Condition monitoring is used as a tool for maintenance management and function as input to decision support. Thus the key parameters in preventing severe damage to railway assets can be determined by automatic real-time monitoring. The technique of radio-frequency identification (RFID) is increasingly applied for the automatic real-time monitoring and control of railway assets, which employs radio waves without the use of physical contact. In this work, a 243-km 2 area of Kuala Lumpur was selected. Because of its large size, determining the locations in which to install the RFID readers for monitoring the bogie components in the Kuala Lumpur railway system is a very complex task. The task involved three challenges: first, finding an optimal evolutionary method for railway network planning in order to deploy the RFID system in a large-area; second, identifying the large area that involved functional features; third, determining which station or stations should be given priority in applying the RFID system to achieve the most effective monitoring of the trains. The first challenge was solved by using a gradientbase cuckoo search algorithm for RFID system deployment. The second challenge was solved by determining all necessary information using geographic information system (GIS) resources. Because of the huge volume of data collected from GIS, it was found that the best method for eliminating data was to develop a new clustering model to separate the useful from the unuseful data and to identify the most suitable stations. Finally, the data set was reduced by developing a specific filter, and the information collected was tested by an analytic hierarchy process as a technique to determine the best stations for system monitoring and control. The results showed the success of the proposed method in solving the significant challenge of large-scale area conditions correlated with multi-objective RFID functions. The method provides high reliability in working with complex and dynamic data. Keywords Geographic information system (GIS) Á Analytic hierarchy process (AHP) Á Radio-frequency identification (RFID) Á Gradient-based cuckoo search algorithm (GBCS) Á Condition monitoring Á Bogie system Á Railway maintenance
Particle Swarm Optimization (PSO) algorithm is often used for solving RFID Network Planning (RNP) problems. However, the direct correlation between RNP parameters (coordinates and power settings of RFID readers) and PSO solutions is rarely shown. This is due to the fact that most researches done in this field focus more on the development of new variants of PSO and the optimization result. For that reason, this paper tends to investigate the correlation between RNP parameters and PSO solutions. One of RNP objectives (Optimal Tag Coverage) is taken as an example. The formula of optimal tag coverage is elaborated in order to expose the allocation of RNP parameters in the formula. In addition, a representation system for embedding RNP parameters in PSO solution is explained. This paper can also serves as an early guideline for solving RNP problems using PSO algorithm.
Abstract. Reverse engineering (RE) process is capable of producing CAD models from the existing part without the need of a blueprints or CAD drawing. One of the method to implement RE is via 3D scanning and the main goal is to produce CAD files that have the highest accuracy possible when compared to the actual parts. Any effort to improve the 3D scanning process should be encouraged because it will save a lot of time and expenses. As a result, this research tends to investigate the effects of surface parameters (Percentage of triangles and Grids resolution) to the performance of RE. Design of Experiments (DOE) method was used and the responses are measured in terms of File size and Error percentage. From the results, it is very interesting to note that the percentage of triangles does not have a significant effect to the file size but plays a major role in minimizing the dimension error. The grids resolution has the significant effects to the file size and error percentage. It can also be concluded that in order to get the best RE performance, the percentage of triangles and file size should be set to maximum. This will ensure that the generated CAD files will have the highest accuracy and from here, high quality products can be made from the RE process.
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