A Blackboard Architecture to Support Case-Based Reasoning in Mechanical Design

1992 ◽  
Author(s):  
Theodore Bardsz ◽  
Ibrahim Zeid
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Mechanical Design ◽  
Maximum Amount ◽  
Design Solution ◽  
Case Based Reasoning ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Design Plan ◽  
Case Based

Abstract One of the most significant issues in applying case-based reasoning (CBR) to mechanical design is to integrate previously unrelated design plans towards the solution of a new design problem. The total design solution (the design plan structure) can be composed of both retrieved and dynamically generated design plans. The retrieved design plans must be mapped to fit the new design context, and the entire design plan structure must be evaluated. An architecture utilizing opportunistic problem solving in a blackboard environment is used to map and evaluate the design plan structure effectively and successfuly. The architecture has several assets when integrated into a CBR environment. First, the maximum amount of information related to the design is generated before any of the mapping problems are addressed. Second, mapping is preformed as just another action toward the evaluation of the design plan. Lastly, the architecture supports the inclusion of memory elements from the knowledge base in the design plan structure. The architecture is implemented using the GBB system. The architecture is part of a newly developed CBR System called DEJAVU. The paper describes DEJAVU and the architecture. An example is also included to illustrate the use of DEJAVU to solve engineering design problems.

A study in applying case-based reasoning to engineering design: Mechanical bearing design

2003 ◽  
Vol 17 (3) ◽  
pp. 235-252 ◽  
Author(s):  
XIAOLI QIN ◽  
WILLIAM C. REGLI
Keyword(s):  
Engineering Design ◽  
Constraint Satisfaction ◽  
Engineering Problem ◽  
Problem Definition ◽  
Case Based Reasoning ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Previous Design ◽  
Bearing Design ◽  
Case Based

Case-based reasoning (CBR) is a promising methodology for solving many complex engineering design problems. CBR employs past problem-solving experiences when solving new problems. This paper presents a case study of how to apply CBR to a specific engineering problem: mechanical bearing design. A system is developed that retrieves previous design cases from a case repository and uses adaptation techniques to modify them to satisfy the current problem requirements. The approach combines both parametric and constraint satisfaction adaptations. Parametric adaptation considers not only parameter substitution but also the interrelationships between the problem definition and its solution. Constraint satisfaction provides a method to globally check the design requirements to assess case adaptability. Currently, our system has been implemented and tested in the domain of rolling bearings. This work serves as a template for application of CBR techniques to realistic engineering problems.

scholarly journals Performance Comparison of Recent Population-Based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 341
Author(s):  
Bugra Alkan ◽  
Malarvizhi Kaniappan Chinnathai
Keyword(s):  
Engineering Design ◽  
Mechanical Design ◽  
Search Algorithm ◽  
Computation Time ◽  
Population Based ◽  
Performance Comparison ◽  
Design Problems ◽  
Component Design ◽  
Engineering Design Problems ◽  
Optimisation Algorithms

The optimisation of complex engineering design problems is highly challenging due to the consideration of various design variables. To obtain acceptable near-optimal solutions within reasonable computation time, metaheuristics can be employed for such problems. However, a plethora of novel metaheuristic algorithms are developed and constantly improved and hence it is important to evaluate the applicability of the novel optimisation strategies and compare their performance using real-world engineering design problems. Therefore, in this paper, eight recent population-based metaheuristic optimisation algorithms—African Vultures Optimisation Algorithm (AVOA), Crystal Structure Algorithm (CryStAl), Human-Behaviour Based Optimisation (HBBO), Gradient-Based Optimiser (GBO), Gorilla Troops Optimiser (GTO), Runge–Kutta optimiser (RUN), Social Network Search (SNS) and Sparrow Search Algorithm (SSA)—are applied to five different mechanical component design problems and their performance on such problems are compared. The results show that the SNS algorithm is consistent, robust and provides better quality solutions at a relatively fast computation time for the considered design problems. GTO and GBO also show comparable performance across the considered problems and AVOA is the most efficient in terms of computation time.

