Novel method for shape complexity evaluation: a threshold from machining to additive manufacturing in the early design phase
Research in Engineering Design - Trang 1-24 - 2024
Tóm tắt
Increasing product diversity, rising performance and reliability demands, and industry competitiveness are some of the many reasons that increase the need of more complex product designs in almost all sectors. The complexity of parts increases with their geometrical features to be designed and manufactured. Researchers agreed that it can be qualitatively evaluated and expressed with terms like low, medium, high, and very high. However, it might be evaluated differently, depending on the designer’s considerations, domain and experience. Quantitative evaluation of a design complexity is, therefore, indispensable and expedites the decision-making about the selection of the manufacturing process. However, having a well-defined and unambiguous metric for quantitative evaluation is challenging. Most of existing metrics are not objective and are only valid for their specific applications. This paper presents a novel, unambiguous, and generalized approach for shape complexity evaluation. The developed metric enables determining if the selected part should be produced by conventional methods such as machining, or by non-conventional methods such as additive manufacturing. In order to ensure its objectivity, only geometrical features have been considered. The metric was tested through 25 different part designs of varying complexity. The investigations showed an accordance between the qualitatively evaluated shape and the calculated complexity factor. Also, the comparison of the results with other metrics showed the weakness of the latter and the efficiency and reliability of our metric. The results have been also validated by 50 experts from 23 countries. Based on these results, a threshold between machining and additive manufacturing is fixed allowing an easier decision-making.
Tài liệu tham khảo
Abdelall ES, Alawneh L, Eldakroury M (2020) A manufacturability-based assessment and design modification support tool. J Appl Res Technol 18:410–424
Abdulhameed O, Al-Ahmari A, Ameen W, Mian SH (2019) Additive manufacturing challenges, trends, and applications. Adv Mech Eng 11(2):1–27. https://doi.org/10.1177/1687814018822880
Aidibe A, Tahan A, Brailovski V (2016) Metrological investigation of a selective laser melting additive manufacturing system: a case study. IFAC-PapersOnLine 49:25–29. https://doi.org/10.1016/j.ifacol.2016.12.156
Alkan B, Vera D, Ahmad M, Ahmad B, Harrison R (2016) Design evaluation of automated manufacturing processes based on complexity of control logic. Procedia CIRP 50:141–146. https://doi.org/10.1016/j.procir.2016.05.031
Almaghariz ES, Conner BP, Lenner L, Gullapalli R, Manogharan GP, Lamoncha B, Fang M (2016) Quantifying the role of part design complexity in using 3D sand printing for molds and cores. Int J Met 10:240–252. https://doi.org/10.1007/s40962-016-0027-5
Ameri F, Summers JD, Mocko GM, Porter M (2008) Engineering design complexity: an investigation of methods and measures. Res Eng Des 19:161–179. https://doi.org/10.1007/s00163-008-0053-2
Arslan MF, Tari S (2020) Complexity of shapes embedded in Z with a bias towards squares. IEEE Trans Image Process 29:8870–8879. https://doi.org/10.1109/TIP.2020.3021316
Arslan MF, Haridis A, Rosin PL, Tari S, Brassey Ch, Gardiner JD, Genctav A, Genctav M (2022) SHREC’21: quantifying shape complexity. Comput Graph 102:144–153
Ben Amor S, Tahan A, Louhichi B (2019) Proposition of a geometric complexity model for additive manufacturing process based on CAD. In: 23 international conference information visualisation, pp 442–448. https://doi.org/10.1109/iv.2019.00080
Bhuvanesh Kumar M, Sathiya P (2021) Methods and materials for additive manufacturing: a critical review on advancements and challenges. Thin Walled Struct 159:107228. https://doi.org/10.1016/j.tws.2020.107228
Brinkhoff T, Kriegel H-P, Schneider R, Braun A (1995) Measuring the complexity of polygonal objects. Simulation framework for continuous phenomena view project. Citeseer, June 2014. https://www.researchgate.net/publication/221589831
