Extension Case-Based Reasoning for Product Configuration Design

2009 ◽  
Vol 69-70 ◽  
pp. 616-620 ◽  
Author(s):  
Yan Wei Zhao ◽  
F. Zhang ◽  
M.Y. Zhang ◽  
Jian Chen ◽  
N. Su
Keyword(s):  
Solution Space ◽  
Product Configuration ◽  
Configuration Design ◽  
Prototype System ◽  
Case Based Reasoning ◽  
Final Configuration ◽  
Similarity Calculation ◽  
Overall Evaluation ◽  
Configuration Scheme ◽  
Case Based

The interface was regarded as standard and not considered in traditional configuration design, which made it difficult to apply to the existence product configuration. The paper proposes an extension case-based reasoning for product configuration design. With matter-elements, reasoning model of Extension Case-Based Reasoning (ECBR) is established, and its corresponding algorithm is proposed. During the configuration design, the solution space of configuration schemes is obtained by the similarity calculation, and then the overall evaluation of similarity and compatible degrees is adopted to form the final configuration scheme. A prototype system of reducer configuration design is successfully developed according to the method, and it proves the proposed method that is feasible and effective.

Product Configuration Knowledge Modeling Using Extend Object Model

2009 ◽  
Vol 16-19 ◽  
pp. 394-398
Author(s):  
Zhi Wei Xu ◽  
Zhong Qi Sheng ◽  
Hua Long Xie
Keyword(s):  
Product Configuration ◽  
Design System ◽  
Configuration Model ◽  
Configuration Design ◽  
Case Based Reasoning ◽  
Object Model ◽  
Case Representation ◽  
Extended Object ◽  
Extended Object Model ◽  
Case Based

This paper presents an extended object model for case-based reasoning in product configuration design. In the extended object model a few of methods of knowledge expression are adopted such as constraints, rules, objects etc. On the basis of extended object model, case representation model for case-based reasoning is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of case-based reasoning in product configuration design such as case representation, indexing, retrieving and case revising. The model extends traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, solution class used in case revise. So the product configuration knowledge that used in the product configuration design can be represented by using this model. In the end a Metering pump product configuration design systems is developed on the basis of the proposed product configuration model to support customized products.

Research on the Technique of Product Configuration in PDM

2007 ◽  
Vol 10-12 ◽  
pp. 132-139
Author(s):  
Lin Lin ◽  
Guo Lei Wang ◽  
S.S. Zhong
Keyword(s):  
Design Process ◽  
Nearest Neighbor ◽  
Theory Model ◽  
Product Data Management ◽  
Product Configuration ◽  
Case Based Reasoning ◽  
Modeling Technology ◽  
Configuration Scheme ◽  
Generator Design ◽  
Case Based

The technology of product configuration in a Product Data Management (PDM) system was discussed in this paper. The paper presented the product configuration modeling technology by based on the ‘and/or’ tree of product configuration, the process relation and coupling relation between components, and then, a general model of the product configuration scheme was proposed. The product configuration algorithm based on the product configuration scheme was also introduced and the feasibility from the theory model to the program was proved. The paper also discussed the application of Case-Based Reasoning(CBR) technology in product configuration, and, the emphasis was given towards the similar component search by the Nearest Neighbor(N-N) method. Finally, the product configuration technology was implemented on hydro-generator design process, and the result indicated this technology was valuable to realize intelligentization and automation of product configuration.

Case Representation and Organization Studies on Case-Based Reasoning Maintenance Resources Requirement Analysis

2013 ◽  
Vol 389 ◽  
pp. 698-702
Author(s):  
Xiao Chen ◽  
Ling Chen ◽  
Wo Ye Liu ◽  
Fei Han
Keyword(s):  
Prototype System ◽  
Case Based Reasoning ◽  
Requirement Analysis ◽  
Organization Studies ◽  
Case Representation ◽  
Relation Database ◽  
Analysis Process ◽  
System Perfection ◽  
Analysis System ◽  
Case Based

To improve the efficiency of planning maintenance resources requirement, the artificial intelligent (AI) technology, especially Case-Based Reasoning (CBR) is applied into maintenance resources requirement analysis process, the process is introduced, and the critical techniques of which, such as case representation and organization etc, are discussed in detail, according to the case characteristics, analyzed the cases main ingredient, cases representation and organization which is based on Relation Database and Object Oriented are detailed discussed, the development of case-based maintenance resources requirement analysis prototype system proved the validity of the technique, formed the foundation for the case-based maintenance resources requirement analysis system perfection.

Classification Algorithm of Case Retrieval Based on Granularity Calculation of Quotient Space

2020 ◽  
pp. 2150003
Author(s):  
Jiaxing Lu ◽  
Jiang Qing ◽  
Huang He ◽  
Zhang Zhengyong ◽  
Wang Rujing
Keyword(s):  
Quotient Space ◽  
Inner Product ◽  
Retrieval Algorithm ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Current Case ◽  
Quotient Spaces ◽  
Similarity Calculation ◽  
Key Steps ◽  
Case Based

Case retrieval is one of the key steps of case-based reasoning. The quality of case retrieval determines the effectiveness of the system. The common similarity calculation methods based on attributes include distance and inner product. Different similarity calculations have different influences on the effect of case retrieval. How to combine different similarity calculation results to get a more widely used and better retrieval algorithm is a hot issue in the current case-based reasoning research. In this paper, the granularity of quotient space is introduced into the similarity calculation based on attribute, and a case retrieval algorithm based on granularity synthesis theory is proposed. This method first uses similarity calculation of different attributes to get different results of case retrieval, and considers that these classification results constitute different quotient spaces, and then organizes these quotient spaces according to granularity synthesis theory to get the classification results of case retrieval. The experimental results verify the validity and correctness of this method and the application potential of granularity calculation of quotient space in case-based reasoning.

