Papers by Keyword: Flexible Factor

Abstract: In earlier decades several studies made on Total Quality Management (TQM) practices in small and medium scale enterprises. By compiling the various research works that were carried out during 2010-2015 in the field of Small and Medium-Scale Industries (SMSIs) TQM can be broadly conceptualized in to as flexible and rigid practices. From the limited level of investigations so far made on the various research works it has lead in identifying the different factors that influence TQM practices in SMSIs and its supplementary growth. The purpose of this article is to examine the influence of flexible and rigid TQM practices in SMSIs. It gives a broad overview of how TQM practices are constructed and how it acts on the various quality improvements. This work is expected to widely sensitize the TQM practices in SMSIs and how quality assurance in organizations will have to gain its place in future.

Abstract: A dynamic size control model during cylindrical grinding is built. The model consists of Elman neural network, fuzzy control subsystem and deformation optimal adaptive control subsystem. To improve the size prediction accuracy, the first and the second derivative of the actual amount removed from the workpiece are added into the Elman network input; To self-adapt and adjust the quantification factor and scale factor in the fuzzy control, the flexible factor is introduced to the fuzzy control model. Simulation and experiment verify that the developed prediction control model is feasible and has high prediction and control precision.

Abstract: A size intelligent prediction control model during traverse grinding is constructed. The model is composed of the neural network prediction model, the deformation optimal adaptive control system and fuzzy control model. Dynamic Elman network is used in the prediction model. The first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the prediction accuracy. The flexible factor is introduced to the fuzzy control model, which can self-adapt and adjust the quantification factor and scale factor in the fuzzy control. Simulation and experiment verify that the developed prediction control model is feasible and has high prediction and control precision.