Rapid prototyping and manufacturing benchmarking

RAPID PROTOTYPING AND MANUFACTURING BENCHMARKING MANI MAHESH B.E (with Distinction) A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF DOCTOR OF PHILOSOPHY NATIONAL UNIVERSITY OF SINGAPORE 2004 Dedicated to my beloved dad, Late Mr. V. Mani, You are the greatest father, ever. Acknowledgements I would like to express my deepest appreciation to my supervisor, A/P. Y. S. Wong, who has the attitude and the substance of a genius: he incessantly and convincingly conveyed a spirit of exploration in regard to this research. Without his guidance and persistent help, this research would not have been possible. I have benefited much from his candid ideas and rigorous approach in research. My sincere thanks to my cosupervisor, A/P Jerry Fuh for his guidance, direction, strong encouragement and support throughout my period of study. My heart felt thanks to A/P. H. T. Loh for his supportive ideas and assistance during the course of this research work. Words alone cannot express my gratitude I owe to my mother Mrs. Uma Mani, sister Ms. Mala Mani, brother-in-law Mr. Radha Ramana and my niece Karishma for their encouragement and support throughout my period of research. Special thanks to my student colleagues and my lab mates for making the working atmosphere cosy and efficient for research. My thanks to Tamasek Polytechnique, for permissions to use their RP&M machines. I am grateful to all people who have directly or indirectly helped me with the completion of this research. Finally, I thank the National University of Singapore for rewarding me with a Research Scholarship and the Department of Mechanical Engineering for using the facilities. i Table of Contents Acknowledgements i Table of contents ii Summary vi List of Illustrations viii List of Tables xii Chapter Introduction 1.1 Background 1.2 Scope of research 1.3 Thesis Outline Chapter Literature Review 2.1 Introduction 2.2 Review of RP&M Benchmark Parts 2.2.1 Kruth, 1991 2.2.2 Gargiulo - 3D Systems, 1992 2.2.3 Wohlers, 1992 2.2.4 Lart, 1992 2.2.5 Van Putte, 1992 10 2.2.6 Schmidt, 1994 11 2.2.7 Aubin, 1994 11 2.2.8 Juster and Childs, 1994 12 2.2.9 Ippolito, Iuliano and Fillippi, 1994 12 2.2.10 R.Ippolito, L.Iuliano and A.Gatto, 1995 14 2.2.11 Shellabear - EOS Gmbh 1998 and Reeves & Cobb, 1996 14 2.2.12 Jayaram, Bagchi, Almonte, 1994 16 2.2.13 Xu Fen and Shi Dongping, 1999 17 2.3 Summary 20 ii Chapter Benchmarking of RP&M Processes/ Systems 22 3.1 Introduction 22 3.2 Towards Generalized Benchmark Parts in RP&M 22 3.3 Classification of RP&M Benchmarks 23 3.3.1 Geometric benchmark 23 3.3.2 Mechanical benchmark part 29 3.3.3 General overview of process benchmarking 32 3.4 RP&M Benchmarking for Performance Estimation 36 3.5 Integrated Benchmarking Process 37 3.6 Measurement of RP&M parts 38 3.7 Summary 39 Chapter Benchmarking for Comparative Evaluation of RP&M Processes/ Systems 40 4.1 Introduction 40 4.2 Case Studies 41 4.2.1 Fabrication of the geometrical benchmark part on SLA 41 4.2.2 Fabrication of the geometrical benchmark part on SLS 43 4.2.3 Fabrication of the geometrical benchmark part on FDM 48 4.2.4 Fabrication of the geometrical benchmark part on LOM 49 4.3 Measurements 52 4.3.1 Measurement of the benchmark parts on the CMM 52 4.3.2 Measurement of the geometrical features 53 4.4 Results and Discussions 53 4.4.1 Geometrical accuracy 53 4.4.2 Surface roughness 55 4.4.3 Warpage analysis on the benchmark parts 56 4.5 Summary Chapter RP&M Process Benchmarking 57 58 5.1 Introduction 58 5.2 Six-Sigma 59 iii 5.3 Towards Sigma Approach in RP&M Process Benchmarking 60 5.5 RP&M Process Benchmarking Methodology 61 5.6 Summary 66 Chapter Benchmarking and Process Tuning of the DLS Process: A Case study 67 6.1 Introduction 67 6.2 Direct Laser Sintering process 67 6.3 Proposed Methodology on the DLS Process/System 68 6.3.1 Process analysis (Step 1) 69 6.3.2 Screening experiments (Step 2) 70 6.3.3 Design of Experiments (Step3) 79 6.3.4 Fabrication (Step 4) 81 6.3.5 Measurements (Step 5) 81 6.3.6 Statistical analysis (Step 6) 82 6.3.7 Experimental verification (Step 7) 88 6.3.8 