Process Capability and Average Roughness in Abrasive Water Jet Cutting Process of Stainless Steel

Authors

  • M. Boujelbene College of Engineering of Hail, University of Hail, Saudi Arabia

Abstract

Process capability analysis is frequently employed to evaluate if a product or a process can meet the customer’s requirement. In general, process capability analysis can be represented by using the process capability index. Until now, the process capability index was frequently used for manufacturing processes with quantitative characteristics. However, for a process with qualitative characteristic like cutting surface, the data’s type and single specification caused limitations of using the process capability index. Taguchi developed a surface quality by abrasive water jet cutting or quadratic quality loss function to address such issues. In this study, we intend to construct a measurable index which incorporates the process capability index philosophy concept to analyze the process capability with the consideration of the qualitative surface roughness. The manufacturers can employ the proposed index to self-assess the process capability. The objective of this study was to examine the effects of abrasive water jet machining variables like cutting speed of the stainless steel material. The roughness of the varied surface through the cut depth was also measured and determined as a process capability index of 3 zones machined surface.

Keywords:

abrasive water jet cutting, process capability, cutting speed, surface roughness, stainless steel

Downloads

Download data is not yet available.

References

A. Akkurt, “Cut front geometry characterization in cutting applications of brass with abrasive water jet”, Journal of Materials Engineering and Performance, Vol. 19, No. 4, pp. 599–606, 2010. DOI: https://doi.org/10.1007/s11665-009-9513-8

J. Valicek, S. Hloch, D. Kozak, “Surface geometric parameters proposal for the advanced control of abrasive waterjet technology”, The International Journal of Advanced Manufacturing Technology, Vol. 41, pp. 323–328, 2009 DOI: https://doi.org/10.1007/s00170-008-1489-2

A. Daymi, M. Boujelbene, E. Bayraktar, A. Ben Amara, D. Katundi, “Influence of feed rate on surface integrity of titanium alloy in high speed milling”, Advanced Materials Research, Vol. 264-265, pp. 1228-1233, 2011 DOI: https://doi.org/10.4028/www.scientific.net/AMR.264-265.1228

Y. Wu, S. Zhang, S. Wang, F. Yang, H. Tao, “Method of obtaining accurate jet lag informationin abrasive water-jet machining process”, The International Journal of Advanced Manufacturing Technology, Vol. 76, No. 9-12, pp. 1827–1835, 2015 DOI: https://doi.org/10.1007/s00170-014-6404-4

I. Miraoui, M. Boujelbene, E. Bayraktar, “Analysis of cut surface quality of sheet metals obtained by laser machining: thermal effects”, Advances in Materials and Processing Technologies, Vol. 1 No. 3-4, pp. 633-642, 2015 DOI: https://doi.org/10.1080/2374068X.2016.1147759

M. Boujelbene, A. S. Alghamdi, I. Miraoui, E. Bayraktar, M. Gazbar, “Effects of the laser cutting parameters on the micro-hardness and on the heat affected zone of the mi-hardened steel”, International Journal of Advanced and Applied Sciences Vol. 4, No. 5, pp. 19-25, 2017

A. Alberdi, A. Rivero, L. N. Lopez de Lacalle, I. Etxeberria, A. Suarez, “Effect of process parameter on the kerf geometry in abrasive water jet milling”, The International Journal of Advanced Manufacturing Technology, Vol. 51, No. 5-8, pp. 467– 480, 2010 DOI: https://doi.org/10.1007/s00170-010-2662-y

M. Boujelbene, P. Abellard, E. Bayraktar, S. Torbaty, “Study of the milling strategy on the tool life and the surface quality for knee prostheses “, Journal of Achievements in Materials and Manufacturing Engineering, Vol. 31, No. 2, 610-615, 2008

M. Boujelbene, S. Ezzdini, N. Elboughdiri, W. Ben Salem, W. Youssef, “Investigation on the surface roughness of the high steel material after wire electrical discharge machining process”, International Journal of Advanced and Applied Sciences, Vol. 4, No. 5, pp. 130-136, 2017 DOI: https://doi.org/10.21833/ijaas.2017.06.018

