Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
A course in fuzzy systems and control
A course in fuzzy systems and control
Industrial Applications of Fuzzy Control
Industrial Applications of Fuzzy Control
Introduction to Fuzzy Logic using MATLAB
Introduction to Fuzzy Logic using MATLAB
The compact fuzzy filter design via Takagi-Sugeno fuzzy models
Expert Systems with Applications: An International Journal
The process model to aid innovation of products conceptual design
Expert Systems with Applications: An International Journal
International Journal of Human-Computer Studies
Expert Systems with Applications: An International Journal
Fuzzy model tuning using simulated annealing
Expert Systems with Applications: An International Journal
A fuzzy multi-criteria decision making model for supplier selection
Expert Systems with Applications: An International Journal
Supplier selection using consistent fuzzy preference relations
Expert Systems with Applications: An International Journal
An interactive method for dynamic intuitionistic fuzzy multi-attribute group decision making
Expert Systems with Applications: An International Journal
Process compilation of thin film microdevices
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Expert Systems with Applications: An International Journal
Stable and convergent iterative feedback tuning of fuzzy controllers for discrete-time SISO systems
Expert Systems with Applications: An International Journal
Evolutionary optimization-based tuning of low-cost fuzzy controllers for servo systems
Knowledge-Based Systems
Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
In this paper we present the development of a system to evaluate alternatives for manufacturing process steps for micro-electro-mechanical systems (MEMS). We explain in detail a formal process flow definition for MEMS fabrication. Then, we develop a fuzzy inference system which allows MEMS developers to capture users' preferences to rank the alternatives available to complete the process steps required to fabricate a device. In the last part to this work, we present two case studies: alternatives evaluation for impurity doping and for lead zirconate titanate (PZT) patterning. Using an assortment of user preference data to rate a variety of criteria for potential alternatives, our approach produces a clear preference for one specific alternative in each case, which exemplifies the usefulness of the system proposed and illustrates how effective this methodology is towards improving the fabrication process for MEMS.