Standardized benchmarked DLS process (Step 8) 89 6.4 Summary Chapter Web-Based RP&M Decision Support Systems 91 93 7.1 Introduction 93 7.2 Fuzzy Approach to Decision Making 94 7.3 IDSSSRP Fuzzy Decision Methodology 96 7.3.1 Stage 1: Representation of the decision problem 96 7.3.2 Stage 2: Fuzzy set evaluation of the goals and constraints 97 7.3.3 Stage 3: Selection of the optimal alternative 111 7.4 Demonstration of the proposed approach 114 7.5 System Architecture of a Web-based IDSSSRP 127 7.6 7.5.1 Organization of the databases 129 7.5.2 Implementation of the web-based IDSSSRP 132 Summary 135 iv Chapter Conclusion 136 8.1 Contributions 137 8.2 Further work 137 Related publications 140 Bibliography 142 Appendix 153 Appendix 157 Appendix 163 v Summary Rapid prototyping and manufacturing (RP&M) prototypes are increasingly used in the development of new products, spanning conceptual design, functional prototypes, and tooling. Due to the variety of RP&M technologies and processes, resulting in prototypes with quite different properties, planning decisions to select the appropriate RP&M process/material for specific application requirements have become rather involved. Appropriate benchmark parts can be designed for performance evaluation of RP&M systems and processes, and provide helpful decision support data. Several benchmark studies have been carried out to determine the levels of dimensional accuracy and surface quality achievable with current RP&M processes. Various test parts have been designed for the benchmark study. Most RP&M benchmark studies published to date typically involved fabrication of one sample for each case of material and process. Different companies and machine operators could fabricate the parts. Hence, besides the process and the material, there may be other factors, such as the building style and specific process parameters that may affect the accuracy and finish of the part. It is noteworthy that comparisons between different processes or between parts built by different companies have generally been based on statistically very small samples. In RP&M benchmarking, it is necessary not only to standardize the design of the benchmark part, but also the fabrication and measurement/test processes. This research presents issues on RP&M benchmarking and attempts to identify factors affecting the definition, fabrication, measurements and analysis of benchmark parts. vi The aim is to develop benchmark parts and benchmarking procedures aimed at performance evaluation of RP&M processes/materials in terms of achievable geometric features and specific functional requirements. The RP&M benchmarking design and study will contribute to the development of the planning and decision support software for RP&M processes. This research also developes a methodology for benchmarking RP&M processes using six-sigma tools. Case studies have been presented for performance evaluations of selected RP&M processes and process benchmarking. Finally the implementation of a web-based decision support system based on the benchmarking results is presented and discussed. vii List of Illustrations Fig 2.1 Parts produced by different techniques: Kruth Fig 2.2 The in-plane benchmark part: Gargiulo Fig 2.3 General view of the model used in comparative study: Lart 10 Fig 2.4 The Kodak benchmark part: Van Putte 10 Fig 2.5 The IMS benchmark part: Aubin 11 Fig 2.6 The benchmark part: Juster & Childs 12 Fig 2.7 User part created in metric units: Ippolito, Iuliano and Fillippi 13 Fig 2.8 The proposed 3D user part: Ippolito, Iuliano and Fillippi 14 Fig 2.9 Geometric benchmark part: Reeves and Cobb 15 Fig 2.10 Test parts from different RP&M processes: M. Shellabear 16 Fig 2.11 Test part: Jayaram, Bagchi, Almonte 16 Fig 2.12 Benchmark part: Xu Fen 17 Fig 2.13 Benchmark for geometric accuracy: Shi Dongping 17 Fig 3.1 Proposed geometric benchmark part 24 Fig 3.2 Geometric benchmark-top view 24 Fig 3.3 Geometric benchmark front view 25 Fig 3.4 Mechanical benchmark part 29 Fig 3.5 Components from mechanical benchmark part 30 Fig 3.6 Key process steps in benchmarking 34 Fig 3.7 RP&M benchmarking 36 Fig 3.8 Action ladder model in benchmarking 37 Fig 3.9 Flow chart for an integrated benchmarking process plan 37 Fig 4.1 Geometric benchmark part built from SLA-190/250 system 41 Fig 4.2 Ability of SLA to build all features including Pass/fail features 42 viii Bibliography 79 Stamatis D.H, ‘Six Sigma and Beyond: Statistics and Probablity’, St. Lucie Press, 2003. 