V. Perzel, P. Hreha, S. Hloch, H. Tozan, J. Valíček, “Vibration emission as a potential source of information for abrasive waterjet quality process control”, The International Journal of Advanced Manufacturing Technology, Vol. 61, No. 1-4, pp. 285– 294, 2012 DOI: https://doi.org/10.1007/s00170-011-3715-6

M. Palleda, “A study of taper angles and material removal rates of drilled holes in the abrasive water jet machining process”, Journal of Materials Processing Technology, Vol. 189, No. 1-3, pp. 292–295, 2007 DOI: https://doi.org/10.1016/j.jmatprotec.2007.01.039

M. Boujelbene, “Influence of the CO2 laser cutting process parameters on the Quadratic Mean Roughness Rq of the low carbon steel”, Procedia Manufacturing, Vol. 20, pp. 259-264, 2018 DOI: https://doi.org/10.1016/j.promfg.2018.02.038

D. C. Montgomery, Introduction to statistical quality control, 4th edn. Wiley, New York, NY, 2001

K. S. Chen, W. L. Pearn, “An application of non-normal process capability indices”, Quality and Reliability Engineering International, Vol. 13, No. 6, pp.355–360, 1997 DOI: https://doi.org/10.1002/(SICI)1099-1638(199711/12)13:6<355::AID-QRE125>3.0.CO;2-V

F. C. Kaminsky, R. A. Dovich, R. J. Burke, “Process capability indices: now and in the future”, Quality Engineering, Vol. 10, No. 3, pp. 445–453, 1998 DOI: https://doi.org/10.1080/08982119808919158

L. I. Tong, K. S. Chenn, H. T. Chen, “Statistical testing for assessing the performance of life time index of elcetronic component with exponential distribution”, Int J Qual Reliab Manage, Vol. 19, No. 7, pp. 812–824, 2001 DOI: https://doi.org/10.1108/02656710210434757

J. P. Chen, C. G. Ding, “A new process capability index for nonnormal distribution”, International Journal of Quality and Reliability Management, Vol. 18, No. 7, pp. 762–770, 2001 DOI: https://doi.org/10.1108/02656710110396076

S. Aravind, K. Shunmugesh, K. T. Akhilc, M. Pramod Kumar, “Process Capability Analysis and Optimization in Turning of 11sMn30 Alloy”, Materials Today: Proceedings, Vol. 4, No. 2, pp. 3608–3617, 2017 DOI: https://doi.org/10.1016/j.matpr.2017.02.253

P. K. Sahu, S. Pal. “Multi-response optimization of process parameters in friction stir welded AM20 magnesium alloy by Taguchi grey relational analysis”, Journal of Magnesium and Alloys, Vol. 3, No. 1, pp. 36-46, 2015 DOI: https://doi.org/10.1016/j.jma.2014.12.002

K. Abhishek, S. Datta, S. S. Mahapatra, “Multi-objective optimization in drilling of CFRP (polyester) composites: Application of a fuzzy embedded harmony search (HS) algorithm”, Measurement, Vol. 77, pp. 222-239, 2016 DOI: https://doi.org/10.1016/j.measurement.2015.09.015

A. Jeang, “Optimal process capability analysis for process design”, International Journal of Production Research, Vol. 48, No. 4, pp. 957–989, 2009 DOI: https://doi.org/10.1080/00207540802471306

B. El Aoud, M. Boujelbene, E. Bayraktar, S. Ben Salem, I. Miskioglu, “Studying Effect of CO2 Laser Cutting Parameters of Titanium Alloy on Heat Affected Zone and Kerf Width Using the Taguchi Method”, Mechanics of Composite and Multi-functional Materials, Vol. 6, pp. 143-150, 2018 DOI: https://doi.org/10.1007/978-3-319-63408-1_14

Downloads

How to Cite

[1]
M. Boujelbene, “Process Capability and Average Roughness in Abrasive Water Jet Cutting Process of Stainless Steel”, Eng. Technol. Appl. Sci. Res., vol. 8, no. 3, pp. 2931–2936, Jun. 2018.

Metrics

Abstract Views: 680
PDF Downloads: 290

Metrics Information
Bookmark and Share

Most read articles by the same author(s)