC program Rule A2 Attached rule Parameter X Updated NC program Modification to achieve effect B Parameter V V 0 Rule set B Rule B1 Optimised NC program U 0 Parameter U Case-based rule for a case that depends on parameters U and V

16 Contents 1. Introduction, objective and approach 2. Acquisition, representation and reuse of the know-how 3. Prototype development and case study 4. Perspective and conclusion

17 Prototypical implementation CAD/CAM/CAPP STEP-NC Server NC controller CATIA V5, Dassault Systèmes STEP-NC programs Manufacturing feature DB Shop-oriented rule base F(x) STEP-NC programs STEP-NC programs Sinumerik 840D, Siemens TOPAC, WZL User-interface Interactive input of the effect of modification

18 Simulation of the experience data for holes Planned technology data Hole.13 Hole.23 Hole.33 Feature geometry data ID Diameter (mm) Depth (mm) Depth/ Diameter Operation type (STEP-NC) Planned technology data Spindle Feedrate speed (mm/rev) (RPM) s s f s L s s e f e L e L b t d f r Hole ,00 drilling 0, , , Hole ,00 drilling 0,10 509, , Hole ,67 drilling 0,14 339, , Hole ,00 drilling 0, , , Hole ,00 drilling 0,10 509, , Hole ,33 drilling 0,14 339, , Hole ,00 drilling 0, , ,00 1, Hole ,00 drilling 0,10 509, ,00 1, Hole ,00 drilling 0,14 339, ,00 1, Hole.12 Hole.22 Hole.32 Hole.11 Hole.21 Hole.31 Feature ID Effect of the modification Optimised technology data Effect of modification Operation type (STEP-NC) Optimised technology data Spindle Feedrate speed (mm/rev) (RPM) s s f s L s s e f e L e L b t d f r d r d 0 d s t s Hole.11 drilling 0, , , Hole.21 drilling 0,10 509, , Workpiece Hole.31 deformation drilling 0,09 271, , Hole.12 drilling 0, , , Hole.22 drilling 0,10 509, , Hole.32 drilling 0,14 339, , Burr reduction, multistep_drilling Hole.13 deep drilling 0,03 713, ,00 50,00 3,00 2,00 2, ,5 Hole.23 Burr reduction drilling 0,10 509, ,00 50,00 3,00 2,00 2, Hole.33 Burr reduction, workpiece deformation drilling 0,09 271, ,00 50,00 3,00 2,00 2, Modified data Parameters according to the STEP-NC data model 9 experience data for the round hole 7 shop-oriented rules related to deep drilling, workpiece deformation and burr reduction

19 Parameters for the drilling according to the STEP-NC data model d c L a L h T a D t L c L s ❶ Geometry data of the hole L h : Depth of hole D h : Diameter of hole ❶ Depth of drilling L a : Retract plane L b : Overcut length d c : Cutting depth ❶ Tool data T a : Tool tip half angle D t : Diameter of tool L c : Cutting edge length ❶ Feedrate and cutting speed f 0 : Feed s 0 : Spindle L s : Depth of start L e : Depth of end f s : Reduced feed at start s s : Reduced cutting speed at start f e : Reduced feed at end s e : Reduced cutting speed at end t d : Dwell time at the bottom L b D h Reduced feedrate Feedrate L e d0 ds ds db db d0 ds ds dr dr ❶ Multi-step drilling d r : Retract distance d 0 : First depth d s : Depth of step t s : Dwell time step d b : Offset before step Retract speed

