scholarly journals A Product Review Using Rule Base And Fuzzy Logic Approach

Author(s):  
Rita R. Bhawalkar
2011 ◽  
Vol 87 ◽  
pp. 119-122
Author(s):  
Tosapolporn Pornpibunsompop ◽  
Attapon Charoenpon ◽  
Ekaratch Pankaew

DFMEA is a significantly efficient tool to systematically evaluate risk in early stage of product design and development but some of knowledge and information are uncertain and imprecise. This research focuses on fuzzy logic approach to diminish weaknesses and applies to launch tube’s DFMEA. The methodology started from determine membership function of severity, occurrence, and detection and provide fuzzy rule base to arranged category of risk. Afterwards, center average index was selected as defuzzifier for risk value representation. Consequently, the prioritization based on risk value was done and chosen the first five risk value of potential failure modes to analyze causes then recommended appropriate actions. After application of fuzzy logic approach, the most vital potential failure mode is damaged launch tube due to detention force which is rated as first and second priority depending on potential cause or mechanism. The third priority is launch tube distortion. The mechanical load calculation and proper material selection are the recommended actions for overcoming those potential failure modes.


Robotica ◽  
2006 ◽  
Vol 25 (3) ◽  
pp. 325-339
Author(s):  
X. J. Wu ◽  
J. Tang ◽  
Q. Li ◽  
K. H. Heng

SUMMARYDue to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on vector-format fuzzy variables. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environ-ment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.


1998 ◽  
Author(s):  
Thomas Meitzler ◽  
Regina Kistner ◽  
Bill Pibil ◽  
Euijung Sohn ◽  
Darryl Bryk ◽  
...  

Author(s):  
Abdoul Azize Kindo ◽  
Guidedi Kaladzavi ◽  
Sadouanouan Malo ◽  
Gaoussou Camara ◽  
Theodore Marie Yves Tapsoba ◽  
...  

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