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Error Allocation in the Design of Precision Machines

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Precision Machines

Part of the book series: Precision Manufacturing ((PRECISION))

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Abstract

Machining accuracy is an important index to evaluate the performance of a precision machine. However, the machining accuracy of parts is seriously limited by the designed machine’s errors. Therefore, error allocation in precision machine design is the key element to produce the components with a closed tolerance. In this chapter, the main errors for the designed machine that affect the machining accuracy are introduced, which include machine tool geometric error, machine tool thermal deformation, and load-induced errors. Among them, the geometric error after the assembly of the machine tool has the most direct impact on the machining accuracy, in which the position- and pose-related errors between each component transmit through kinematic chain and lead to the error combination. The essence of error allocation design is to use tolerance to limit the error of every part and finally ensure the overall output trajectory accuracy of the cutting tool. The deformation error caused by uneven temperature distribution is mainly caused by cutting process, friction behavior, and the surrounding environment, and it will further change the relative position of each part of the machine tool. Finally, load error under the action of force is introduced, which produces the elasticity or even structural deformation and further affects the relative position of the machine tool components. It shows that reasonable error allocation under the influence of multiple errors for the precision machine design is critical to ensure the machining precision.

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References

  • Altintas Y, Brecher C, Weck M, Witt S (2005) Virtual machine tool. CIRP Ann Manuf Technol 54(2):115–138

    Google Scholar 

  • Aurich JC, Biermann D, Blum H, Brecher C, Carstensen C, Denkena B, Klocke F, Kröger M, Steinmann P, Weinert K (2009) Modelling and simulation of process machine interaction in grinding. Prod Eng 3(1):111–120

    Google Scholar 

  • Biera J, Vinolas J, Nieto FJ (1997) Time-domain dynamic modelling of the external plunge grinding process. Int J Mach Tools Manuf 37(11):1555–1572

    Google Scholar 

  • Brinksmeier E, Mutlugünes Y, Klocke F, Aurich JC, Shore P, Ohmori H (2010) Ultra-precision grinding. CIRP Ann Manuf Technol 59:652–671

    Google Scholar 

  • Ding S, Huang XD, Yu CJ, Wang W (2016) Actual inverse kinematics for position-independent and position-dependent geometric error compensation of five-axis machine tools. Int J Mach Tools Manuf 111:55–62

    Google Scholar 

  • Guo E, Ren N, Liu Z, Zheng X (2019) Influence of sensitive pose errors on tooth deviation of cylindrical gear in power skiving. Adv Mech Eng 11(4):1–12

    Google Scholar 

  • Hamouda K, Bournine H, Tamarkin M, Babichev A, Saidi P, Amrou D (2016) Effect of the velocity of rotation in the process of vibration grinding on the surface state. Mater Sci 52(2):216–221

    Google Scholar 

  • Hwang TW, Evens CJ, Malkin S (1999) High speed grinding of silicon nitride with electroplated diamond wheels, part 1: wear and wheel life. ASME J Manuf Sci Eng 121(1):32–41

    Google Scholar 

  • Kim MS, Chung SC (2005) A systematic approach to design high-performance feed drive systems. Int J Mach Tools Manuf 45(12-13):1421–1435

    Google Scholar 

  • Kreith FD, Goswami Y (2015) The CRC handbook of mechanical engineering: factors in precision engineering. CRC Press, New York

    MATH  Google Scholar 

  • Lasemi A, Xue DY, Gu PH (2016) Accurate identification and compensation of geometric errors of 5-axis CNC machine tools using double ball bar. Meas Sci Technol 24:1–18

    Google Scholar 

  • Lee KI, Yang SH (2013) Measurement and verification of position-independent geometric errors of a five-axis machine tool using a double ball-bar. Int J Mach Tools Manuf 70:45–52

    Google Scholar 

  • Lee CH, Yang MY, Oh CW, Gim TW, Ha JY (2015) An integrated prediction model including the cutting process for virtual product development of machine tools. Int J Mach Tools Manuf 90:29–43

    Google Scholar 

  • Liao YS, Shiang LC (1991) Computer simulation of self-excited and forced vibrations in the external cylindrical plunge grinding process. J Eng Ind 113:297–304