Cultivating Students’ Ability of Applying Knowledge in Engineering Design Through Course Project

2011 ◽  
Author(s):  
Jining Qiu ◽  
Bo Zhang ◽  
Huimin Dong ◽  
Yuan Gao
Keyword(s):  
Engineering Design ◽  
Engineering Students ◽  
Mechanical Design ◽  
Gear Train ◽  
Design Problems ◽  
Academic Knowledge ◽  
Multi Stage ◽  
University Of Technology ◽  
Engineering Design Problems ◽  
Wind Power Generator

The ability to solve engineering design problems using academic knowledge flexibly is essential for mechanical engineering students and is also quality that employers look for. This paper introduces how students could explore and experience the process of mechanical design in the course project of Theory of Machines and Mechanisms (TMM) in Dalian University of Technology (DUT) through sharing the design process of accelerator (gear-box) in wind power generator by one representative team of students in the course project. Firstly, design requirements are set based on industrial need and the choosing of the best scheme of multi-stage gear train is conducted. Following that is the design of kinematic parameters of gears and the evaluation of selected system. Then, a possible solution to control the input speed of the generator is proposed. In the end, a survey to 279 students who participate in the course project shows the importance of course project in cultivating their ability to apply knowledge in design.

DEJAVU: Case-based reasoning for mechanical design

1993 ◽  
Vol 7 (2) ◽  
pp. 111-124 ◽  
Author(s):  
Theodore Bardasz ◽  
Ibrahim Zeid
Keyword(s):  
Mechanical Design ◽  
Design Knowledge ◽  
Case Based Reasoning ◽  
Design Environment ◽  
Design Problems ◽  
Evaluation Module ◽  
Main Components ◽  
Domain Independent ◽  
Synergistic Relationship ◽  
Case Based

The architecture and implementation of a mechanical designer's assistant shell called DEJAVU is presented. The architecture is based on an integration of design and CAD with some of the more well known concepts in case-based reasoning (CBR). DEJAVU provides a flexible and cognitively intuitive approach for acquiring and utilizing design knowledge. It is a domain independent mechanical design shell that can incrementally acquire design knowledge in the domain of the user. DEJAVU provides a design environment that can learn from the designer(s) until it can begin to perform design tasks autonomously or semi-autonomously. The main components of DEJAVU are a knowledge base of design plans, an evaluation module in the form of a design plan system, and a blackboard-based adaptation module. The existance of these components are derived from the utilization of a CBR architecture. DEJAVU is the first step in developing a robust designer's assistant shell for mechanical design problems. One of the major contributions of DEJAVU is the development of a clean architecture for the utilization of case-based reasoning in a mechanical designer's assistant shell. In addition, the components of the architecture have been developed, tailored or modified from a general CBR context into a more synergistic relationship with mechanical design.

GPS: Engineering Design Problems Promote Problem Solving

2021 ◽  
Vol 114 (2) ◽  
pp. 154-158
Author(s):  
Cathrine Maiorca
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
School Mathematics ◽  
Mathematical Tasks ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Problem Solvers

Growing Problem Solvers provides four original, related, classroom-ready mathematical tasks, one for each grade band. Together, these tasks illustrate the trajectory of learners’ growth as problem solvers across their years of school mathematics.

A design-plan-oriented methodology for applying case-based adaptation to engineering design

1998 ◽  
Vol 12 (5) ◽  
pp. 463-478 ◽  
Author(s):  
TALAL AL-SHIHABI ◽  
IBRAHIM ZEID
Keyword(s):  
Engineering Design ◽  
Design Problem ◽  
Structural Engineering ◽  
Design System ◽  
Case Based Reasoning ◽  
Adaptation Process ◽  
Case Representation ◽  
Generic Framework ◽  
Design Plan ◽  
Case Based

Adaptation of design cases is usually the most challenging part in building any case-based reasoning design system. The success of the adaptation process in finding a solution for a new design problem determines the success of the entire case-based reasoning (CBR) system. The techniques used for generating design solutions have many common aspects among the various engineering design classes that make them amenable to be captured in a generic framework for an acceptable level of abstraction. This paper proposes a design-plan-oriented methodology for adapting design cases to produce a solution to a new design problem in the domain of engineering design. The proposed methodology uses multicase adaptation and case built-in adaptation knowledge to produce a design plan for a new design problem. We first define the model of case representation to work with the proposed methodology. We then define the overall structure of the procedural framework of this methodology and its subprocesses. The system is then demonstrated through an application from the structural engineering domain.

