Skip to main content
SpringerLink
Log in

Experimental investigation of tool vibration and surface roughness in the precision end-milling process using the singular spectrum analysis

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The vibrations on the cutting tool have a momentous influence for the surface quality of workpiece with respect to surface profile and roughness during the precision end-milling process. Singular spectrum analysis (SSA) is a new non-parametric technique of time series analysis and forecasting. The significant features of the cutting tool vibration signals from the sensors are extracted and transformed from the SSA-processed vibration signals. In the present study, SSA is applied to extract and transform the raw signals of the vibrations on the cutting tool for investigating the relationship between tool vibration and surface roughness in the precision end-milling process of hardened steel SCM440. In this experimental investigation, the spindle speed, feed rate, and cutting depth were chosen as the numerical factor; the cutting feed direction and holder type were regarded as the categorical factor. An experimental plan consisting of five-factor (three numerical plus two categorical) d-optimal design based on the response surface methodology was employed to carry out the experimental study. A micro-cutting test was conducted to visualize the effect of vibration of tooltip on the performance of surface roughness. With the experimental values up to 95% confidence interval, it is fairly well for the experimental results to present the mathematical models of the tool vibration and surface roughness. Results show that the effects of feed rate and cutting depth provide the reinforcement on the overall vibration to cause the unstable cutting process and exhibit the result of the worst machined surface. The amplitude of vibration signals along the cutting feed direction is generally larger than that along other direction. The spindle speed and tool holder type affect the stability of cutting tooltip during the cutting process.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Chae J, Park SS, Freiheit T (2006) Investigation of micro-cutting operations. Int J Mach Tools Manuf 46:313–332

    Article  Google Scholar 

  2. Tounsi N, Otho A (2000) Identification of machine-tool–workpiece system dynamics. Int J Mach Tools Manuf 40:1367–1384

    Article  Google Scholar 

  3. Cowley A (1970) Structural analysis. Machine tool structures. Pergamon, Oxford

    Google Scholar 

  4. Marinescu I, Ispas C, Boboc D (2002) Handbook of machine tool analysis. Marcel Dekker, New York

    Google Scholar 

  5. Dimla DE Sr (2004) The impact of cutting conditions on cutting forces and vibration signals in turning with plane face geometry inserts. J Mater Process Technol 155–156:1708–1715

    Article  Google Scholar 

  6. Thomas M, Beauchamp Y, Youssef AY, Masounave J (1996) Effect of tool vibration on surface roughness during lathe dry turning process. Comput Ind Eng 31(3–4):637–644

    Article  Google Scholar 

  7. Mer A, Diniz AE (1994) Correlating tool wear, tool life, surface roughness and tool vibration in finish turning with coated carbide tools. Wear 173:137–144

    Article  Google Scholar 

  8. Jang DY, Choi YG, Kim HG, Hsiao A (1996) Study of the correlation between surface roughness and cutting vibration to develop an online roughness measuring technique in hard turning. Int J Mach Tools Manuf 36(4):453–464

    Article  Google Scholar 

  9. Abouelatta OB, Madl J (2001) Surface roughness prediction based on cutting parameters and tool vibrations in turning operations. J Mater Process Technol 118:269–277

    Article  Google Scholar 

  10. Dimla DE (2002) The correlation of vibration signal features to cutting tool wear in a metal turning operation. Int J Adv Manuf Technol 19:705–713

    Article  Google Scholar 

  11. Risbood KA, Dixit US, Sahasrabudhe AD (2003) Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning. J Mater Process Technol 132(1–3):203–214

    Article  Google Scholar 

  12. Li HZ, Zeng H, Chen XQ (2006) An experimental study of tool wear and cutting force variation in the end milling of Inconel 718 with coated carbide inserts. J Mater Process Technol 180:296–304

    Article  Google Scholar 

  13. Golyandina N, Nekrutkin V, Zhigljavsky A (2001) Analysis of time series structure—SSA and related techniques. Chapman &Hall/CRC, Boca Raton, pp 13–17

    Book  MATH  Google Scholar 

  14. Salgado DR, Alonso FJ (2006) Tool wear detection in turning operations using singular spectrum analysis. J Mater Process Technol 171:451–458

    Article  Google Scholar 

  15. Kilundu B, Dehombreux P, Chiementin X (2011) Tool wear monitoring by machine learning techniques and singular spectrum analysis. Mech Syst Signal Process 25:400–415

    Article  Google Scholar 

  16. Myers RH, Montgomery DC (1995) Response surface methodology: process and product optimization using designed experiments. John Wiley and Sons, New York

    MATH  Google Scholar 

  17. Khuri AI, Cornell JA (1996) Response surfaces, designs and analyses. Marcel Dekker, New York

    MATH  Google Scholar 

  18. Puri AB, Bhattacharyya B (2005) Modeling and analysis of white layer depth in a wire-cut EDM process through response surface methodology. Int J Adv Manuf Technol 25:301–307

    Article  Google Scholar 

  19. Lin BT, Jean MD, Chou JH (2007) Using response surface methodology with response transformation in optimizing plasma spraying coatings. Int J Adv Manuf Technol 34:307–315

    Article  Google Scholar 

  20. Davim JP, Gaitonde VN, Karnik SR (2008) An investigative study of delamination in drilling of medium density fibreboard (MDF) using response surface models. Int J Adv Manuf Technol 37:49–57

    Article  Google Scholar 

  21. Palanikumar K (2008) Application of Taguchi and response surface methodologies for surface roughness in machining glass fiber reinforced plastics by PCD tooling. Int J Adv Manuf Technol 36:19–27

    Article  Google Scholar 

  22. Çaydaş U, Hasçalik A (2008) Modeling and analysis of electrode wear and white layer thickness in die-sinking EDM process through response surface methodology. Int J Adv Manuf Technol 38:1148–1156

    Article  Google Scholar 

  23. Munda J, Bhattacharyya B (2008) Investigation into electrochemical micromachining (EMM) through response surface methodology based approach. Int J Adv Manuf Technol 35:821–832

    Article  Google Scholar 

  24. Box GEP, Lucas HL (1959) Design of experiments in non-linear situations. Biometrika 46(1/2):77–90

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical and Automatic Engineering, Chungchou University of Science and Technology, No.6, Lane 2, Sec. 3, Shanjiao Rd., Yuanlin Town, Changhua, Taiwan, 51001, Republic of China

    Chih-Cherng Chen

  2. Department of Mechanical Engineering, Hsiuping University of Science and Technology, No. 11, Gungye Rd., Dali District, Taichung, Taiwan, 41280, Republic of China

    Nun-Ming Liu, Ko-Ta Chiang & Hua-Lun Chen

Authors
  1. Chih-Cherng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nun-Ming Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ko-Ta Chiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hua-Lun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ko-Ta Chiang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, CC., Liu, NM., Chiang, KT. et al. Experimental investigation of tool vibration and surface roughness in the precision end-milling process using the singular spectrum analysis. Int J Adv Manuf Technol 63, 797–815 (2012). https://doi.org/10.1007/s00170-012-3943-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-012-3943-4

Keywords

Search

Navigation