NISCAIR Online Periodicals Repository Collection: JSIR Vol.65(04) [April 2006]

Prediction of air delivery, noise and power consumption of fan for TEFC electric motors

Wed, 29 Mar 2006 22:58:59 GMT

Title: Prediction of air delivery, noise and power consumption of fan for TEFC electric motors

Authors: Desale, Rajgopal; Deshmukh, N K

Abstract: This paper describes the method for estimating air delivery, noise and power consumed by fan for TEFC (Totally Enclosed Fan Cooled) motor at design stage itself. It is a program based on semi-empirical relations with constants derived from extensive experiments. Program (in C++) is provided with inputs with regard to fan geometry, rotational speed and system resistance, the programme gives necessary output for air delivery, noise and power consumed. Optimisation is done based on the weightage factor provided by the user. Fans for different frame size were designed, developed, tested and results compared with predicted values and found to be within 10% for air delivery and noise. However, power consumption results were within 15%.

Page(s): 344-348

An adaptive network-based fuzzy approach for prediction of surface roughness in CNC end milling

Wed, 29 Mar 2006 22:58:59 GMT

Title: An adaptive network-based fuzzy approach for prediction of surface roughness in CNC end milling

Authors: Roy, Shibendu Shekhar

Abstract: An Adaptive Network-based Fuzzy Inference System (ANFIS) has been designed for modeling and predicting the surface roughness in end milling operation for set of three given milling parameters (spindle speed, feed rate and depth of cut). Two different membership functions (triangular and bell shaped) were used during the hybrid-training process of ANFIS in order to compare the prediction accuracy of surface roughness by the two membership functions. The predicted surface roughness values obtained from ANFIS were compared with experimental data and multiple regression analysis. The comparison indicates that the adoption of both membership functions in ANFIS achieved better accuracy than multiple regression model.

Page(s): 329-334

Sensitivity study of Gaussian dispersion models

Wed, 29 Mar 2006 22:58:59 GMT

Title: Sensitivity study of Gaussian dispersion models

Authors: Sriram, G; Mohan, N Krishna; Gopalasamy, V

Abstract: Over the last three decades, strict environmental regulations and the availability of personal computers have fueled an immense use of mathematical models to predict the dispersion of air pollution plumes. This paper discusses how the propagation of seemingly small errors in the Gaussian model parameters can cause very large variations in the model’s predictions.

Page(s): 321-324

Multiple-objective planning for a production and distribution model of the supply chain: Case of a bicycle manufacturer

Wed, 29 Mar 2006 22:58:59 GMT

Title: Multiple-objective planning for a production and distribution model of the supply chain: Case of a bicycle manufacturer

Authors: Tzeng, Gwo-Hshiung; Tang, Tzung-I; Hung, Yu-Min; Chang, Min-Lan

Abstract: The bicycle industry is one of the most competitive industries in Taiwan. To construct multi-objective production and distribution models for supply chain, following five methods are compared and discussed: (i) Multi-objective compromise programming; (ii) Fuzzy multi-objective programming; (iii) Weighted multi-objective programming; (iv) Weighted fuzzy multi-objective programming; and (v) Two-phase fuzzy multi- objective programming. The weighted multi-objective model has been found better for considering the maximum profit for enterprises and the maximum quality for customer service. After raising the per-unit production cost in production processes, it was observed that the total profit would decrease in real empirical study. In addition, if the unit inventory cost increases due to improving the customer service level, then the total profit might increase, but not significantly.

Page(s): 309-320