80 Stamatis D.H, ‘Six Sigma and Beyond: Design for Six Sigma’, St. Lucie Press, 2003. 81 Stamatis D.H., ‘Six Sigma and Beyond: Design of Experiments’, St. Lucie Press, 2003. 82 User Guide 3D Systems Stereolihography Build station SLA-190/SLA-250. 83 User Guide DTM Sinterstation System 2000/2500 user guide. 84 User Guide FDM 2000/3000 Release 1.0. 85 User Guide Helisys LOM Technology 1015 system. 86 User Manual CMM. 87 Van Putte D.A, ‘ A Brief Benchmarking Study of Rapid Proototyping Processes’, Proceedings of the Third International Conference on Rapid Prototyping, Dayton, OH, June 1992, pp. 251-263. 88 Vouzelaud T, Bagchi A, ‘Adaptive lamina generation for shape dependent process control and/or object decomposition’, Patent Number 5,432,704, 1995. 89 Vuyyuru P, Kirschman C, Fadel G.M, Bagchi A, Jara-Almonte C, ‘A NURBS based approach for rapid prototyping realization’, Fifth International Conference on Rapid Prototyping, Dayton, OH, 1994, pp. 229-240. 90 Watson D, Park S.M, Muraleedharan A, Crawford R, Beaman J, ‘Design Rules for Solid Freeform Fabrication,’ Proceedings of the NSF Design and Manufacturing Grantees Conferences, Long Beach, CA, January 5-8, 1999. 91 Wohlers Terry, ‘Chrysler Compares Rapid Prototyping Systems’, ComputerAided Engineering, Vol. 11, No. 10, October 1992. 150 Bibliography 92 Wohlers Terry, ‘Future potential of rapid prototyping and manufacturing around the world’ Rapid Prototyping Journal, Vol Issue 1, ISSN 1355-2546,1995. 93 Wohlers Report, ‘Rapid Prototyping, Tooling & Manufacturing State of the Industry’ Annual Worldwide Progress Report, 2003. 94 Wong Y.S, Fuh J.Y.H, Loh H.T, Mahesh M, ‘Rapid Prototyping and Manufacturing (RP&M) Benchmarking’, Chapter 3, Software Solutions for RP, (Ed.) Gibson I, PEP Ltd, UK, 2002, pp. 57- 94. 95 Mahesh M, Wong Y.S, Fuh J.Y.H, Loh H.T, ‘Benchmarking for Comparative Evaluation of RP systems and processes’, Rapid Prototyping Journal, vol. 10, No. 2, Emerald Group Publishing Limited, 2004, pp. 123-135. 96 WWW at http://wohlersassociates.com/Wohlers-Talk.html/ 97 WWW at Stereolithography : http://www.3dsystems.com/ 98 WWW at Laminated Object Manufacturing: http://www.cubictechnologies.com/ 99 WWW at Paper Lamination Technology: http://www.kiracorp.co.jp/ 100 WWW at Selective Laser Sintering: http://www.3dsystems.com/ 101 WWW at Fused Deposition Modeling: http://www.stratasys.com/ 102 WWW at Solid Ground Curing : http://www.cubital.com/ 103 WWW at Three dimensional plotting: http://www.solid-scape.com/ 104 WWW at Zcorp: www.zcorp.com/ 105 WWW at Sanders prototype: www.sanders-prototype.com/ 106 WWW at Sandia National Laboratories : http://www.sandia.gov/media/lens.htm 107 WWW at Soligen Inc: http://www.soligen.com/ 108 WWW at Rapid Prototyping and Manufacturing Institute - http://rpmi.marc.gatech.edu /build /research.html/ 109 WWW at Raptia, http://www.raptia.org/ 151 Bibliography 110 Xiangwei Wang, ‘Calibration of shrinkage and beam offset in SLS process’, Rapid Prototyping Journal, MCB University Press, Volume 5, Number 3, 1999, pp. 129-133. 111 Xu F, Wong Y.S, Loh H.T, Fuh J.Y.H, Miyazawa, ‘Optimal Orientation with variable slicing in Stereolithography’, Rapid Prototyping Journal, 3, No.3, 1997, pp. 76-88. 112 Xu Fen, ‘Integrated Decision Support for Part Fabrication with Rapid Prototyping & Manufacturing Systems’, Ph.D. Thesis, National University of Singapore, 1999. 113 Yang Tai Hung, Jackman John, ‘A Probabilistic View of Problems in Form Error Estimation,’ ASME Journal of Manufacturing Science and Engineering, Vol. 119, August 1997, pp. 375-382. 114 Zadeh L.A, ‘Fuzzy Sets. Information and Control’, 8, 1965, pp. 338-353. 115 Zimmermann H.J, ‘Fuzzy Sets, Decision Making and Expert Systems’, International Series in Management Science/Operations Research, 1987. 