The most significant process parameters affecting dimensional shrinkage in transverse and longitudinal directions of molded parts in Plastic Injection Molding (PIM) process are injection velocity, mold temperature, melt temperature and packing pressure. In the present work, ANN model was developed for forward and reverse mapping prediction. In forward mapping PIM process parameters are expressed as the input parameters to predict dimensional shrinkage, whereas in reverse mapping, attempts were made to predict an appropriate set of process parameters required for arriving at the required dimensional shrinkage. The trained network with one thousand input-output data randomly generated from regression equations reported by earlier researchers resulted in minimum mean squared error. The performance of developed model was compared with experimental values for ten different test cases. The results show that ANN model with both forward and reverse mapping is capable of prediction with an error level of less than ten percent.

Green sand casting is treated as the most versatile casting process due to their excellent design flexibility that offer complex shapes and ability to reclaim silica sand. The modern foundries are looking for alternate moulding materials to partially replace the high cost silica sand. Cow dung is a naturally available eco-friendly binding as well as additive material and is used to partially replace the silica sand. Improper choice of the combination of moulding sand variables, such as degree of ramming, percentage of cow dung, percentage of clay, and percent of water will affect the moulding sand properties and thereby quality of casting. In the present work, Taguchi method is employed to plan and conduct experiments. Pareto analysis of variance is performed to know the contribution of variables on the moulding sand properties (i.e. compression strength, permeability, loss-on-ignition). Taguchi DEAR method is used to determine the single optimal levels of input factors that enhances the performances of all the sand mould properties. Percent of clay and cow-dung found to be the most dominating factor towards all the sand mould properties.

The present work focuses on the mold design and production of the multifunctional device laryngoscope with surface quality through the injection molding process. A laryngoscope is a device used by anesthesiologists to lift the tongue that facilitates to fix the air pipe in the larynx. Demand still exists in the laryngoscope part to assist anesthesiologists to take care of the airway without causing chest compression and ensure visualization of vocal cords. Therefore, the present work aims at developing a laryngoscope with a double channeled device, wherein one for aligning the camera and another for the air pipe. The paper outlines the design parameters required for manufacturing a single cavity mold to produce a laryngoscope viz. injection molding machine. The mold has multiple plates with complex fluid channels which ensures effective thermal management in-mold system. The mold is manufactured using high-strength tool steel materials and the product laryngoscope (ABS: Acrylonitrile butadiene styrene) is fabricated from the designed mold. Taguchi L9 experimental array was used to determine the optimal conditions (injection pressure, injection velocity, mold and melt temperature) for desired surface finish in the laryngoscope parts. The designed mold and optimized injection molding conditions resulted in a lower surface roughness value equal to 0.214 µm. Thereby, injection-molded laryngoscope parts can be used for large-scale productions for the benefit of medical applications.

Text Extraction plays a major role in finding vital and valuable information. Text extraction involvesdetection, localization, tracking, binarization, extraction, enhancement and recognition of the text fromthe given image. These text characters are difficult to be detected and recognized due to their deviation ofsize, font, style, orientation, alignment, contrast, complex coloured, textured background. Due to rapidgrowth of available multimedia documents and growing requirement for information, identification,indexing and retrieval, many researches have been done on text extraction in images. Several techniqueshave been developed for extracting the text from an image. The proposed methods were based onmorphological operators, wavelet transform, artificial neural network, skeletonization operation, edgedetection algorithm, histogram technique etc. All these techniques have their benefits and restrictions. This article discusses various schemes proposed earlier for extracting the text from an image. This paperalso provides the performance comparison of several existing methods proposed by researchers inextracting the text from an image.