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Skin cancer is the most common of all cancers. About 35 million cases of skin cancer are diagnosed every year. Malignant melanoma is a dangerous type of skin cancer and it is difficult to treat. Early diagnosis and treatment can increase the survival rate from melanoma. However, the therapeutic treatment is the main option but still it is not feasible for most of the cases. The conventional method of drug release may cause damage to the normal cells present near the abnormal cells due to improper dosage of drug. In order to reduce the impact of drug in normal cells, the flow rate of the drug has to be controlled and the fascination rate of the drug by abnormal cells should be made maximum by targeted drug delivery. The proposed work is to convert the biological system comprising three layers like dermis, subcutaneous tissues, and bones and muscular layers into an equivalent electrical system. The mathematical model for the biological system is determined with its equivalent electrical system, and the tool PSPICE is used to evaluate the fascination and dispersion rate of the drug. In addition to evaluation of fascination and dispersion rate using PSPICE, the fascination rate of drug is measured individually for the three layers as well as for the combination of first two layers (dermis and subcutaneous layers) and for all the three layers using MATLAB. The comparison of the fascination and dispersion rates is done for all the three layers and the same has been analyzed by incorporating a conventional proportional-integral-derivative controller to minimize the dispersion rate.

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Machining the mica insulation in commutator to provide under cut in the surface of contact with the carbon brush is a vital process related to the life of the product. Complete removal of mica in the contact surface is essential and this requires complex sensing and positioning of the thin mica layer during machining. This study revealed improving the sensing and positioning technologies is not adequate and evolved a robust product-process design to overcome the real root cause of variations in the manufacturing process. Combined use of orthogonal array, Shainin technique, physical-mechanism analysis, relations-diagram and evaporating-cloud method complemented the problem solving approach in gaining knowledge and evolving robustness.