116 Zhao Zhiwen, Laperriere Luc, ‘Adaptive Direct Slicing of the Solid Model for Rapid Prototyping’, Universite du Quebec a Trois-Rivieres C.P.500, TroisRivieres, Quebec, Canada G9A 5H7. 152 Appendix Appendix Table A1.1. Geometric feature measurements Geometric Features CH CH CH CH CR CR CR CR CR SP SP SP SP SC SC SC SC SC SC HC HC CN CN SLA DM 10.0833 RD 0.0042 DM 10.0950 RD 0.0038 DM 10.0765 RD 0.0066 DM 10.0920 RD 0.0083 DM 10.0621 RD 0.0297 DM 10.0609 RD 0.0029 DM 10.0771 RD 0.0102 DM 10.0833 RD 0.0184 DM 15.1281 RD 0.0055 DM 14.8131 SPR 0.0167 DM 14.9588 SPR 0.0384 DM 14.8575 SPR 0.0196 DM 14.8954 SPR 0.0091 DM 9.6566 CYN 2.7930 DM 4.5793 CYN 1.1759 DM 4.9095 CYN 1.4740 DM 8.4497 CYN 1.9517 DM 3.5727 CYN 2.0019 DM 3.9235 CYN 1.3723 DM 10.7810 CYN 1.0227 DM 8.9863 CYN 2.7811 ANG 36.8200 CON 0.0114 ANG 37.2013 CON 0.0162 SLS DM 8.9668 RD 0.3907 DM 8.9725 RD 0.2037 DM 8.9881 RD 0.1857 DM 9.2271 RD 0.2356 DM 9.2545 RD 0.2900 DM 8.8200 RD 0.4012 DM 8.8254 RD 0.3126 DM 8.7569 RD 0.2690 DM 14.0473 RD 0.2611 DM 17.0193 SPR 0.3076 DM 17.1279 SPR 0.1183 DM 17.5853 SPR 0.1870 DM 17.6982 SPR 0.2150 DM 7.4202 CYN 2.6043 DM 4.2680 CYN 1.4285 DM 3.7845 CYN 2.1065 DM 8.4434 CYN 2.4248 DM 5.2572 CYN 1.4967 DM 4.5556 CYN 1.6636 DM 9.0160 CYN 2.4199 DM 8.7845 CYN 2.3168 ANG 38.6876 CON 0.0984 ANG 38.8811 CON 0.0451 FDM DM 10.0024 RD 0.0073 DM 9.9759 RD 0.0821 DM 10.0030 RD 0.0333 DM 10.0055 RD 0.0085 DM 9.9803 RD 0.0069 DM 9.9582 RD 0.0048 DM 10.0122 RD 0.0095 DM 10.0063 RD 0.0106 DM 15.0151 RD 0.0518 DM 14.9896 SPR 0.0075 DM 14.9556 SPR 0.0355 DM 14.8421 SPR 0.0304 DM 14.8352 SPR 0.0589 DM 7.5251 CYN 2.0692 DM 3.5959 CYN 1.1888 DM 3.0930 CYN 1.7969 DM 8.0537 CYN 2.4296 DM 3.6848 CYN 1.3674 DM 3.3157 CYN 1.8819 DM 8.1143 CYN 2.6523 DM 8.3199 CYN 2.3107 ANG 36.9203 CON 0.0158 ANG 36.9928 CON 0.0321 LOM DM 9.9089 RD 0.0391 DM 9.9204 RD 0.0108 DM 9.8299 RD 0.0484 DM 9.8783 RD 0.0476 DM 9.8214 RD 0.0027 DM 9.8079 RD 0.0098 DM 9.7998 RD 0.0290 DM 9.8457 RD 0.0122 DM 14.8728 RD 0.0062 DM 15.2477 SPR 0.0204 DM 15.2621 SPR 0.0882 DM 15.1629 SPR 0.0732 DM 15.1495 SPR 0.0698 DM 7.7351 CYN 2.2595 DM 3.4897 CYN 1.4700 DM 3.8761 CYN 1.6755 DM 8.1104 CYN 2.9025 DM 3.8603 CYN 1.8887 DM 3.5200 CYN 2.3731 DM 8.7872 CYN 2.4081 DM 9.1013 CYN 1.5369 ANG 35.2223 CON 0.0241 ANG 35.7721 CON 0.0643 153 Appendix Index: DM: Diameter, RD: Roundness, CYN: Cylindricity, SPR: Spherity, CON: Concity, FLT: Flatness, CCN: Concentricity, SQR: Squareness, PAR: Parallelism, ANG: Min.Angularity Table A1.2. Relative measurements Relative Measurements Distance: HS HS SB Flatness: SB FB Symmetry: SP Coaxiality: HC Perpendicularity SB- CB Angularity Wedge Parallelism CB SLA SLS FDM LOM 61.4881x 60.5284 25.1545 x 25.1210 170.1038x170.3304 0.1468 0.0414 145.8939,145.7701 109.8494 109.7736 62.0734 x 60.6094 26.1230 x25.5292 170.8658x170.1549 0.1357 0.0680 146.4939,146.7701 110.3554,110.3855 60.9950 x60.0947 25.0024 x25.0910 170.1738x169.8054 0.1397 0.0184 145.3584,145.3284 109.8965,109.7894 61.1436 x60.3210 25.1909 x25.2777 170.1867x170.9608 0.2731 0.0287 146.8965,146.7832 110.2500,110.1925 RD 0.0099 CCN 0.1843 RD 0.0065 CCN 0.1939 FLT 0.0224 SQR 0.1136 FLT 0.0381 SQR 0.1147 ANG 153.419278 ANG 148.903473 FLT 0.0018 PAR 0.0772 FLT 0.0024 PAR 0.0576 RD 0.2737 CCN 0.2598 RD 0.3025 CCN 0.1723 FLT 0.0075 SQR 0.5572 FLT 0.0026 SQR 0.7023 ANG 155.115186 ANG 150.472539 FLT 0.0374 PAR 0.4744 FLT 0.0304 PAR 0.5213 RD 0.0530 CCN 0.2062 RD 0.0219 CCN 0.2444 FLT 0.0052 SQR 0.0358 FLT 0.0554 SQR 0.1758 ANG 153.797042 ANG 149.247875 FLT 0.0050 PAR 0.0933 FLT 0.0022 PAR 0.0162 RD 0.0285 CCN 0.1645 RD 0.0371 CCN 0.2917 FLT 0.0970 SQR 0.3066 FLT 0.0409 SQR 0.5448 ANG 153.641372 ANG 148.010241 FLT 0.0078 PAR 0.2333 FLT 0.0014 PAR 0.0568 Roundness is like profile of a line except that the curve is closed to itself. Flatness is the three-dimensional equivalent of straightness. Cylindricity is the three-dimensional equivalent of roundness. Concentricity is a tolerance where the axis of a feature is required to be coaxial to a specified datum regardless of the datum’s and the features size. Parallelism is a tolerance, which