Browsing by Author "Singh, Navin Runjit."
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Item Application of military logistic techniques to industrial applications.(2002) Singh, Navin Runjit.; Thomson, Elza.The main reason for the low production efficiencies at North Coast Milling is the frequent stoppages due to equipment breakdowns and the requirement for unscheduled maintenance. In order for this factory to be able to reach the desired efficiencies, it is imperative that downtime and cost drivers in the production lines be identified and rectified. In order to achieve world-class performance, more and more companies are replacing their reactive strategies for maintenance with proactive strategies like Preventive maintenance (PM), Reliability-centred maintenance (RCM) and Condition based maintenance (CBM) and aggressive strategies like Total Productive Maintenance (TPM). While these newer maintenance strategies require increased commitments to training, resources and integration, they also promise to improve performance. New asset management philosophies are being implemented world-wide in an effort to improve industrial system reliability as well as to reduce maintenance costs. Concepts such as TPM, RCM and CBM are being customised for implementation in various industries. Real-time condition monitoring via computerised maintenance management systems has helped make it possible to transfer from a time-based maintenance strategy to a condition-based maintenance strategy. Detecting possible future failures is now a cost-effective reality that reduces considerably the risk of catastrophic failures and system breakdowns. The aIm of the study is to apply military logistic techniques to the industrial environment of North Coast Milling in order to identify downtime and cost drivers. It will be shown that more of the military logistics techniques can be incorporated into some of the existing maintenance techniques at this factory, which would aid in the achievement of maximum plant utilisation and minimum downtime.!Item Multiuser demodulation for DS-CDMA systems in fading channels.(2000) Singh, Navin Runjit.; Takawira, Fambirai.The problems of optimal as well as suboptimal detection for CDMA transmissions over an additive white Gaussian noise (AWGN) channel, have been the focus of study in the recent past. However, CDMA transmissions are frequently made over channels which exhibit fading and/or dispersion; hence receivers need to be designed which take into account this behaviour. In spite of the major research effort invested in multiuser demodulation techniques, several practical as well as theoretical open problems still exist. Some of them are considered in more detail in this thesis. The aim of the thesis is to develop multiuser demodulation algorithms for mobile communication systems in frequency-selective fading channels, and to analyze their implementation complexity. The emphasis is restricted to the uplink of an asynchronous DS-CDMA system where the users transmit in an uncoordinated manner and are received by one centralized receiver. The original work that is undertaken for the MScEng study is the evaluation of a multiuser receiver structure for a frequency-selective fading channel, where there exists a steady specular path and two fading paths. Furthermore, the effect of using selection diversity is investigated by examining the bit error rate, asymptotic multi user efficiency and near-far resistance of the proposed detector structure. These results are confirmed both analytically and by simulation in the thesis. An investigation is also conducted into the application of neural networks to the problem of multiuser detection in code division multiple access systems. The neural network will be used as a classifier in an adaptive receiver which incorporates an extended Kalman filter for joint amplitude and delay estimation. Finally, some open problems for future research will be pointed out in the thesis. Keywords: AWGN channel , DS-CDMA system, frequency-selective, multi user demodulation, asymptotic multiuser efficiency, near-far resistance, neural network, Kalman filter.