Budde L, Nagler O, Friedli T (2015) A method to set up a complexity index to improve decision-making performance. Procedia CIRP 36:53–58. https://doi.org/10.1016/j.procir.2015.01.052
Camarero JJ, Sisó S, Gil-Pelegrín E (2002) Fractal dimension does not adequately describe the complexity of leaf margin in seedlings of Quercus species. Anales Del Jardín Botánico De Madrid. https://doi.org/10.3989/ajbm.2002.v60.i1.82
da Silva LRR, Sales WF, Campos FDAR, de Sousa JAG, Davis R, Singh A, Teixeira Coelho R, Borgohain B (2021) A comprehensive review on additive manufacturing of medical devices. Prog Addit Manuf 6:517–553. https://doi.org/10.1007/s40964-021-00188-0
DebRoy T, Wei HL, Zuback JS, Mukherjee T, Elmer JW, Milewski JO, Beese AM, Wilson-Heid A, Zhange ADW (2018) Additive manufacturing of metallic components—process, structure and properties. Prog Mater Sci 92:112–224. https://doi.org/10.1016/j.pmatsci.2017.10.001
Du D-Z, Ko K-I (2000) Theory of computational complexity, 2nd edn. Wiley, Hoboken
Dumitrescu R, Szecsi T (2002) Implementing design for manufacture rules. Technical paper—Society of Manufacturing Engineers, MS02–124
Elmaraghy W, Elmaraghy H, Tomiyama T, Monostori L (2012) Complexity in engineering design and manufacturing. CIRP Ann Manuf Technol 61:793–814. https://doi.org/10.1016/j.cirp.2012.05.001
Gardiner JD, Behnsen J, Brassey CA (2018) Alpha shapes: determining 3D shape complexity across morphologically diverse structures. BMC Evol Biol 18(1):1–16. https://doi.org/10.1186/s12862-018-1305-z
Genctav A, Tari S (2019) Discrepancy: local/global shape characterization with a roundness bias. J Math Imaging vis 61(1):160–171. https://doi.org/10.1007/s10851-018-0851-8
Genctav M, Genctav A, Tari S (2016) Nonlocal via local—nonlinear via linear: a new distance field via screened Poisson equation. J Math Imaging vis 55(2):242–252
Gupta SK, Nau DS, Zhang GM (1993) Interpreting product designs for manufacturability evaluation. Technical Research Report, University of Maryland Libraries
Hayward J, Orford JD, Whalley WB (1989) Three implementations of fractal analysis of article outlines. Comput Geosci 15(2):199–207
Jacobs MA (2013) Complexity: toward an empirical measure. Technovation 33:111–118. https://doi.org/10.1016/j.technovation.2013.01.001
Johnson MD, Valverde LM, Thomison WD (2017) An investigation and evaluation of computer-aided design model complexity metrics. Comput Aided Des Appl 15:61–75. https://doi.org/10.1080/16864360.2017.1353729
Joshi D, Ravi B (2010) Quantifying the shape complexity of cast parts. Comput Aided Des Appl 7:685–700. https://doi.org/10.3722/cadaps.2010.685-700
Kerbrat O, Mognol P, Hascoet JY (2010) Manufacturing complexity evaluation at the design stage for both machining and layered manufacturing. CIRP J Manuf Sci Technol 2(3):208–215
Leach RK, Bourell D, Carmignato S, Donmez A, Senin N, Dewulf W (2019) Geometrical metrology for metal additive manufacturing. CIRP Ann 68(2):677–700. https://doi.org/10.1016/j.cirp.2019.05.004
Lépine M Jr, Tahan AS (2016) The relationship between geometrical complexity and process capability. ASME J Manuf Sci Eng 138:051009-1–051009-13. https://doi.org/10.1115/1.4031900
Li Y (2008) Manufacturability analysis for non-feature-based objects. ProQuest Diss. Thesis, Iowa State University, no. 3316207, p 121
Matsumoto T, Sato K, Matsuoka Y, Kato T (2019) Quantification of “complexity” in curved surface shape using total absolute curvature. Comput Graph (pergamon) 78(xxxx):108–115. https://doi.org/10.1016/j.cag.2018.10.009
Mazur M, Brincat P, Leary M, Brandt M (2017) Numerical and experimental evaluation of a conformally cooled H13 steel injection mould manufactured with selective laser melting. Int J Adv Manuf Technol 93(1–4):881–900
Modrak V, Bednar S (2016) Entropy based versus combinatorial product configuration complexity in mass customized manufacturing. Procedia CIRP 41:183–188. https://doi.org/10.1016/j.procir.2015.12.100
Nagahanumaiah, Mukherjee NP, Ravi B (2005) An integrated framework for die and mold cost estimation using design features and tooling parameters. Int J Adv Manuf Technol 26:1138–1149. https://doi.org/10.1007/s00170-004-2084-9
Orfi N, Terpenny J, Sahin-Sariisik A (2011) Harnessing product complexity: step 1-establishing product complexity dimensions and indicators. Eng Econ 56:59–79. https://doi.org/10.1080/0013791X.2010.549935
