a manufacturing process cannot be released to production until it has been proven to be stable. also, we cannot begin to talk about process capability until we have demonstrated stability in our process. this means that the process variation is the result of random causes only and all assignable or special causes have been removed. in complicated manufacturing processes, such as drilling proces...

One of the ways of attaining higher productivity and profitability in machining processes is to enhance process supervision and control systems. Because of the nonlinear behavior and complexity of machining processes, researchers have used knowledge-based techniques to improve the performance of such systems. Their main reason for using this approach is that a suitable process model is indispen...

In this paper, a comparative study was carried out to evaluate the real-time performance of fuzzy proportional-integral plus fuzzy proportional-derivative (Fuzzy PI + Fuzzy PD) controller with the real-time performance of Conventional PI for a liquid-level process experiment. The process considered for this experiment shows highly nonlinear behavior due to equal percentage pneumatic control val...

There exist problems in fuzzy finite element methods because technique of solving fuzzy equations is not perfect. For example, computation amount is too big and both sides of the equality are not exactly equal when solutions are substituted into the original equation. The concept of monosource fuzzy number is developed to simplify the calculation process of fuzzy equations. However the source o...

Over the past few years, a number of key issues related to the product family design process have been addressed, and a great deal of work has been done to improve it. Many different philosophies, approaches, frameworks, methods and methodologies have been employed in this effort, such as mass customization, modularity, delayed differentiation, commonality, platforms, product families, and so o...

One of the techniques used to support decisions in uncertain environments is the Fuzzy TOPSIS method. However, from crisp data, this method considers only one fuzzy set in their analysis, besides being a strictly mathematical optimization technique. This article proposes extensions to the original Fuzzy TOPSIS, exploring two distinct versions: to increase the method with the necessary resources...

This study presents an adaptation method for Sugeno fuzzy inference systems that maintain the readability and interpretability of the fuzzy model during and after the learning process. This approach can be used for modelling of dynamical systems and for building adaptive model-based control algorithms for chemical processes. The gradient-descent based learning algorithm can be used on-line to f...

A special nonlinear fuzzy controller is presented to control the output signal of an undamped one-degree-of-freedom oscillating system with nonlinear characteristic. Basically, this controller consists of a feedback part and a feed-forward part. Whereas the feedback part is made up by a classical fuzzy controller, the feed-forward part is based on a fuzzy model taking into account the nonlinear...

This paper studies a renewal reward process with fuzzy random interarrival times and rewards under the >-independence associated with any continuous Archimedean t-norm >. The interarrival times and rewards of the renewal reward process are assumed to be positive fuzzy random variables whose fuzzy realizations are >-independent fuzzy variables. Under these conditions, some limit theorems in mean...