Product Function: Component Modeling Using Rough Sets

2009 ◽  
Author(s):  
Toshiharu Miwa ◽  
Hideki Aoyama
Keyword(s):  
Product Development ◽  
Rough Sets ◽  
Early Stage ◽  
Modeling Method ◽  
Rough Sets Theory ◽  
Development Cycle ◽  
Product Function ◽  
Lower And Upper Approximations ◽  
Sets Theory ◽  
Manufacturing Parameters

The acceleration of the product development cycle continues to be a significant challenge for manufacturing firms around the world. The misunderstanding of important relationships between product functions and components leads the delay of product development. The present paper describes an identification method of the relationships between product functions and components at the early stage of product development. The proposed product function-component modeling method using rough sets theory extracts the characteristic relationships between product functions and components from a small amount of the qualitative and linguistically-expressed knowledge data. The advantage of using the rough sets is that the combination of necessary and possible sets (lower and upper approximations) represents the vague knowledge. The present paper describes an example of a conventional cutting process with 6 manufacturing parameters that this method contributes to the identification of cutting mechanism from a small amount of sampling data (7% of whole event) compared to the conventional statistical modeling method.

The Rough Sets Theory and Evidence Theory

1990 ◽  
Vol 13 (3) ◽  
pp. 245-262
Author(s):  
Andrzej Skowron
Keyword(s):  
Rough Sets ◽  
Evidence Theory ◽  
Decision Table ◽  
Combination Rule ◽  
Approximation Space ◽  
Approximation Spaces ◽  
Rough Sets Theory ◽  
Decision Attributes ◽  
Lower And Upper Approximations ◽  
Sets Theory

The aim of the paper is to show some connections between the rough sets theory and the Dempser-Shafer approach. We prove that for every Pawlak’s approximation space there exists a Dempster-Shafer space with the qualities of the lower and upper approximations of sets in the approximation space equal to the credibility and plausibility of sets in the Dempster-Shafer space, respectively. Analogous connections hold between approximation spaces generated by the decision tables and Dempster-Shafer spaces, namely for every decision table space there exists a Dempster-Shafer space such that the qualities of the lower and upper approximations (with respect to the condition attributes) of sets definable in the decision table by condition and decision attributes coincide with the credibility and plausibility of sets in the Dempster-Shafer space, respectively. A combination rule in approximation spaces analogous to the combination rule used in the Dempster approach is derived.

Compound-Fault Diagnosis of Bearing Based on Order Tracking Wavelet Packet and Rough Sets

2011 ◽  
Vol 130-134 ◽  
pp. 1681-1685 ◽  
Author(s):  
Guang Tian ◽  
Hao Tian ◽  
Guang Sheng Liu ◽  
Jin Hui Zhao ◽  
Li Ping Luo
Keyword(s):  
Fault Diagnosis ◽  
Rough Sets ◽  
Wavelet Packet ◽  
Decision Rules ◽  
Vibration Signals ◽  
Rough Sets Theory ◽  
Equal Angle ◽  
Order Tracking ◽  
Start Up ◽  
Sets Theory

The diagnosis of compound-fault is always a difficult point, and there is not an effective method in equipment diagnosis field, then a new method of compound-fault diagnosis was presented. The vibration signals at start-up in the gearbox are non-stationary signals, and traditional ways of diagnosis have low precision. Order tracking and wavelet packet and rough sets theory are introduced in the compound-fault diagnosis of bearing. First, the vibration signals at start-up were resampled using computer order tracking arithmetic and equal angle distributed vibration signals were obtained, and wavelet packet has been used for equal angle distributed vibration signals decomposition and reconstruction. Then, energy distribution of every frequency band can be calculated according to normalization process. A new feature vector can be obtained, then clear and concise decision rules can be obtained by rough sets theory. Finally, the result of compound-fault example proves that the proposed method has high validity and more amplitude appliance foreground.

Next-day peak electricity price forecasting using NN based on rough sets theory

2008 ◽  
Author(s):  
Hirofumi Toyama ◽  
Tomonobu Senjyu ◽  
Shantanu Chakraborty ◽  
Atsushi Yona ◽  
Toshihisa Funabashi ◽  
...  
Keyword(s):  
Rough Sets ◽  
Electricity Price ◽  
Price Forecasting ◽  
Rough Sets Theory ◽  
Electricity Price Forecasting ◽  
Sets Theory
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