Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process
Today's manufacturing methods are caught between the growing need for quality, high process safety, ...
Neural networks are potential tools that can be used to improve process quality control. In fact, va...
The need for production has roots in human life and its history. This date back to primitive days of...
The cost of a fabrication line such as one in a semiconductor house has increased dramatically over ...
A neural network-based process model is proposed to optimize the semiconductor manufacturing process...
Neural networks have been applied within manufacturing domains, in particular electronics industries...
This paper describes a generic dynamic control system designed for use in semiconductor fabrication ...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
Manufacturers address the distinct operational objectives of product innovation and manufacturing ef...
This paper deals with applications of machine learning algorithms in manufacturing. Machine learning...
The thesis focuses on the design and implementation of a control scheme for a photolithography proce...
The thesis focuses on the design and implementation of a control scheme for a photolithography proce...
Advances in technology like the miniaturization of electronic devices have caused wafer fabrication ...
Advances in technology like the miniaturization of electronic devices have caused wafer fabrication ...
Today's manufacturing methods are caught between the growing need for quality, high process safety, ...
Neural networks are potential tools that can be used to improve process quality control. In fact, va...
The need for production has roots in human life and its history. This date back to primitive days of...
The cost of a fabrication line such as one in a semiconductor house has increased dramatically over ...
A neural network-based process model is proposed to optimize the semiconductor manufacturing process...
Neural networks have been applied within manufacturing domains, in particular electronics industries...
This paper describes a generic dynamic control system designed for use in semiconductor fabrication ...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
An optimal design of semiconductor device and its process uniformity are critical factors affecting ...
Manufacturers address the distinct operational objectives of product innovation and manufacturing ef...
This paper deals with applications of machine learning algorithms in manufacturing. Machine learning...
The thesis focuses on the design and implementation of a control scheme for a photolithography proce...
The thesis focuses on the design and implementation of a control scheme for a photolithography proce...
Advances in technology like the miniaturization of electronic devices have caused wafer fabrication ...
Advances in technology like the miniaturization of electronic devices have caused wafer fabrication ...
Today's manufacturing methods are caught between the growing need for quality, high process safety, ...
Neural networks are potential tools that can be used to improve process quality control. In fact, va...
The need for production has roots in human life and its history. This date back to primitive days of...