Applying Case-Based Reasoning to Mechanical Bearing Design

2000 ◽  
Author(s):  
Xiaoli Qin ◽  
William C. Regli
Keyword(s):  
Constraint Satisfaction ◽  
Rolling Bearing ◽  
Problem Definition ◽  
Design System ◽  
Case Based Reasoning ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Complex Engineering ◽  
Bearing Design ◽  
Case Based

Abstract Case-Based Reasoning (CBR) provides a promising methodology for solving many complex engineering design problems. CBR is based on the idea that past problem-solving experiences can be reused and learned from in solving new problems. This paper presents an overview of a CBR design system to assist human engineers in performing mechanical bearing design. It retrieves previously designed cases from a case-base and uses adaptation techniques to adapt them to satisfy the current problem requirements. Our approach combines parametric adaptations and constraint satisfaction adaptations. The technique of parametric adaptation considers not only parameter substitution, but also the interrelationships between the problem definition and its solution. The technique of constraint satisfaction adaptation provides a method to globally check the design requirements to assess case adaptability. Currently, our system has been tested in the rolling bearing domain.

Should Teams Collaborate During Conceptual Engineering Design? An Experimental Study

2018 ◽  
Author(s):  
Joshua T. Gyory ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Conceptual Design ◽  
Engineering Students ◽  
Individual Performance ◽  
Design Problems ◽  
Group Problem Solving ◽  
Conceptual Engineering ◽  
Engineering Design Problems ◽  
Working Together

A commonly held presumption is that the production of a team is superior to that of individual performance. However, in certain scenarios, such as during brainstorming activities and in configuration engineering design problems, it has been shown that individuals working alone are more effective than teams working together. This research considers whether the same outcomes hold for a more open-ended scenario, in conceptual engineering design. Thus, a behavioral study is run with freshman engineering students solving a conceptual design problem working in teams or individually. Results corroborate previous findings, showing that individuals outperform teams in the quality of their design solutions. One of the primary differences between individuals and group problem solving is the fact that groups need to verbalize to communicate ideas. Consequently, this study also analyzes how verbalization, which may be one disadvantage of team problem solving, affects the performance of individuals in this context of conceptual engineering design. Individuals who verbalize throughout problem solving, however, perform similarly to those who did not. Overall, the results from this study suggest that, individuals are still better performers and teams may not always be the optimal circumstance. Moreover, verbalization does not seem to act as a cognitive barrier to problem solving, and further investigation needs to be done to diagnose the potential impediments which put teams at a disadvantage to individuals during conceptual design.

A Flexible Optimization Procedure for Mechanical Component Design Based on Genetic Adaptive Search

1998 ◽  
Vol 120 (2) ◽  
pp. 162-164 ◽  
Author(s):  
K. Deb ◽  
M. Goyal
Keyword(s):  
Engineering Design ◽  
Optimization Problems ◽  
Mechanical Design ◽  
Optimization Procedure ◽  
Continuous Variables ◽  
Design Problems ◽  
Component Design ◽  
Engineering Design Problems ◽  
Complex Engineering ◽  
Optimum Solution

A flexible algorithm for solving nonlinear engineering design optimization problems involving zero-one, discrete, and continuous variables is presented. The algorithm restricts its search only to the permissible values of the variables, thereby reducing the search effort in converging near the optimum solution. The efficiency and ease of application of the proposed method is demonstrated by solving four different mechanical design problems chosen from the optimization literature. These results are encouraging and suggest the use of the technique to other more complex engineering design problems.

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