Large Scale Reverse Engineering
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1 Large Scale Reverse Engineering John Costello 7/26-28/2011 BOEING is a trademark of Boeing Management Company. EOT_RT_Sub_Template.ppt 1/6/2009 1
2 Definition of Reverse Engineering Boeing By using the Normal or As-Built condition of an object to lay out construct and design in 3D space. Obtaining and use of actual measurement data that allow virtual product modeling for purposes of design, manufacturing, and support. This can also be used to convert physical master tools to virtual tools EOT_RT_Sub_Template.ppt 2
3 Design Process Migration Legacy A/C Design Engineering Prints Pictures Tribal Knowledge MOD Design Process & Producability Current State Aircraft Modify to fit on Assembly Design/Modfication Low First Time Quality Engineering Prints As Built Data RE MOD Design Process & Producibility Interface Design Future State Aircraft Design/Modification Low Risk RRE Documents the As-Built Physical Interfaces EOT_RT_Sub_Template.ppt 3
4 Benefits & Uses Visualization Texture Mapping Photo-realistic Rendering Design in Context Reference Modeling Collaborative Design Reviews Configuration Control Trend Analysis Parts Assemblies Installations Tooling Facilities Characterization Part/Model/Assy. Verification Certification EOT_RT_Sub_Template.ppt 4
5 Reverse Engineering Uses Reference Modeling Construction of Reference Models using RE data with the level of granularity to determine detailed interfaces, stay out zones, long system runs, etc. When: Prior to design layouts and detail design Model Validation Construction of Reference Models using RE data to validate existing Engineering designed models to the As-Maintained Configuration When: After detail design Re-Engineer Construction of Engineering Models using RE data with interpretation of design intent to fabricate parts When: No 3-D model exists, or existing engineering is insufficient to fabricate replacement parts Reverse Engineering To define parts or interface models using RE data with no interpretation of design intent implied by point cloud (use data as is) When: To establish the As-Maintained Configuration EOT_RT_Sub_Template.ppt 5
6 Large Scale Reverse Engineering Multi Fleet Configuration and Aero Issues EOT_RT_Sub_Template.ppt 6
7 767A Tanker EOT_RT_Sub_Template.ppt 7
8 767 Tanker WARP EOT_RT_Sub_Template.ppt 8
9 767 Tanker WARP EOT_RT_Sub_Template.ppt 9
10 767 Tanker WARP EOT_RT_Sub_Template.ppt 10
11 EOT_RT_Sub_Template.ppt 11
12 767 Tanker WARP Point Cloud Model Data modeled in CATIA V-5 EOT_RT_Sub_Template.ppt 12
13 767 Tanker WARP Scan Data Data modeled in CATIA V-5 EOT_RT_Sub_Template.ppt 13
14 Time Line WARP & Pylon OML Measurements Initial WARP Measurements 2. WARP and Wing 3. WARP, Pylon, and Wing 4. WARP, Pylon, and Wing a) I4 with LH pod SN 5 & RH SN 12 (Dec 10) b) I2 with LH pod SN 9 & RH SN 6 (Jan 11) c) I3 with LH pod SN 7 & RH SN 8 (Feb 11) d) I2 RH with pod SN 2 & pylon that was with SN 1 (Feb 11) e) I2 RH with pod SN 1 (Feb 11) 5. WARP Tilt and Toe a) I1 with LH pod SN 11 & pylon SN 2 and RH SN 6 pod/pylon b) I2 with LH pod SN 9 & RH SN 6 14 EOT_RT_Sub_Template.ppt 14
15 Data Analysis WARP Tilt Deviation I2 LH (SN 9 pod/pylon) is deg nose high RH (SN 6 pod/pylon) is deg nose low WARP Toe Measurements I1 Nominal toe is 3 deg nose inboard LH (SN 11 pod w SN 2 pylon) is deg nose inboard RH (SN 6 pod/pylon) is deg nose inboard I2 LH (SN 9 pod/pylon) is deg nose inboard RH (SN 6 pod/pylon) is deg nose inboard Note: same pod/pylon on two aircraft with very similar toe angles 15
16 Data Analysis - continued EOT_RT_Sub_Template.ppt 16
17 Data Analysis - continued WARP OML Comparison EOT_RT_Sub_Template.ppt 17
18 Data Analysis - continued All WARPs have similar OML deviations Forward section of each WARP is outside of theoretical moldline by more than 0.12 Majority of center and aft sections are within of the theoretical moldline Center section of most WARPs is inside of theoretical moldline by up to Largest deviation is typically on left side of WARPS SN 8 is the only WARP with deviation on both left and right sides 18
19 Data Analysis - continued EOT_RT_Sub_Template.ppt 19
20 Pylon OML Observations Forward two thirds of inboard and outboard sides of pylons are generally within Pylon trailing edges Most inboard and outboard sides of the trailing edge are within SN7 and SN9 trailing edge lower half is twisted outboard by over 0.12 Pylon blisters Forward two thirds are generally within The left pylons have blister aft segments with areas outside theoretical by at least I3 left pylon (SN7) has largest area with aft segment outside theoretical by up to 0.1 Best built pylons I2 RH (was with pod SN 1) I2 RH (pod SN 6) Worst built pylons I2 LH (pod SN 9) I3 LH (pod SN 7) 20
21 Data Analysis - continued EOT_RT_Sub_Template.ppt 21
22 Large Scale Reverse Engineering Virtual Assembly and Predictive Shimming EOT_RT_Sub_Template.ppt 22
23 Scanning for Virtual Assembly & Predictive Shimming Lower Lobe Data High Speed Spherical scanner for Spatial scans Laser Line arm scanner for line of site of interface points EOT_RT_Sub_Template.ppt 23
24 Scanning for Virtual Assembly & Predictive Shimming Lower Lobe Data Laser Line arm scanner data Spherical Scanner data EOT_RT_Sub_Template.ppt 24
25 Aux Fuel Tank & Rails Front Back Scan Data EOT_RT_Sub_Template.ppt 25
26 Aux Fuel Tank & Rails Tank Mounting Rails Scan Data Modeled Data EOT_RT_Sub_Template.ppt 26
27 Virtual Digital Assembly / Predictive Shimming Lower lobe Data Delrin Shims Tank Data EOT_RT_Sub_Template.ppt 27
28 Questions! New Technology taking 20 Century Aircraft to 21 st Century Development and Modification Capabilities th 1st Time Quality, Improved Efficiency & Overall Customer Satisfaction EOT_RT_Sub_Template.ppt 28
29 EOT_RT_Sub_Template.ppt 29
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