The Experts below are selected from a list of 15243 Experts worldwide ranked by ideXlab platform
Irem Y. Tumer - One of the best experts on this subject based on the ideXlab platform.
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A Comparison of Functional Models for Use in the Function-Failure Design Method
2006Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar Functionality. To capitalize on this finding, a knowledge base of historical failure information linked to Functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s Functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should Functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed Functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized Functional and failure mode vocabularies are used. Two separate Function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed Functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed Functional models.
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Going Back in Time to Improve Design: The Elemental Function-Failure Design Method
Volume 3b: 15th International Conference on Design Theory and Methodology, 2003Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:In today’s world it is more important than ever to quickly and accurately satisfy customer needs when launching a new product. It is equally important to design products that adequately accomplish their desired Functions with a minimum amount of failures. When failure analysis and prevention are coupled with a product design from its conception, shorter design times and fewer redesigns are necessary to arrive at a final product design. In this article, we explore the potential of a novel design methodology to guide designers toward new designs or redesigns that avoid failures. The Elemental Function-Failure Design Method (EFDM) is based on Functional similarity of the product being designed to failed products within a knowledge base. The idea of using component Functionality to explore the failure space in design was first introduced as a Function-failure analysis approach by Tumer and Stone (2003). The overall approach offers potential improvement over current failure analysis methods (FMEA, etc.), because it can be implemented hand in hand with other conceptual design steps and carried throughout a product’s design cycle. In this paper, this idea is formalized into a systematic methodology that is specifically tailored for use at the conceptual design stage before any physical design choices have been made, hence moving failure analysis earlier in the design cycle. In the following, formalized guidelines for using the EFDM will be outlined for use in new designs and for redesign in existing products. A Function-failure knowledge base, derived from actual failure occurrences for Bell 206 rotorcraft will be introduced and used to derive potential failure modes in a comparison of the EFDM and traditional FMEA for two design examples. This comparison will demonstrate the EFDM’s potential in conceptual design failure analysis.Copyright © 2003 by ASME
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Comparing Two Levels of Functional Detail for Mapping Historical Failures: You Are Only as Good as Your Knowledge Base
Design Engineering Volumes 1 and 2, 2003Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer’s needs. Prior work indicates that similar failure modes occur within products (or components) with similar Functionality. To capitalize on this finding, a knowledge base of historical failure information linked to Functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool is implemented during conceptual design and keeps the designer congnizant of failures that are likely to occur based on the product’s Functionality. EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product’s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using EFDM is: At what level of detail should Functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed Functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized Functional and failure mode vocabularies are used. Two separate Function-failure knowledge bases are then created and compared. Results indicate that encoding failure data using more detailed Functional models allows for a more robust knowledge base. Interestingly however, when applying EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed Functional models.Copyright © 2003 by ASME
Michael E. Stock - One of the best experts on this subject based on the ideXlab platform.
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A Comparison of Functional Models for Use in the Function-Failure Design Method
2006Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar Functionality. To capitalize on this finding, a knowledge base of historical failure information linked to Functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s Functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should Functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed Functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized Functional and failure mode vocabularies are used. Two separate Function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed Functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed Functional models.
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Going Back in Time to Improve Design: The Elemental Function-Failure Design Method
Volume 3b: 15th International Conference on Design Theory and Methodology, 2003Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:In today’s world it is more important than ever to quickly and accurately satisfy customer needs when launching a new product. It is equally important to design products that adequately accomplish their desired Functions with a minimum amount of failures. When failure analysis and prevention are coupled with a product design from its conception, shorter design times and fewer redesigns are necessary to arrive at a final product design. In this article, we explore the potential of a novel design methodology to guide designers toward new designs or redesigns that avoid failures. The Elemental Function-Failure Design Method (EFDM) is based on Functional similarity of the product being designed to failed products within a knowledge base. The idea of using component Functionality to explore the failure space in design was first introduced as a Function-failure analysis approach by Tumer and Stone (2003). The overall approach offers potential improvement over current failure analysis methods (FMEA, etc.), because it can be implemented hand in hand with other conceptual design steps and carried throughout a product’s design cycle. In this paper, this idea is formalized into a systematic methodology that is specifically tailored for use at the conceptual design stage before any physical design choices have been made, hence moving failure analysis earlier in the design cycle. In the following, formalized guidelines for using the EFDM will be outlined for use in new designs and for redesign in existing products. A Function-failure knowledge base, derived from actual failure occurrences for Bell 206 rotorcraft will be introduced and used to derive potential failure modes in a comparison of the EFDM and traditional FMEA for two design examples. This comparison will demonstrate the EFDM’s potential in conceptual design failure analysis.Copyright © 2003 by ASME
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Comparing Two Levels of Functional Detail for Mapping Historical Failures: You Are Only as Good as Your Knowledge Base
Design Engineering Volumes 1 and 2, 2003Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer’s needs. Prior work indicates that similar failure modes occur within products (or components) with similar Functionality. To capitalize on this finding, a knowledge base of historical failure information linked to Functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool is implemented during conceptual design and keeps the designer congnizant of failures that are likely to occur based on the product’s Functionality. EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product’s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using EFDM is: At what level of detail should Functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed Functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized Functional and failure mode vocabularies are used. Two separate Function-failure knowledge bases are then created and compared. Results indicate that encoding failure data using more detailed Functional models allows for a more robust knowledge base. Interestingly however, when applying EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed Functional models.Copyright © 2003 by ASME
Robert Stone - One of the best experts on this subject based on the ideXlab platform.
