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Frontiers of Mechanical Engineering

ISSN 2095-0233

ISSN 2095-0241(Online)

CN 11-5984/TH

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Front. Mech. Eng.    2014, Vol. 9 Issue (1) : 1-14    https://doi.org/10.1007/s11465-014-0296-8
RESEARCH ARTICLE
Robust design of configurations and parameters of adaptable products
Jian ZHANG1,2,Yongliang CHEN3,Deyi XUE1,Peihua GU2,*()
1. Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary T2N1N4, Canada
2. Department of Mechatronics Engineering, Shantou University, Shantou 515063, China
3. Department of Mechanical Engineering, Tianjin University, Tianjin 300072, China
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Abstract

An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.
Keywords adaptable product      robust design      optimization      uncertainties     
Corresponding Author(s): Peihua GU   
Issue Date: 16 May 2014
 Cite this article:   
Jian ZHANG,Yongliang CHEN,Deyi XUE, et al. Robust design of configurations and parameters of adaptable products[J]. Front. Mech. Eng., 2014, 9(1): 1-14.
 URL:  
https://academic.hep.com.cn/fme/EN/10.1007/s11465-014-0296-8
https://academic.hep.com.cn/fme/EN/Y2014/V9/I1/1
Fig.1  Relations among design requirements, design configuration candidates, and operation configuration states
Fig.2  Hybrid AND-OR tree for modeling design configuration candidates and operation configuration states
Fig.3  Design configuration candidate (a) and operation configuration state (b) generated from the hybrid AND-OR tree
Fig.4  Classification of parameters in adaptable design
Fig.5  Adaptation of parameters in the product operation stage
Fig.6  Two types of vibratory feeders. (a) Liner vibratory feeder; (b) bowl vibratory feeder
Fig.7  Two types of rectangular containers. (a) Container without tracks; (b) container with tracks
Fig.8  Three types of bowl containers. (a) Cylindrical container with internal tracks; (b) frustum cone container with internal tracks; (c) frustum cone container with external tracks
Fig.9  Springs in parallel. (a) Type A1; (b) type A2
Fig.10  Springs not in parallel. (a) Type B1; (b) type B2; (c) type B3; (d) type B4
Fig.11  Modeling of different configurations of the adaptable vibratory feeder
Fig.12  Feasible design configuration candidate of the adaptable vibratory feeder
Fig.13  Operation configuration state of the adaptable vibratory feeder
NameSymbolBoundsUnit
Vibration amplitude of the containerA[0.1×10-3, 2 ×10-3]m
Tab.1  Functional performance
NameSymbolBoundsUnit
Maximum force of the drive deviceFa[40, 800]N
Tab.2  Adaptable design parameter
NameSymbolBoundsUnit
Spring constant of each plate springKp[0.15 ×105, 3.5 ×105]N/m
Mass of materials stored in the containerMm[0.3, 1.5]kg
Angle between the plate spring and the baseα[0.7, 1.4]rad
Tab.3  Un-adaptable design parameters
NameSymbolValueUnit
Frequency of the drive devicew314.16rad/s
Density of aluminumρa2.70 ×103kg/m3
Density of cast ironρc7.80 ×103kg/m3
Spring constant of each rubber springK10.5 ×104N/m
Spring constant of each spring with round sectionK21.2 ×104N/m
Spring constant of each spring with rectangular sectionK33.5 ×104N/m
Spring constant of each conical springK40.8 ×104N/m
Damping coefficient of the functional unitCf250(N∙s)/m
Damping coefficient of the base unitCb400(N∙s)/m
Mass volume of the rectangular container without tracksVCN0.85 × 10-3m3
Mass volume of the rectangular container with tracksVCT0.95 × 10-3m3
Mass volume of the cylindrical container with internal tracksVCC1.2 × 10-3m3
Mass volume of the frustum cone container with internal tracksVCF0.9× 10-3m3
Mass volume of the frustum cone container with external tracksVCO0.95 × 10-3m3
Mass volume of the cylindrical baseVB10.8 × 10-3m3
Mass volume of the block baseVB21.0 × 10-3m3
Mass volume of the truncated cone baseVB31.2 × 10-3m3
Mass of the drive deviceMe1.5kg
Number of plate springs in the type A1 configurationNA14–
Number of plate springs in the type A2 configurationNA26–
Number of plate springs in the type B1 configurationNB13–
Number of plate springs in the type B2 configurationNB24–
Number of plate springs in the type B3 configurationNB35–
Number of plate springs in the type B4 configurationNB46–
Number of isolators in the 3-poins layoutNT3–
Number of isolators in the 4-points layoutNR4–
Tab.4  Unchangeable non-design parameters
NameSymbolStandard deviationUnit
Variation of mass in the containerΔMm0.5kg
Variation of the damping factor of the functional unitΔCf60(N∙s)/m
Variation of the maximum force of the drive deviceΔFa25N
Variation of the damping factor of the base unitΔCb50(N∙s)/m
Tab.5  Parameter variations
Fig.14  Equivalent model of vibratory feeder. (a) Model of vibratory feeder without isolator; (b) model of vibratory feeder with isolators
Fig.15  Results of configuration optimization based on generic programming