controls independent surfaces and axes, which are to be equal distances from a datum plane or axis. Perpendicularity is a tolerance, which controls surfaces and axes, which are 90 degrees from the datum axis. Angularity is the tolerance of an axis surface, or centre plane at a specified angle from another feature, datum plane or axis. 154 Appendix Table A1.3. The dimensional error of the various features on the benchmark part Geometric feature SP1 SP2 SP3 SP4 CR1 CR2 CR3 CR4 CR5 CH1 CH2 CH3 CH4 SC1 HC1 CN1 SC2 HC2 CN1 SC3 HS1 (60) HS2 (25) HS1 (60) HS2 (25) SB Symmetry SP SP Perpendicularity Perpendicularity Parallelism Parallelism Coaxiality Coaxiality Angularity Dimensional error (deviation) Exp No Exp No Exp No Exp No Exp No Exp No Exp No 0.1391 0.1636 0.1025 0.0788 0.0898 0.0744 0.0787 0.0022 0.0925 0.0427 0.037 0.0112 0.0823 0.0369 0.1245 0.1928 0.1659 0.1572 0.0908 0.1214 0.1252 0.0834 0.1094 0.0875 0.0685 0.0679 0.0631 0.0548 0.1385 0.1298 0.1851 0.1318 0.1257 0.1422 0.1356 0.1442 0.1159 0.148 0.1276 0.1171 0.1515 0.1246 0.1456 0.1272 0.1412 0.1366 0.1263 0.1394 0.1119 0.1536 0.1362 0.2187 0.1405 0.131 0.1534 0.1142 0.1232 0.1126 0.1300 0.109 0.1043 0.1182 0.1023 0.1230 0.1127 0.1261 0.1115 0.1068 0.1110 0.1015 0.1346 0.1397 0.1585 0.1224 0.1292 0.1310 0.1229 0.138 0.1412 0.1636 0.1496 0.1449 0.1555 0.1324 0.1275 0.1421 0.1723 0.1518 0.1389 0.1701 0.14 0.0365 0.0441 0.0749 0.0388 0.0165 0.1691 0.0992 0.0411 0.0663 0.0952 0.0655 0.0838 0.1414 0.1265 0.0889 0.0361 0.0587 0.019 0.0022 0.0015 0.0982 0.0567 0.0623 0.0056 0.0643 0.1116 0.0881 0.1474 0.0302 0.124 0.1279 0.1234 0.1619 0.1725 0.1725 0.0092 0.0094 0.0313 0.0579 0.0865 0.0266 0.0146 0.0531 0.0336 0.0014 0.0939 0.0951 0.0841 0.0441 Relational measurements 0.0436 0.0206 0.0654 0.0259 0.0326 0.0495 0.0563 0.0812 0.2732 0.2396 0.4609 0.0041 0.3047 0.0045 0.0418 0.0234 0.0641 0.026 0.0348 0.0515 0.0558 0.042 0.0534 0.1825 0.3226 0.0141 X 0.0123 0.0473 0.0256 0.0658 0.0313 0.0394 0.0502 0.0549 0.2464 0.0811 0.3041 0.5133 0.0124 0.2657 0.0012 0.0424 0.0192 0.0634 0.0185 0.0315 0.05 0.0519 0.2934 0.173 0.4261 0.2841 0.0209 0.2998 0.0017 0.0445 0.0205 0.0605 0.0271 0.0412 0.0501 0.0517 0.3802 0.2245 0.3668 0.4248 0.0067 0.307 0.0085 0.0439 0.0193 0.069 0.0226 0.0478 0.0516 0.0554 0.0064 0.0342 0.5343 0.1871 0.0542 X 0.0218 0.0722 0.0256 0.0643 0.0234 0.0423 X X 0.0846 0.0336 0.2164 0.2487 0.0239 X 0.0021 Exp No 0.0942 0.0245 0.1599 0.0603 0.162 0.1265 0.16 0.1721 0.1272 0.1257 0.1514 0.1652 0.1722 0.1158 0.1222 0.0119 0.2224 0.1995 0.0246 0.0533 Exp No 0.1493 0.0256 0.1218 0.0602 0.1486 0.1626 0.1691 0.1578 0.1398 0.1292 0.1486 0.1432 0.1391 0.0493 0.0541 0.0889 0.0662 0.0592 0.0374 0.0683 0.0469 X 0.0235 X 0.0665 X 0.0234 X 0.0358 0.0311 0.0498 0.0504 0.0519 X 0.0533 X 0.112 X 0.4475 X 0.2016 X 0.0625 X X X 0.0059 0.0042 X- Measurements that were not taken 155 Appendix Table A1.4. Accuracy details of a fabricated GBP before the implementation of the proposed approach Accuracy details STL file dimensions (mm) Actual measured dimensions (mm) X-axis Error (deviation) 170 161.425 Y-axis 163.34 X-axis 0.0504 Y-axis 0.0392 60 57.076 58.220 0.0487 0.0455 25 24.205 24.306 0.0318 0.0277 15 15.210 15.407 0.0140 0.0271 Surface roughness, Ra: 23.3237 µm Table A1.5. Accuracy details of a fabricated GBP after the implementation of the proposed approach Accuracy details STL file dimensions (mm) Actual measured dimensions Error (deviation) (mm) 170 X-axis 170.1020 Y-axis 170.1620 X-axis 0.0006 Y-axis 0.0095 60 60.1840 60.2250 0.0030 0.0036 25 25.2620 25.2820 0.0104 0.0112 15 15.1020 15.1465 0.0068 0.0097 Note: Desired accuracy could be obtained from post-processing Surface roughness, Ra: 10.1264 µm 156 Appendix APPENDIX SLA-Warpage measurement 1.5 1.5-2 1-1.5 0.5 S4 0.5-1 0-0.5 S1 Fig A2.1. SLA – Warpage measurement LOM -Warpage measurement 4-5 3-4 2-3 1-2 S5 0-1 S1 Fig A2.2. LOM – Warpage measurement FDM-Warpage measurement 2.5 2-2.5 1.5 1.5-2 1-1.5 0.5 S4 0.5-1 0-0.5 S1 Fig A2.3. FDM – Warpage measurement 157 Appendix 1st SLS part- Warpage measurement 6-8 4-6 S5 S1 2-4 0-2 Fig A2.4. 