UGC CARE norms ugc approved journal norms IJRTI Research Journal

WhatsApp
Click Here

International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 75

Article Submitted : 4301

Article Published : 2432

Total Authors : 6372

Total Reviewer : 533

Total Countries : 46

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: comparative analysis and optimization of process parameters in machining operation using central composite design and box behnken design over steel 1018
Authors Name: Abhinay Kumar , Dr Ajay Kumar Sarathe
Download E-Certificate: Download
Author Reg. ID:
IJRTI_170581
Published Paper Id: IJRTI1711011
Published In: Volume 2 Issue 11, November-2017
DOI:
Abstract: Surface roughness is a parameter which determines the quality of machined product. Now a days the general manufacturing problem can be described as the attainment of a predefined product quality with given equipment, cost and time constraints. So in recent years, a lot of extensive research work has been carried out for achieving predefined surface quality of machined product to eliminate wastage of over machining. Response surface methodology is used for prediction of surface roughness of machined part. This paper particularly shows the main findings of an experimental investigation into the effects of the cutting speed, feed rate, depth of cut, nose radius and cutting environment in turning. Design of experiment techniques, i.e. Response Surface Methodology (RSM) is going to be used to accomplish the objective of the experimental study. In this research work a new predictive model is proposed which is based on Central composite design and box behnken design. These both the techniques use statistical analysis and quadratic model for optimization of parameters in turning operation. Quadratic model gives best fits for the regression to find the optimal solution of equation and the proposed quadratic equation for predictive model
Keywords: Response Surface Methodology (RSM), DOE, CCD, BBD, ANOVA
Cite Article: "comparative analysis and optimization of process parameters in machining operation using central composite design and box behnken design over steel 1018", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 11, page no.58 - 68, November-2017, Available :http://www.ijrti.org/papers/IJRTI1711011.pdf
Downloads: 000101949
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI1711011
Registration ID:170581
Published In: Volume 2 Issue 11, November-2017
DOI (Digital Object Identifier):
Page No: 58 - 68
Country: bhopal, madhya pradesh, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI1711011
Published Paper PDF: https://www.ijrti.org/papers/IJRTI1711011
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Join RMS/Earn 300

IJRTI

Indexing Partner