20 Simulation of the experience data for pockets Pocket.2 Pocket.1 Planned technology data Geometrical data of feature Cutting tool Planned technology data Approx. Feature ID Volume Type Dimension (length*width* depth in mm) (cm 3 ) Pocket.1 50*45*20 46,53 Pocket.2 40*40*30 46,71 Operation type (STEP-NC) Bottom_and_side _rough_milling Bottom_and_side _finish_milling Bottom_and_side _rough_milling Bottom_and_side _finish_milling Endmill - HSS Endmill - HSS Endmill - HSS Endmill - HSS Diameter (mm) No. of tooth Feed per tooth (mm/tooth) Spindle speed (RPM) removal rate (mm 3 /min) 20,00 4 0, , ,00 5,00 10,00 2,00 2,00 10,00 4 0, ,00 230,40 2,00 2, ,00 4 0, , ,00 5,00 10,00 2,00 2,00 10,00 4 0, ,00 230,40 2,00 2, d a d r a s a b S t L OL L OC C m bidirectional 10,00 - conventional contour parallel - - conventional bidirectional 10,00 5,00 conventional contour parallel - 5,00 conventional Optimised technology data Feature ID Pocket.1 Pocket.2 Impact of modification Process time increasement Surface finish improvement Process time increasement Surface finish improvement Operation type Bottom_and_side _rough_milling Bottom_and_side _finish_milling Bottom_and_side _rough_milling Bottom_and_side _finish_milling Effect of the modification Cutting tool Type Endmill - HSS Endmill - HSS Endmill - HSS Endmill - HSS Diameter (mm) No. of tooth Optimised technology data Feed per tooth (mm/tooth) Spindle speed (RPM) removal rate (mm 3 /min) 20,00 4 0, , ,00 5,00 10,00 2,00 2,00 10,00 4 0, ,00 259,20 2,00 2, ,00 4 0, , ,00 5,00 10,00 2,00 2,00 10,00 4 0, ,00 259,20 2,00 2, Modified data d a d r a s a b S t L OL L OC C m bidirectional 10,00 - conventional contour parallel - - climb bidirectional 10,00 5,00 conventional contour parallel - 5,00 climb Parameters according to the STEP-NC data model 2 experience data for the pocket 2 shop-oriented rules related to process time and surface finish ❶ Feedrate and cutting speed da : Axial cutting depth (mm) dr : Radial cutting depth (mm) as : Finish allowance side (mm) ab : Finish allowance bottom (mm) St : Type of machining strategy LOL : Overlap length (mm) LOC : Overcut length (mm) Cm : Cutting mode (conventional or climb)

21 Import of the optimised operation data for a new workpiece New workpiece STEP-NC Server Similar feature exist? Yes? No Shop-oriented rule base F(x) Import of operations + Update of the operation data by applying rules List of manufacturing features and their operations No Feature type Feature ID Depth (mm) Diameter (mm) Operation type Operation imported? Rule applied? 1 round_hole Hole drilling No Yes 2 round_hole Hole drilling No Yes 3 round_hole Hole drilling No Yes 4 round_hole Hole drilling Ja Yes 5 closed_pocket Pocket bottom_and_side_rough_milling Yes No bottom_and_side_finish_milling Yes No 6 closed_pocket Pocket bottom_and_side_rough_milling No Yes bottom_and_side_finish_milling No Yes Import of 3 operation Application of rules for 5 operation In the same manner, the sequence of operation, cutting strategy and cutting parameters can be imported from the STEP-NC server in batch in principle.

22 Contents 1. Introduction, objective and approach 2. Acquisition, representation and reuse of the know-how 3. Prototype development and case study 4. Perspective and conclusion

23 State of development and items to do for a pilot product Progress Items to do STEP-NC Data Handling (Read/Write, DBMS) 80 % Handling of special curve types Graphical representation of feature Revision history (Version and variant management) 70 % Handling of more manufacturing features Know-how manipulation algorithm (Acquisition, representation, reuse) 60 % Manipulation of geometrical surroundings Addition of problem areas covered Trend analysis Interface with the planning department (Data consistency) 60 % Tolerance & surface condition input Integration with the tool database Integration with the material database Interface with shop floor (Data consistency) 70 % March 2003 Feedback of modifications in the toolpath level Feedback of the inspection result Machine-dependent data feedback

24 Perspective Profit / Effort Profit Accumulation and reuse of the know-how Saving in the NC programming time Saving in the test machining effort Effort System development and maintenance Training Hardware and software cost Application time Workpiece/feature spectrum of a manufacturer Know-how for a special / critical machining cases Features covered by an experience data Accumulation of the know-how in a specific machining area

25 Conclusion: Benefits of the application of the STEP-NC Server ❶ Use of the optimised manufacturing features and operations (as defined in STEP-NC) as building blocks for the NC programming ❶ Easy integration in the CAD/CAM/CNC process chain: - Bi-directional exchange of STEP-NC file ❶ Simplified acquisition of the know-how of the machine operator ❶ Hybrid representation of the know-how: - Manufacturing feature database and shop-oriented rule base ❶ Transparent reuse of the know-how by applying similarity principle ❶ User-oriented solution for the decision support ❶ Easy maintenance: - Automated accumulation of shop-oriented rules from daily NC processes ❶ Reduction of efforts for the test machining at the shop floor ❶ Reduction of efforts for the NC programming at the planning department ❶ Share of the machining know-how within a shop floor, company or customer