Entity

Time filter

Source Type

MMU
Ambāla, India

Gupta V.,MMU
International Journal of Applied Engineering Research | Year: 2012

India is a large coal producing country where a large number of heavy earthmoving equipment is deployed for the production system. The cost of equipment is increasing day by day. The dumpers play a major role for the haulage of minerals and other bulk materials in mining and earthmoving industry. A large fleet of dumpers are deployed at the mining and construction projects to perform various tasks. An effective utilization of the dumpers would be only possible if the equipment availability can be improved. The maintenance of dumpers at the workshops often suffers due to limited manpower resource. This leads to an increased downtime of the machines and as a result the equipment availability gets reduced. The cost of maintenance of dumpers is influenced by a number of factors like type of job, quality of supervision, availability of logistics, etc. The maintenance times for the different subsystems of dumpers would vary depending on the type and complexity of the job. This paper aims to study the major factors influencing the maintenance system and to determine the optimal manpower cost for maintenance jobs. The effect of these factors on the various types of maintenance jobs with regard to their complexity has also been examined. The constraints in such analytical exercise have been formulated on the basis of some prioritised key jobs. The model development and the scope for application of the fuzzy logic goal programming approach for maintenance system job evaluation have been presented. © Research India Publications. Source


Gupta V.,MMU
International Journal of Applied Engineering Research | Year: 2012

Recession, render down economy and fold up of giant corporate houses are very frequent phenomenon now, having affect on society directly. These effects change the society badly in the form of sociological, economical and physiological changes. For the welfare of common people and self, industrialists have to espouse the newer and effectual technologies to minimise the risk of loosing the business. In industries, every equipment plays an imperative function and its malfunction leads to heavy cost, fearing of loosing the business forever. The present study to resolute the expenditure inference conjures up of maintenance of boilers at Sugar Plant. For this, a preemptive Goal Programming conjures up by considering foremost influencing factors. Any alteration in these factors, maintenance time also gets ostentatious. However, these factors are sublevelled more for an accurate conjecture of optimal maintenance time. Finally, the conjure up is worked out within 3% variation from the benchmark jobs involved. © Research India Publications. Source


Kaushik G.,Maharishi Markandeshwar University and 380 81 | Sinha H.P.,MMU | Dewan L.,National Institute of Technology Kurukshetra
Journal of Theoretical and Applied Information Technology | Year: 2014

The core intention of this work is to investigate the wavelet function that is optimum in identifying and denoising the various biomedical signals. Using traditional methods it is difficult to recover the noises present in the signals. This paper presents a detail analysis of Discrete Wavelet Transform (DWT) denoising on various wavelet families and biomedical signals such as ECG, EMG and EEG. We have developed a trained network in order to optimally denoise the signals by using a back propagation algorithm in the neural network. Initially noise is added to the original signal, then the signal is decomposed using the Shift Invariant method. After decomposition, the proposed wavelet based method is used for noise removal. Then the signal is reconstructed by using wavelet reconstruction method. The denoised signals will be compressed by a hybrid wavelet shannon fano coding for reducing its storage size. © 2005 - 2014 JATIT & LLS. All rights reserved. Source


Kaushik G.,Maharishi Markandeshwar University | Sinha H.P.,MMU | Dewan L.,National Institute of Technology Kurukshetra
Research Journal of Applied Sciences | Year: 2014

The core intention of this research is to investigate the wavelet function that is optimum in identifying and de-noising the various biomedical signals. Using traditional methods, it is difficult to recover the noises present in the signals. This study presents a detail analysis of Discrete Wavelet Transform (DWT) de-noising on various wavelet families and biomedical signals such as ECG, EMG and EEG. Researchers have developed a trained network in order to optimally denoise the signals by using a Back Propagation algorithm in the neural network. Initially noise is added to the original signal then the signal is decomposed using the Shift Invariant Method. After decomposition, the proposed Wavelet Based Method is used for noise removal. Then, the signal is reconstructed by using Wavelet Reconstruction Method. The denoised signals will be compressed by a hybrid wavelet shannon fano coding for reducing its storage size. © Medwell Journals, 2014. Source


Kaur G.,Panjab University | Kumar N.,Panjab University | Khanna R.,MMU | Kumar A.,Business Initiatives and Project Planning
2015 2nd International Conference on Recent Advances in Engineering and Computational Sciences, RAECS 2015 | Year: 2015

Speech signal carries the information about the linguistic message. Speaker-specific information is also contained in speech signal. No two peoples voice are exactly alike because voice has fingerprint qualities. It is generated by acoustically exciting the cavities of the mouth and nose, and can be used to recognize (identify/verify) a person. The work leading in this paper has been focused on establishing a text-dependent closed-set speaker verification. In this, correlation method is used to verify the speaker. © 2015 IEEE. Source

Discover hidden collaborations