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.

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.

A System Approach to Simulation-Based Design Under Uncertainty, Through Best in Class Simulation Process Integration and Design Optimization

2004 ◽  
Author(s):  
Nick Tzannetakis ◽  
Stijn Donders ◽  
Joost Van de Peer ◽  
Paul Weal
Keyword(s):  
Six Sigma ◽  
Process Integration ◽  
Real Life ◽  
Product Development Process ◽  
Design Parameters ◽  
Manufacturing Companies ◽  
Development Costs ◽  
Simulation Based Design ◽  
Key Factor ◽  
Reliability And Robustness

The importance of design robustness and reliability is a well-established notion and practice in today’s industry. Manufacturing companies strive to achieve Six-Sigma quality measures. While Virtual Prototyping is a key-factor in accelerating the product development process while reducing development costs, it has not contributed in the quest for improved product reliability and robustness performance since it is based on deterministic approaches. This paper provides a systematic approach to design for six-sigma simultaneously addressing variability and uncertainty present in real life on most design parameters. An example from the automotive industry illustrates the methodologies.

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.

Case-based reasoning for complexity management in Industry 4.0

2020 ◽  
Vol 31 (5) ◽  
pp. 999-1021
Author(s):  
Peter Schott ◽  
Matthias Lederer ◽  
Isabella Eigner ◽  
Freimut Bodendorf
Keyword(s):  
Knowledge Transfer ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Optimization ◽  
Case Based Reasoning ◽  
Manufacturing Companies ◽  
Content Type ◽  
Complexity Management ◽  
Managing Complexity ◽  
Case Based

PurposeIncreasingly, dynamic market environments lead to growing complexity in manufacturing and pose a severe threat for the competitiveness of manufacturing companies. Systematic guidance to manage this complexity, especially in the context of Industry 4.0 and the therewith rising trends such as digitalization and data-driven production optimization, is lacking. To address this deficit a case-based reasoning (CBR) system for providing knowledge about managing complexity in Industry 4.0 is presented.Design/methodology/approachFirst, the explicit knowledge representation for managing complexity in IT-based manufacturing is introduced. Second, the CBR process step to retrieve knowledge from an artificially composed case base with in total 70 cases of data-based complexity management in the context of Industry 4.0 is set out. Third, knowledge transfer alongside several maturity levels of information technology capabilities of manufacturing systems for reuse in new problem scenarios is introduced.FindingsThe paper comprises the conceptual approach for designing a CBR system to support data-based complexity management in manufacturing systems. Furthermore, the appropriateness of the CBR system to provide applicable knowledge for reducing and managing complexity in corporate practice is shown.Research limitations/implicationsThe presented research results are evaluated in the course of an embedded single case study and may therefore lack generalizability. Future research to test and enhance the appropriateness of the developed CBR system will strengthen the research contribution.Originality/valueThe paper provides a novel approach to systematically support knowledge transfer for data-based complexity management by transferring the well-known and established methodology of CBR to the rising application domain of manufacturing systems in the context of Industry 4.0.

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