scholarly journals Demand Prediction of Railway Emergency Resources Based on Case-Based Reasoning

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jianping Sun ◽  
Hantao Cao ◽  
Biao Geng ◽  
Zhaoping Tang ◽  
Xiaopeng Li
Keyword(s):  
Nearest Neighbor ◽  
Structural Similarity ◽  
Empirical Method ◽  
Case Based Reasoning ◽  
Local Similarity ◽  
Demand Prediction ◽  
Railway Traffic ◽  
Proposed Model ◽  
Similarity Calculation ◽  
Case Based

The demand prediction of emergency resources is helpful for rational allocation and optimization of emergency resources for railway rescue when emergency incident occurs. In this paper, a case base containing China railway traffic accident that has occurred since 1978 is established, and the case-based reasoning (CBR) method is applied in railway emergency resource demand predicting research. The core case attributes of railway emergencies are described. In view of the attribute types of railway emergency cases, five types of attributes, including enumeration, numerical, interval, character and fuzzy type, are considered, and the local similarity calculation models of different attributes are given. In order to avoid the problem of missing attribute in the traditional nearest neighbor algorithm, a global case similarity calculation method based on structural similarity and attribute similarity is designed. The empirical results show that case 3 is the most similar to the target case, and the calculating quantities of the proposed model are closer to the actual usage quantity and more accurate in the demand prediction of railway emergency resources, compared with the traditional empirical method. The relative errors of demand forecasts for the 9 resources have been, respectively, reduced by 15.9884%, 15.1471%, 6.4286%, 17.1429%, 66.6667%, 38.8889%, 27.5%, 0%, and 17.7778%. Therefore, the proposed model is both reasonable and applicable. The research results are of great significance to effectively deal with railway emergencies.

Combining Case Based Reasoning and Shape Matching Based on Clearance Analyzes to Support the Reuse of Components

2012 ◽  
Author(s):  
Joel Johansson
Keyword(s):  
Process Design ◽  
Lead Time ◽  
Shape Matching ◽  
Product Development Process ◽  
Prototype System ◽  
Case Based Reasoning ◽  
Manufacturing Companies ◽  
Key Factor ◽  
Product Specifications ◽  
Case Based

For manufacturing companies it is important to develop and produce products that meet requirements from customers and investors. One key factor in meeting these requirements is the efficiency of the product development process. Design automation is a powerful tool to increase efficiency in that process resulting in shortened lead-time, improved product performance, and ultimately decreased cost. Further, automation is beneficial as it increases the ability to adapt products to new product specifications, which is critical to some categories of products. In this paper the retrieval and evaluation processes of the Case Based Reasoning (CBR) method are extended to include shape matching. This enhanced CBR method supports the reuse of existing components when introducing new variants of variant-rich products. The matching method is based on clearance analyzes and is performed during the retrieval of cases and supports the evaluation of suggestions. The method is described along with a prototype-system where the process of selecting components for roof racks for cars is targeted for automation. One specific component of the roof rack is targeted, namely a rubber pad used in the interface between the car roof and the rack.

COMPOSER: A case-based reasoning system for engineering design

Robotica ◽  
1998 ◽  
Vol 16 (3) ◽  
pp. 285-295 ◽  
Author(s):  
Lisa Purvis ◽  
Pearl Pu
Keyword(s):  
Engineering Design ◽  
Configuration Design ◽  
Case Based Reasoning ◽  
Assembly Sequence ◽  
Reasoning System ◽  
Frequent Use ◽  
Wide Range ◽  
Many Sources ◽  
Combine Information ◽  
Case Based

The frequent use of past experience by human engineers when solving new problems has led to an interest in the use of case based reasoning (CBR) to help automate engineering design. In engineering design it often occurs that many past exp eriences must be combined to solve a new problem, and thus the process of case based adaptation must efficiently and systematically combine information from many sources. We have developed a constraint based methodology for case combination that allows its application across a wide range of problems. We have shown that our approach provides an efficient adaptation methodology that ensures convergence upon a solution if one exists, provides a uniform representation of cases, and is generalizable beyond just one domain. Our technique is implemented in a case based reasoning system called COMPOSER, which ha s been tested in two design domains: assembly sequence design and configuration design.

CASE-BASED REASONING FOR KNOWLEDGE ACQUISITION SUGGESTIONS

1994 ◽  
Vol 03 (01) ◽  
pp. 23-45
Author(s):  
LEE BECKER ◽  
TODD GUAY
Keyword(s):  
Decision Tree ◽  
Knowledge Acquisition ◽  
Decision Trees ◽  
Current Knowledge ◽  
General Mechanism ◽  
Prototype System ◽  
Case Based Reasoning ◽  
Acquisition Session ◽  
Specific Kind ◽  
Case Based

Case-based suggestion (CBS) is a general mechanism for system-driven interactive knowledge acquisition. CBS applies case-based reasoning to the task of knowledge acquisition. It utilizes previously acquired knowledge embodied in cases to assist the expert during the current knowledge acquisition session. In this work we describe the general CBS technique and illustrate its use during the acquisition of a specific kind of knowledge. A system utilizing CBS was implemented in the acquisition module of a prototype system called ODS, which structures acquired diagnostic knowledge in decision trees. The algorithm used for case-based suggestion by the ODS system and a description of how the decision tree knowledge was represented in the case base is presented. Several evaluation metrics are introduced, and the application of these measures to several experiences of acquiring knowledge with ODS is discussed.

Sign in / Sign up

Export Citation Format

Share Document