Fig.16  Optimal configurations of the adaptable vibratory feeder. (a) Configuration of liner vibratory feeder; (b) configuration of bowl vibratory feeder
Optimal parameter valuesRobustness of vibratory feeder with linear functional unitRobustness of vibratory feeder with spiral functional unitOverall robustness
Kp= 9.9×104 N/mS(170,1) = 40.85 (-)S(170,2) = 43.45 (-)S(170) = 42.41 (-)
Mm = 0.3 kg
α = 1.32 rad
Tab.6  Optimal parameter values and robustness measures for the robust adaptable design
1 GuP, HasheminaM, NeeA Y C. Adaptable design. CIRP Annals – Manufacturing Technology, 2004, 53(2): 539–557
2 KorenY, HuS J, GuP, ShpitalniM.Open-architecture products. CIRP Annals – Manufacturing Technology, 2013, 62(2): 719–729
3 GuP, XueD, NeeA Y C. Adaptable design: concepts, methods and applications. Proceedings of the Institution of Mechanical Engineers. Part B, Journal of Engineering Manufacture, 2009, 223(11): 1367–1387
doi: 10.1243/09544054JEM1387
4 LiY, XueD, GuP. Design for product adaptability. Concurrent Engineering: Research and Applications, 2008, 16(3): 221–232
5 FletcherD, BrennanR W, GuP. A method for quantifying adaptability in engineering design. Concurrent Engineering: Research and Applications, 2009, 17(4): 279–289
6 ChengQ, ZhangG, LiuZ, GuP, CaiL. A structure-based approach to evaluation product adaptability in adaptable design. Journal of Mechanical Science and Technology, 2011, 25(5): 1081–1094
doi: 10.1007/s12206-011-0224-3
7 XueD, HuaG, MehradV, GuP. Optimal adaptable design for creating the changeable product based on changeable requirements considering the whole product life-cycle. Journal of Manufacturing Systems, 2012, 31(1): 59–68
doi: 10.1016/j.jmsy.2011.04.003
8 ZhangJ, GuP, BaoN, ZhangG. Analytical robust design of mechanical systems. In: Proceedings of the ASME 2008 international design engineering technical conferences & computers and information in engineering conference. New York, 2008
9 TaguchiG. Performance analysis design. International Journal of Production Research, 1978, 16(6): 521–530
doi: 10.1080/00207547808930043
10 TaguchiG. Taguchi on Robust Technology Development: Bringing Quality Engineering Upstream. New York: ASME Press, 1993
11 ParkinsonA, SorensenC, PourhassanN. A general approach for robust optimal design. Journal of Mechanical Design, Transactions of the ASME, 1993, 115(1): 74–80
12 ZhangJ, BaoN, ZhangG, GuP. Analytical approach to robust design of nonlinear mechanical system. Frontiers of Mechanical Engineering, 2009, 4(2): 203–214
doi: 10.1007/s11465-009-0022-0
13 DuX, ChenW. Towards a better understanding of modeling feasibility robustness in engineering design. Journal of Mechanical Design, Transactions of the ASME, 2000, 122(4): 385–394
14 FonsecaJ R, FriswellM I, LeesA W. Efficient robust design via Monte Carlo sample reweighting. International Journal for Numerical Methods in Engineering, 2007, 69(11): 2279–2301
doi: 10.1002/nme.1850
15 KumarA, NairP, KeaneA, ShahparS. Robust design using Bayesian Monte Carlo. International Journal for Numerical Methods in Engineering, 2008, 73(11): 1497–1517
doi: 10.1002/nme.2126
16 SamadianiE, JoshiY, AllenJ K, MistreeF. Adaptable robust design of multi-scale convective systems applied to energy efficient data centers. Numerical Heat Transfer, Part A, Application. An International Journal of Computation and Methodology, 2009, 57(2): 69–100
17 ZhangJ, LiS, BaoN, ZhangG, XueD, GuP.A robust design approach to determination of tolerance of mechanical products. CIRP Annals – Manufacturing Technology, 2010, 59(1): 195–198
18 HuW, AzarmS, AlmansooriA. New approximation assisted multi-objective collaborative robust optimization (new AA-McRO) under interval uncertainty. Structural and Multidisciplinary Optimization, 2013, 47(1): 19–35
doi: 10.1007/s00158-012-0816-2
19 ZhangJ, XueD, GuP. Robust adaptable design considering changes of parameter values in product operation stage. In: Proceedings of the 22nd CIRP design conference. Bangalore, 2012
20 HongG, HuL, XueD, TuY L, XiongY L. Identification of the optimal product configuration and parameters based on individual customer requirements on performance and costs in one-of-a-kind production. International Journal of Production Research, 2008, 46(12): 3297–3326
doi: 10.1080/00207540601099274
21 ParameswaranM A, GanapathyS. Vibratory conveying – analysis and design: a review. Mechanism and Machine Theory, 1979, 14(2): 89–97
doi: 10.1016/0094-114X(79)90024-7
22 LiY, ChenY. Technology improvement on electromagnetic vibration bowel feeder. Modern Manufacturing Engineering, 2005, 5: 109–111
23 LuoY. Study on characteristic and control of electromagnetic vibration feeder. Packaging Engineering, 2005, 26(4): 54–56
24 RaoS S. Mechanical Vibrations. New Jersey: Prentice Hall, 2011
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