Page DL, Koschan AF, Sukumar SR, Roui-Abidi B, Abidi MA (2003) Shape analysis algorithm based on information theory. In: IEEE international conference on image processing, vol 1, pp 229–232. https://doi.org/10.1109/icip.2003.1246940
Pellerin J, Caumon G, Julio C, Mejia-Herrera P, Botella A (2015) Elements for measuring the complexity of 3D structural models: connectivity and geometry. Comput Geosci 76:130–140. https://doi.org/10.1016/j.cageo.2015.01.002
Psarra S, Grajewski T (2001) Describing shape and shape complexity using local properties. In: Proceedings of 3rd international Sp. Syntax, pp 28.1–28.16
Qamar SZ, Arif AFM, Sheikh AK (2004) A new definition of shape complexity for metal extrusion. J Mater Process Technol 155–156:1734–1739. https://doi.org/10.1016/j.jmatprotec.2004.04.163
Razavykia A, Brusa E, Delprete C, Yavari R (2020) An overview of additive manufacturing technologies—a review to technical synthesis in numerical study of selective laser melting. Materials (basel) 13(17):1–22. https://doi.org/10.3390/ma13173895
Rodríguez-Toro CA, Tate SJ, Jared GEM, Swift KG (2003) Complexity metrics for design (simplicity + simplicity = complexity). Proc Inst Mech Eng Part B J Eng Manuf 217:721–726. https://doi.org/10.1243/095440503322011461
Rosin PL (2009) Classification of pathological shapes using convexity measures. Pattern Recogn Lett 30(5):570–578. https://doi.org/10.1016/j.patrec.2008.12.001
Saleem W, Belyaev A, Wang D, Seidel HP (2011) On visual complexity of 3D shapes. Comput Graph (pergamon) 35(3):580–585. https://doi.org/10.1016/j.cag.2011.03.006
Samy SN, Elmaraghy H (2010) A model for measuring products assembly complexity. Int J Comput Integr Manuf 23:1015–1027. https://doi.org/10.1080/0951192X.2010.511652
Spies K (1959) Die Zwischenformen beim Gesenkschmieden und ihre Herstellung durch Formwalzen [Intermediate shapes in die forging and their manufacture through roll forming], Forschungsberichte des Landes Nordrhein-Westfalen, Germany, 728, Verlag für Sozialwissenschaften
Summers JD, Shah JJ (2010) Mechanical engineering design complexity metrics: size, coupling, and solvability. J Mech Des Trans ASME 132:021004-1–021004-11. https://doi.org/10.1115/1.4000759
Teterin GP, Tarnovsky IJ, Chechik AA (1966) Criterion of complexity of the configuration of forgings. Kuznechno-Shtanmpovochnoe Proizvodstvo 7:6–8 (in Russian)
Tomov B, Radev R (2010) Shape complexity factor for closed die forging. Int J Mater Form 3:319–322. https://doi.org/10.1007/s12289-010-0771-7
Valentan B, Brajlih T, Drstvensek I, Balic J (2006) Evaluation of shape complexity based on STL data. J Achiev Mater Manuf Eng 17:293–296
Valentan B, Brajlih T, Drstvensek I (2008) Basic solutions on shape complexity evaluation of STL data. J Achiev Mater Manuf Eng 26:73–80
Valentan B, Brajlih T, Drstvensek I, Balic J (2011) Development of a part-complexity evaluation model for application in additive fabrication technologies. Strojniski Vestnik J Mech Eng 57:709–718. https://doi.org/10.5545/sv-jme.2010.057
Vasselle B, Giraudon G (1993) 2-D digital curve analysis: aA regularity measure. In: 1993 IEEE 4th international conference on computer vision, August, pp 556–561. https://doi.org/10.1109/iccv.1993.378162
Wang F, Vemuri BC, Rao M, Chen Y (2003) Cumulative residual entropy, a new measure of information & its application to image alignment. In: Proceedings of the IEEE international conference on computer vision, 1(Iccv):548–553. https://doi.org/10.1109/iccv.2003.1238395
Williamson J (2015) Illustrating the real-world benefits of additive manufacturing. The manufacturer, p 1
Zhang Z, Luo Q (2007) A grey measurement of product complexity. In: Conference proceedings—IEEE international conference on systems, man and cybernetics, pp 2176–2180. https://doi.org/10.1109/ICSMC.2007.4413624
Zhao G, Wright E, Grandhi RV (1995) Forging preform design with shape complexity control in simulating backward deformation. Int J Mach Tools Manuf 35:1225–1239. https://doi.org/10.1016/0890-6955(94)00117-3
Zunic J, Rosin PL (2004) A new convexity measure for polygons. IEEE Trans Pattern Anal Mach Intell 26(7):923–934. https://doi.org/10.1109/TPAMI.2004.19