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Sahoo, Manoj Kumar
- Optimization of Milling Operation Parameter by Extended Taguchi Method
Abstract Views :902 |
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Authors
Affiliations
1 Department of Mechanical Engineering, Chouksey Engineering College, Bilaspur, IN
2 Department of Mechanical Engineering, Lakhmi Chand Institute of Technology, Bilaspur, IN
1 Department of Mechanical Engineering, Chouksey Engineering College, Bilaspur, IN
2 Department of Mechanical Engineering, Lakhmi Chand Institute of Technology, Bilaspur, IN
Source
International Journal of Technology, Vol 3, No 1 (2013), Pagination: 1-5Abstract
It has long been recognized that conditions during cutting, such as feed rate, cutting speed and depth of cut, should be selected to optimize the economics of machining operations as assessed by productivity, total manufacturing cost per component or some other suitable criterion. These quality features are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects create multiobjective problems. To predict this problem we take the sixteen combinations of milling machining operation from DOE. In view of the fact, that traditional Taguchi method cannot solve a multi-objective optimization problem; to overcome this limitation grey relational theory has been coupled with Taguchi method. This problem can be solved by extended Taguchi’s method to convert multi objective problem into single objective problem. The developed models for different constraints have been used for the construction of an optimization programmed which can be used to obtain optimum cutting speeds, feed rates, axial depth of cut and radial depth of cut under different constraints.Keywords
Milling, Quality, Surface Roughness, Material Removal Rate.References
- U. Khandey, S. Datta, S. S. Mahapatra and A. Bandyopadhyay, “Taguchi Approach coupled with PCA and Utility Concept for Optimization of Correlated Multi-Quality Characteristics in Straight Turning of Mild Steel”, For International Journal of Machining and Machinability of Materials,, Inderscience Publications. (Under Review) (Manuscript ID: IJMTM8950)
- Jaya Krishna, Kurnool (D. t),Vijaya Kumar Reddy, (2011), “Modeling of Machining Parameters in CNC End Milling Using Principal Component Analysis Based Neural Networks”. Innovative Systems Design and Engineering, Vol. 2 No. 3.
- Sanjit Moshat, Saurav Datta, Asish Bandyopadhyay and Pradip Kumar Pal, (2010) Optimization of CNC end milling process parameters using PCA-based Taguchi method, International Journal of Engineering, Science and Technology Vol. 2, No. 1, pp. 92-102.
- Wang M. Y. and Lan T. S., (2008), “Parametric Optimization on Multi-Objective Precision Turning Using Grey Relational Analysis”. Information Technology Journal, Volume 7, pp.1072- 1076.
- Peace, G., S., (1993), “Taguchi Methods- A Hands-On Approach”, Addison- Wesley Publishing Company. Massachusetts.
- Walia R. S., Shan H. S. and Kumar, P., (2006), “Multi-Response Optimization of CFAAFM Process Through Taguchi Method and Utility Concept”, Materials and Manufacturing Processes, Volume 21, pp. 907-914.
- Sahoo P., Barman T. K. and Routara B. C., (2008), “Taguchi based practical dimension modeling and optimization in CNC turning”, Advance in Production Engineering and Management, Volume 3, Number 4, pp. 205-217.
- Suresh P. V. S., Rao P. V. and Deshmukh S. G., (2002), “A genetic algorithmic approach for optimization of surface roughness prediction model”, International Journal of Machine Tools and Manufacture, Volume 42, pp. 675–680.
- Six Sigma in Industries
Abstract Views :215 |
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Authors
Affiliations
1 Department of Mechanical Engineering, Rungta College of Engineering & Technology, Raipur, IN
2 Department of Mechanical Engineering, Lakhmi Chand Institute of Technology, Bilaspur, IN
1 Department of Mechanical Engineering, Rungta College of Engineering & Technology, Raipur, IN
2 Department of Mechanical Engineering, Lakhmi Chand Institute of Technology, Bilaspur, IN
Source
International Journal of Technology, Vol 2, No 2 (2012), Pagination: 29-32Abstract
Implementation failure in six sigma concept in supply chain management has been increasing as a concern. The reason for many Six Sigma programmes to fail is due to an implementation model which is not at all user friendly. Using a successful Six Sigma, we have to perform strategic analysis driven by the market and the customer. It is necessary to establish a high-level, cross-functional team to drive the improvement initiative and to identify overall improvement tools. We can perform high-level process mapping and prioritize improvement opportunities and develop a detailed plan for low-level improvement teams, and then to implement, document, and revise as necessary. This is important for both practitioners and academicians for achieving success at the industry level.Keywords
Document, Implementation, MSOC, Revise, Six Sigma.- Vibration Analysis of a V-Groove Edged Cracked Cantilever Beam
Abstract Views :193 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, Chouksey Engineering College, Bilaspur, IN
1 Department of Mechanical Engineering, Chouksey Engineering College, Bilaspur, IN