1st SLS part- Warpage measurement 2st SLS part -Warpage Measurement 4-5 3-4 2-3 S5 S1 12 S3 1-2 0-1 Fig A2.5. 2nd SLS part – Warpage measurement Table A2.1. Process planning in rapid prototyping X- Input Variables Process Y-Output Variables Conceptual design The designer Design representation Mode of file transfer Purpose of the prototype Purpose of the prototype Size, accuracy, surface finish, etc. System setting Operator, RP system settings Operator, System, etc. Material and RP process based Quality check Product Design Design Software Data exchange format Data export Choice of an RP process Material based on the Process Compatibility Ease of prototyping Quality of the file Qualitative representation Integrity of file information Appropriate RP methods Appropriate RP methods Prototype quality Optimized parameters Process of Fabrication (Benchmarked Procedure) Safety procedures Post processing Prototype quality Prototype quality General quality of work Prototype quality Measurement check Verification 158 Appendix Table A2.2. Characteristics of the material used in the experiment Type Nylon plastic polymer Size of the powder particles Recommended preheating temperature Recommended layer thickness 100µm 60°C 0.2mm Table A2.3. Relative rating of the base plates used Base plates Steel Resistance to temperature Bonding of base layers to the plate Relative rating Very good Very poor Aluminium Polymer Good Poor Poor Good a. steel b. aluminium c. polymer d. wood Wood Good Very good Fig A2.6. Choice of base plates for the fabrication on the DLS system 159 Appendix Table A2.4. Undesirable end-results and errors in the DLS process Undesirable results Influence during fabrication process Warpage Serious effect-temperature dependant Delamination Serious effect- temperature, layer thickness, laser power dependant Surface Roughness Serious effect-controlled by optimized parameter setting Shrinkage Serious effect- material dependant Errors Laser beam error Laser compensations if needed System set up error Optimized setting of the system in general Post processing error Based on the post processing methods Fig A2.7. CMM measurements Table A2.5. Analysis of the feature geometry Individual geometric features Analysis Main Effects Plots- Data means for dimensional error Preferred settings of control factors based on the analysis Sphere PBT: 35 C LP: 20 W LT: 0.2 mm SS: 1200 mm/s 160 Appendix Circle PBT: 35 C LP: 20 W LT: 0.2 mm SS: 1400 mm/s Cone PBT: 35 C LP: 20 W LT: 0.1 mm SS: 1400nmm/s Cylinders PBT: 35 C LP: 20 W LT: 0.15 mm SS: 1400 mm/s Square boss PBT: 35C LP: 25 W LT: 0.15 mm SS: 1200 mm/s 161 Appendix Wedge PBT: 40 C LP: 20 W LT: 0.2 mm SS: 1600mm/s 162 Appendix APPENDIX Table A3.1. Material table MaterialID MaterialName MaterialType MachineTypeID Descriptions Price VendorID PhysicalID StockStatus PostcureMtd CriticalExpo DepthPenetration Visocsity Density TensileStr TensileMod Elongation ImpactStr YoungModulus Hardness GlassTransTemp SpecificGravity ParticleSize Color SpecificHeat ThermalCond MeltingTemp Shrinkage HeatTransCoeff UploadID Updated_Date Updated_Time A number for every material Name of Material Type of Material (epoxy, resin) SLS SLA FDM, etc. Character of material Price of material per kg Link to the vendor info Physical properties of the material (solid, etc.) Material stock status Postcure method Critical Exposure Depth of Penetration Viscosity centipoises at 30 deg Density at 25 deg Tensile strength (ASTM D637) Tensile Modulus (ASTM D637) Elongation (ASTM D637) Impact Strength (notched izod) Young's modulus of the material Hardness (shore D-scale) Glass Transition Temperature Specific Gravity of the material Size of the material Color of the material Specific Heat of the material Thermal conduction of the material Melting temperature of the material Shrinkage of material Heat Transfer Coefficient of the material ID of the user uploaded the material Date when the material is updated Time when the material is updated Table A3.2. Machine table MachineID MachineName MachineTypeID MaxPower X_BuildingSize Y_BuildingSize Z_BuildingSize Z_Accuracy XY_Accuracy MiniWall MiniHole MaxSpeed A number for