This research has developed an extended Artificial Neural Networks (ANN) based high speed accurate transmission line fault location for double phase to- earth fault on non-direct-ground. Therefore, this research presents a system that capable of detecting and locating the fault with less proportion of error. This system uses the Global Positioning System (GPS) to locate the position and the Global System for Mobile Communication (GSM) to send these messages to system supervisor. A reduction in the size of the neural network improves the performance of the same and this can be achieved by performing feature extraction. By doing this, all of the important and relevant information present in the waveforms of the voltage and current signals can be used effectively. Voltage and current waveforms have been generated and were sampled at a frequency of 720 Hertz. The neural network diagnostic system trained for double faults was found to be able to accurately diagnose abnormal behavior resulting from simultaneous multiple faults. Graceful degradation of the diagnostic system was observed in situations where faults where not accurately diagnosed or under damage to a few nodes.

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Electronic weighing systems are used in industries and business establishments for weighing and segregating materials accurately for process scales. Thus, the aim of this research is to design and implement a microcontroller based optical displacement weighing scale. The electronic weighing system comprises the basic load cell suitable signal conditioners and output recorders/indicators giving both the analog and digital output for further processing. The signals from the load cell are amplified and fed to analog/digital converter, which provide an output in the digital format for display printing/processing etc. The strain gauge based load cell is the most popular weight transducer used in the electronic weighing system.

Intense competition in today’s economy, the shrinking life cycles of products, and the heightening expectations of customers have forced business enterprises to focus their attention on correctly arranging and controlling their production and supply chain systems. Thus, manufacturing firms/industries adopt JIT techniques to enjoy competitive advantage. In this paper, a literature review is presented to show the important applications of JIT Algorithms and Models in Production Systems. The purpose of this step is to review the results obtained from the implementation and to provide the practical recommendations for further improvement. This will help reveal practical issues encountered in the implementation. All these issues should become main concerns if the manufacturing Plant wants to get maximum benefits from the JIT implementation. This study bridged a research gap by identifying a framework for re-design of manufacturing systems into practical optimum Just-In-Time systems. The conventional JIT approach is mostly applicable to static production systems and the dynamic production systems require a more practical integrated JIT approach.

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