    Google Scholar 

  • Mayr J, Jedrzejewski J, Uhlmann E, Donmez AM, Knapp W, Härtig F, Wendt K, Moriwaki T, Shore P, Schmitt R, Brecher C, Würz T, Wegener K (2012) Thermal issues in machine tools. CIRP Ann Manuf Technol 61(2):771–791

    Google Scholar 

  • Mekid S (2008) Introduction to precision machine design and error assessment. CRC Press, Boca Raton, London, New York

    Google Scholar 

  • Putz M, Regel J, Wenzel A, Bräunig M (2019) Thermal errors in milling: comparison of displacements of the machine tool, tool and workpiece. Procedia CIRP 82:389–394

    Google Scholar 

  • Raju AS, Vaidyanathan S, Venkatesh VC (1976) Comparative performance of coated sandwich and conventional carbide tools. In: Proceeding of international conference on hard material tool technology, Pittsburgh, pp 144–156

    Google Scholar 

  • Ramesh R, Mannan MA, Poo AN (2000) Error compensation in machine tools – a review part I: geometric, cutting-force induced and fixture dependent errors. Int J Mach Tools Manuf 40:1235–1256

    Google Scholar 

  • Schwenke H, Knapp W, Haitjema H, Weckenmann A, Schmitt R, Delbressine F (2008) Geometric error measurement and compensation of machines-an update. CIRP Ann Manuf Technol 57:660–675

    Google Scholar 

  • Sexton JS, Stone BJ (1981) The development of an ultra-hard abrasive grinding wheel which suppresses chatter. CIRP Ann Manuf Technol 30(1):215–218

    Google Scholar 

  • Shi XL, Liu HL, Li H, Liu C, Tan GY (2016) Comprehensive error measurement and compensation method for equivalent cutting forces. Int J Adv Manuf Technol 85(1–4):149–156

    Google Scholar 

  • Suto T, Sata T (1981) Simulation of grinding process based on wheel surface characteristics. Bull Jpn Soc Precision Eng 15(1):27–33

    Google Scholar 

  • Taniguchi N (1994) The state of the art of nanotechnology for processing of ultraprecision and ultra fine products. Journal of the American Society of Precision Engineering 16(1):5–24

    Google Scholar 

  • Tian WJ, Gao WG, Zhang DW, Huang T (2014) A general approach for error modelling of machine tools. Int J Mach Tools Manuf 79:17–23

    Google Scholar 

  • Turek P, Jędrzejewski J, Modrzycki W (2010) Methods of machine tool error compensation. J Mach Eng 10(4):5–26

    Google Scholar 

  • Yang JX, Mayer JRR, Altintas Y (2015) A position independent geometric errors identification and correction method for five–axis serial machines based on screw theory. Int J Mach Tools Manuf 95:52–66

    Google Scholar 

  • Zhang SJ, To S, Wang SJ, Zhu ZW (2015) A review of surface roughness generation in ultra-precision machining. Int J Mach Tools Manuf 91:76–95

    Google Scholar 

  • Zhao QL, Guo B (2015) Ultra-precision grinding of optical glasses using mono-layer nickel electroplated coarse-grained diamond wheels, part 2: investigation of profile and surface grinding. Precis Eng 39:67–78

    Google Scholar 

  • Zhao LP, Chen HR, Yao YY, Diao GZ (2016) A new approach to improving the machining precision based on dynamic sensitivity analysis. Int J Mach Tools Manuf 102:9–21

    Google Scholar 

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Authors and Affiliations

  1. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China

    Shan Shan Chen & Guo Feng Zhang

Authors
  1. Shan Shan Chen
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  2. Guo Feng Zhang
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Corresponding author

Correspondence to Shan Shan Chen .

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Editors and Affiliations

  1. SKL, Xi'an, Shanxi, China

    Shuming Yang

  2. School of Mechanical Engineering, Xi’an Jiao Tong University, Xi'an, China

    Zhuangde Jiang

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Chen, S.S., Zhang, G.F. (2020). Error Allocation in the Design of Precision Machines. In: Yang, S., Jiang, Z. (eds) Precision Machines. Precision Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-10-5192-0_26-1

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  • DOI: https://doi.org/10.1007/978-981-10-5192-0_26-1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5192-0

  • Online ISBN: 978-981-10-5192-0

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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