each machine Machine name Machine type (e.g. SLS, SLA, Inkjet) Maximum laser power Maximum building dimension in X direction Maximum building dimension in Y direction Maximum building dimension in Z direction Accuracy in Z direction Accuracy in X-Y direction Minimum wall dimension Minimum hole dimension Maximum beam speed 163 Appendix MachineDimension Weight DataFormat MinThickness MaxThickness ElecticalSupply MaterialID1 MaterialID2 MaterialID3 MaterialID4 ApplicationID1 ApplicationID2 ApplicationID3 ApplicationID4 VendorID Price Photo PhotoAddress StockStatus UploadID Update_Date Update_Time Machine dimension Machine weight CAD data format Minimum slice thickness (mm) Maximum slice thickness (mm) Electrical supply of the machine Material used for this machine Material used for this machine Material used for this machine Material used for this machine Application used for this machine Application used for this machine Application used for this machine Application used for this machine Vendor of the machine The price per unit Photograph of the machine Path address to the photo of the machine Machine stock status User ID who uploaded this machine Date where the machine is uploaded Time where the machine is uploaded Table A3.3. Application table ApplicationID ApplicationName Description UploadID SamplePhoto1 SamplePhoto2 Updated_Date Updated_Time A number for each application Name of the application Description of the application User ID who uploaded the application Photo of application sample1 Photo of application sample2 Date where application is uploaded Time where application is uploaded Table A3.4. User’s table in the knowledge database UserID FirstName LastName Password LoginID Company Address City StateProv PostalCode County Email WebLink ContactNo FaxNo Position A number for every user First Name of the user Last Name of the user Password for the user to log in Log in name Company of the user Address of the user City the user from State or province the user from Postal code of the user Country the user from Email of the user Personal homepage of the user User contact number User fax number Admin or Member privileges 164 Appendix Registered_Date Registered_Time Updated_Date Updated_Time ClientIP Date user joined Time user joined Date where user make any amendment Time where user make any amendment IP address of user Table A3.5. Geometric features GeoId Accurate Medium LeastAccurate Identification of geometric features Corresponding Membership function (Integer) Corresponding Membership function (Integer) Corresponding Membership function (Integer) Table A3.6. Mechanical properties ProcessID Fillet Blend Chamfer Others Identification of RP&M process Corresponding Membership function (Integer Corresponding Membership function (Integer Corresponding Membership function (Integer Corresponding Membership function (Integer Table A3.7. Mechanical features MechId Very Good Good Moderate Identification of mechanical properties Corresponding Membership function (Integer) Corresponding Membership function (Integer) Corresponding Membership function (Integer) Table A3.8. Fine features ProcessID GeoId CaseA CaseB CaseC Identification of RP&M process Identification of geometric features Corresponding Membership function (Integer) Corresponding Membership function (Integer) Corresponding Membership function (Integer) Table A3.9. Process benchmarks BenchmarkID ProcessBenchmarkName MachineName BenchmarkingProcedure Identification of process benchmarks Corresponding benchmark name Machine based on the process Corresponding benchmark procedure 165 [...]