Qualitative Evaluation of Engineering Designs Using Fuzzy Logic

1996 ◽  
Author(s):  
Rajkumar Roy ◽  
Ian C. Parmee ◽  
Graham Purchase
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Engineering Design ◽  
Evaluation System ◽  
Design Space ◽  
Qualitative Evaluation ◽  
Fuzzy Rules ◽  
Design Solution ◽  
Fuzzy Expert System ◽  
Adaptive Search

Abstract The paper describes a Qualitative Evaluation System developed using a fuzzy expert system. The evaluation system gives a qualitative rating to design solutions by considering manufacturability aspects, choice of materials and some special preferences. The information is used in decision support for engineering design. The system is an integrated part of a decision support tool for engineering design called the ‘Adaptive Search Manager’ (ASM). ASM uses an adaptive search technique to identify multiple design solutions for a 12 dimensional Turbine Blade Cooling System design problem. Thus the task has been to develop a fuzzy expert system that can qualitatively evaluate any design solution from a design space using a realistically small number of fuzzy rules. The developed system utilises a knowledge separation and then a knowledge integration technique. The design knowledge is first separated into three categories: inter variable knowledge, intra variable knowledge and heuristics. Inter variable knowledge and intra variable knowledge are integrated using a concept of “compromise”. The qualitative evaluation system can evaluate any design solution within the 12 dimensional design space, but uses only 44 fuzzy rules and one function that implements the inter variable knowledge.

scholarly journals Prediction of Rainfall Characteristics Based on Fuzzy Expert System

2020 ◽  
Vol 8 (5) ◽  
pp. 1125-1130
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Tamil Nadu ◽  
Weather Prediction ◽  
Research Work ◽  
Fuzzy Rules ◽  
Dew Point ◽  
Modern World ◽  
Fuzzy Expert System ◽  
Rainfall Prediction

Rainfall prediction is one of the most extremely important and trickiest job in the modern world because, Rain is the lifeblood of human survival, of life on our planet. Gorgeous beauty of fuzzy logic was described by various author for prediction in various field. In this work, fuzzy logic is applied in proposing a model to predict rainfall percentage with parameters. Fuzzy Expert System inputs(parameter) include the temperature, humidity, wind speed , Dew point etc., with Output as rainfall Percentage .Here we develop a new model as RPFES Model to predict rainfall percentage for particular geographical location of Tamil Nadu. There are four steps for developing RPFES Model : The first step is Fuzzification process by triangular membership function for representing the input variables and output variables. The next step is Fuzzy Inference with Fuzzy Rules the method applied in this research work are Root Sum Square (RSS). The Root Sum Square of drawing inference was employed to infer the data from the fuzzy rules developed and finally we move to Defuzzification process for getting Rainfall percentage by individually. From RPFES Model, Individual Person get the Rainfall Prediction as Percentage with purely by Fuzzy Logic and not by Metrological Center. Weather Prediction is the major essential and challenging operational responsibilities which are carried out by meteorological services all over the world.

A FUZZY EXPERT SYSTEM FOR SOLVING REAL-OPTION DECISION PROCESSES

2001 ◽  
Vol 06 (02) ◽  
Author(s):  
C.A Magni ◽  
G. Mastroleo ◽  
G. Facchinetti
Keyword(s):  
Expert System ◽  
Real Option ◽  
Decision Processes ◽  
Fuzzy Expert System

Contribution to the Research and Development of Radiation Chambers in Steam Reforming. Problem-Oriented Application of a Fuzzy Expert System

1992 ◽  
Vol 57 (10) ◽  
pp. 2125-2134 ◽  
Author(s):  
Petr Stehlík ◽  
František Babinec
Keyword(s):  
Carbon Dioxide ◽  
Mathematical Model ◽  
Expert System ◽  
Service Life ◽  
Research And Development ◽  
Steam Reforming ◽  
Methane Conversion ◽  
Chemical Processes ◽  
Fuzzy Expert System ◽  
Present Contribution

An application of a fuzzy expert system intended for estimating some parameters of steam reforming can also be one of the examples of an ever increasing utilization of expert systems in practice. The present contribution deals with the method making use of a verified mathematical model for simulating thermal chemical processes in reforming furnace radiation chamber in order to create knowledge base. This base includes linguistic values of selected independent and dependent variable quantities. Examples given illustrate an evaluation of dependent variable quantities (methane conversion into carbon dioxide and monoxide, reaction tube service life) by means of the said expert system based on queries.

scholarly journals Knowledge Acquisition and Representation for High-Performance Building Design: A Review for Defining Requirements for Developing a Design Expert System

2021 ◽  
Vol 13 (9) ◽  
pp. 4640
Author(s):  
Seung-Yeoun Choi ◽  
Sean-Hay Kim
Keyword(s):  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Acquisition ◽  
Data Analytics ◽  
High Performance ◽  
Problem Definition ◽  
Design Expert ◽  
Decision Support Process ◽  
High Performance Building

New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach.

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