Product End Quality Assessment using Vibration Analysis Technique
- February 17, 2018
- Posted by: RSIS
- Categories: Engineering, Mechanical Engineering
International Journal of Research and Innovation in Applied Science (IJRIAS) | Volume III, Issue II, February 2018 | ISSN 2454-6194
Product End Quality Assessment using Vibration Analysis Technique
Manjunath K.S1, Dr. H. N. Suresh2
1Assistant Professor, Department of Mechanical Engineering, Bangalore Technological Institute, Bangalore, India
2Professor & HOD, Department of Automobile Engineering, Dayanand Sagar College of Engineering, Bangalore, India
Abstract—In manufacturing industry in production of parts machine tool plays a vital role. Good quality end product depends on condition of the machine. More condition monitoring methods are used to determine condition of the machine like vibration and noise but vibration signal analysis is the best one because by measuring vibration signal majority of machine tool problems can be assessed. Two lathes were selected (PSG A141) for the study one is in good condition (PSG A141A) and other not in a condition (PSG A141B). This work is carried out using shock pulse meter (SPM) to collect vibration level at different operating condition. Then the vibration data is analyzed using statistical tools like Multiple Regression Analysis to check the relationship between vibration level and their parameters, collinearity between dependant and independent variables along with determination of their coefficients. Monte Carlo Simulation in @RISK of palisade, UK is used for effective analysis for the generated regression model. Process Capability and Capability Index method is used to examine the process condition by which we can check whether product is acceptable or not. In this study, the graphical result shows that whether the vibration level is under control or not by specifying suitable upper and lower specification limits. When the process capability and capability index value is more than 1, it means a better quality product or the process is capable of producing acceptable products.
Index Terms—vibration, analysis, specification limit, frequency, quality.
I. INTRODUCTION
FFT analyzer and Artificial Neural network technique to conclude and propose the best possible solution to the challenges of error caused during the operation of a machine tool for improved productivity [1]. Control charts were added for the monitoring of machine tool performance parameters. A method of size normalization has been included to compensate for overall performance parameter inter-dependence [2].