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A Comparison of Functional Models for Use in the Function-Failure Design Method
2006Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar Functionality. To capitalize on this finding, a knowledge base of historical failure information linked to Functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s Functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should Functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed Functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized Functional and failure mode vocabularies are used. Two separate Function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed Functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed Functional models.
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Going Back in Time to Improve Design: The Elemental Function-Failure Design Method
Volume 3b: 15th International Conference on Design Theory and Methodology, 2003Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:In today’s world it is more important than ever to quickly and accurately satisfy customer needs when launching a new product. It is equally important to design products that adequately accomplish their desired Functions with a minimum amount of failures. When failure analysis and prevention are coupled with a product design from its conception, shorter design times and fewer redesigns are necessary to arrive at a final product design. In this article, we explore the potential of a novel design methodology to guide designers toward new designs or redesigns that avoid failures. The Elemental Function-Failure Design Method (EFDM) is based on Functional similarity of the product being designed to failed products within a knowledge base. The idea of using component Functionality to explore the failure space in design was first introduced as a Function-failure analysis approach by Tumer and Stone (2003). The overall approach offers potential improvement over current failure analysis methods (FMEA, etc.), because it can be implemented hand in hand with other conceptual design steps and carried throughout a product’s design cycle. In this paper, this idea is formalized into a systematic methodology that is specifically tailored for use at the conceptual design stage before any physical design choices have been made, hence moving failure analysis earlier in the design cycle. In the following, formalized guidelines for using the EFDM will be outlined for use in new designs and for redesign in existing products. A Function-failure knowledge base, derived from actual failure occurrences for Bell 206 rotorcraft will be introduced and used to derive potential failure modes in a comparison of the EFDM and traditional FMEA for two design examples. This comparison will demonstrate the EFDM’s potential in conceptual design failure analysis.Copyright © 2003 by ASME
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Comparing Two Levels of Functional Detail for Mapping Historical Failures: You Are Only as Good as Your Knowledge Base
Design Engineering Volumes 1 and 2, 2003Co-Authors: Michael E. Stock, Robert Stone, Irem Y. TumerAbstract:When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer’s needs. Prior work indicates that similar failure modes occur within products (or components) with similar Functionality. To capitalize on this finding, a knowledge base of historical failure information linked to Functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool is implemented during conceptual design and keeps the designer congnizant of failures that are likely to occur based on the product’s Functionality. EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product’s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using EFDM is: At what level of detail should Functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed Functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized Functional and failure mode vocabularies are used. Two separate Function-failure knowledge bases are then created and compared. Results indicate that encoding failure data using more detailed Functional models allows for a more robust knowledge base. Interestingly however, when applying EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed Functional models.Copyright © 2003 by ASME
Zhan Ke-jie - One of the best experts on this subject based on the ideXlab platform.
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Space-time Pattern and Driving Mechanism of Desertification Land Reversion in Arid Area
Journal of Desert Research, 2004Co-Authors: Zhan Ke-jieAbstract:The 160 mm precipitation is the threshold for desertification land reversion and vegetation recover under no irrigation in arid area, and the method is the key of successes. Practice for desertification land reversion in south fringe of Tengger Desert proved that the integrated countermeasures of desertification land enclosure compounded with artificial assistant methods at windward region could fix mobile sand dune by making use of Elemental Function; finally reach the purpose of increasing vegetation coverage and reversing desertified land. In the succession of vegetation community in test region for 20 years there were a series of changes from simple to complicated, which incarnated on the number, type, density, space pattern of species and so on.
Bin Wang - One of the best experts on this subject based on the ideXlab platform.
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Key Elemental Function Identification Based on Function-Failure Knowledge
Applied Mechanics and Materials, 2011Co-Authors: Mei Qing Wang, Bin WangAbstract:Functional modeling is the key step in product design process. To improve the quality of Functional modeling, an identification method of key Elemental Function based on Function-failure knowledge was proposed. A Function-failure knowledge model for mechanical product was built, which consists of Function-failure mode, relationships among failure modes, and failure risk information. By means of the Function-failure repository, the approach to calculate risk number (RN) of the Elemental Function was presented, in which the relationships among failure modes were considered. Then the key Elemental Functions were identified by the RN value. Finally, a case was studied to illustrate the proposed method.