... - R.C.Camp, 1989 Rapid Prototyping and Manufacturing (RP&M) is a relatively new manufacturing technology where 3D prototypes are directly built from their CAD models RP&M benchmarking is important for evaluating the strengths and weaknesses of RP&M systems With the aid of benchmarking, the capability of a specific system can be tested, measured, analysed, and verified through a standardized procedure... besides the process and the material, there may be other factors, such as the building style and specific process parameters that may affect the accuracy and finish of the part In RP&M benchmarking, it is necessary not only to standardize the design of the benchmark part, but also the fabrication and measurement/test processes This research examines issues on RP&M benchmarking and attempts to identify... fabrication, measurements and analysis of benchmark parts The aim is to develop benchmark parts and benchmarking procedures for performance evaluation of RP&M processes/systems and materials in terms of achievable geometric features and specific functional requirements The primary objective of the RP&M benchmarking design and study is to contribute to the development of the planning and decision support... evaluating different RP&M processes and systems A comparative study is additionally presented on the existing RP&M benchmark parts Chapter 3 discusses the benchmarking of RP&M processes Geometric and mechanical benchmark parts are proposed and discussed, followed by process benchmarking and its usefulness In addition this chapter discusses the importance and relevance of standardized or benchmarked measurement... surveyor (Webster’s New World Dictionary) The essence of benchmarking is the process of identifying the highest standards of excellence for products, services and processes, and then making the improvements necessary to reach those standards It involves systematic measure of a process against a well established or performing process, and then adopting and adapting benchmarked functions or procedures that... Review fabrication of the geometric and mechanical benchmark parts This will require a process benchmarking involving testing, measurement and analytical procedures The next chapter presents proposals towards generalised benchmarking consisting of a geometric benchmark part, mechanical benchmark part and standardized procedure for the fabrication, testing/measurement and evaluation of RP&M processes/systems... process evaluation and optimization Chapter 6 discusses the case study on the Direct Laser Sintering (DLS) process parameter tuning based on the methodology of process benchmarking The process tuning and the problems encountered are also discussed in detail to demonstrate the effectiveness of the six-sigma way of benchmarking 5 Chapter 1 Introduction Chapter 7 is about the Rapid Prototyping decision... capitol, trained personnel and location of equipment before selecting the technology 2.2.7 Aubin (1994) Aubin (1994) presents the results of a worldwide assessment of commercial rapid prototyping technologies that was initiated by the Intelligent Manufacturing Systems (IMS) project The objectives of this assessment included characterization of the commercially available rapid prototyping technologies... provide insight into various pre-processing, building and post-processing issues Their investigation was considered a start point in developing standards Fig 2.11 Test part used by Jayaram et al., 1994 16 Chapter 2 2.2.13 Literature Review Xu Fen and Shi Dongping (1999) The research efforts of Xu (1999) and Shi (1999) on benchmarking aim to develop practical and more generic benchmark parts (Figure 2.12 &... in identifying best practices or processes in manufacturing Benchmarking has been gaining popularity in recent years Organizations that faithfully use benchmarking strategies are therefore able to achieve considerable cost and time saving, with quality improvement Camp (1989) has appropriately pointed out the working definition preferred for benchmarking Benchmarking is the search for industry best . definition preferred for benchmarking. Benchmarking is the search for industry best practices that lead to superior performance.” - R.C.Camp, 1989 Rapid Prototyping and Manufacturing (RP&M). v Summary Rapid prototyping and manufacturing (RP&M) prototypes are increasingly used in the development of new products, spanning conceptual design, functional prototypes, and tooling essence of benchmarking is the process of identifying the highest standards of excellence for products, services and processes, and then making the improvements necessary to reach those standards.