Relevant bibliographies by topics / Engineering design reasoning

Academic literature on the topic 'Engineering design reasoning'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Engineering design reasoning"

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Howard, H. Craig, Jenmu Wang, Francois Daube, and Taufiq Rafiq. "Applying design-dependent knowledge in structural engineering design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 3, no. 2 (May 1989): 111–23. http://dx.doi.org/10.1017/s0890060400001141.

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Recent knowledge-based expert systems for structural engineering design have focused on design-independent knowledge (abstract reasoning rules for designing), and while great strides have been made in that area, there is still a significant need to develop systems to take advantage of the wealth of knowledge contained in every substantial structural design. On the other hand, previous database-oriented design efforts have focused primarily on knowledge-poor databases of solutions, in which the traditional engineering handbook of solutions has simply been replaced by digital data. The challenge is to find a way to capture and apply the kind of case-based, design-dependent knowledge that structural engineers have traditionally used. The long-term results will be better structural designs and better structural designers. This paper discusses the character of the design-dependent knowledge in a structural engineering context, describes two initial applications of case-based reasoning to component design, and presents a general paradigm for a knowledge-based design system integrating rule-based and case-based reasoning.
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Mayes, Robert, Bryon Gallant, and Emma Fettes. "Interdisciplinary STEM through Engineering Design-based Reasoning." International Journal of Engineering Pedagogy (iJEP) 8, no. 3 (May 28, 2018): 60. http://dx.doi.org/10.3991/ijep.v8i3.8026.

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Interdisciplinary STEM programs are in demand for United States middle schools (ages 11 to 13 years) and high schools (ages 14 to 18). The Real STEM Project collaborated with 12 schools to develop and implement such programs. We open with a description of the project, including the 21st century STEM reasoning abilities that were proposed as learning outcomes for the STEM programs. We then focus on one of the five reasoning abilities, engineering design-based reasoning, since engineering often serves as a driver for STEM programs. An exemplar of engineering design as a driver for STEM from one of the participating teacher’s classrooms is provided, and a summary of teaching practices supporting interdisciplinary STEM is drawn from the example.
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Stéphane, Negny, and Le Lann Jean Marc. "Case-based reasoning for chemical engineering design." Chemical Engineering Research and Design 86, no. 6 (June 2008): 648–58. http://dx.doi.org/10.1016/j.cherd.2008.02.011.

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Kannapan, Srikanth M., and Kurt M. Marshek. "Design synthetic reasoning." Mechanism and Machine Theory 26, no. 7 (January 1991): 711–39. http://dx.doi.org/10.1016/0094-114x(91)90033-z.

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Howard, Thomas J., and Mogens Myrup Andreasen. "Mind-sets of functional reasoning in engineering design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 27, no. 3 (July 24, 2013): 233–40. http://dx.doi.org/10.1017/s0890060413000231.

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AbstractThe concept of a function is of great importance in design. This paper describes from theory how designers should reason about functions when designing. This paper introduces the link model, showing how functions and properties link the product and its use, to the perceived value of the product. The important and useful distinction between functions and properties is made along with the distinction between “wirk functions,” which is what the product does when operating, and “use functions,” which is what the product is used for. The paper makes a novel contribution beyond previous literature, showing that not only is a product's behavior or mode of action designed but also the use activity of the end user. Based on the theoretical perspective unfolded, the authors offer nine mind-sets for both design practitioners and researchers to consider when reasoning about functions.
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Nakatani, Yoshio, Makoto Tsukiyama, and Toyoo Fukuda. "Engineering design support framework by case-based reasoning." ISA Transactions 31, no. 2 (January 1992): 165–80. http://dx.doi.org/10.1016/0019-0578(92)90037-j.

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Sham, S. H. R. "Nonmonotonic Reasoning in Design." Journal of Computing in Civil Engineering 7, no. 1 (January 1993): 36–53. http://dx.doi.org/10.1061/(asce)0887-3801(1993)7:1(36).

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Shiva Kumar, H., and C. S. Krishnamoorthy. "A framework for case-based reasoning in engineering design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 9, no. 3 (June 1995): 161–82. http://dx.doi.org/10.1017/s0890060400002419.

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AbstractAlthough the case-based reasoning (CBR) process is domain dependent, certain aspects of it can readily be captured into a generic framework which in turn can be applied to various engineering domains. One such exercise that has been carried out is described here. In this paper, we present the notion that CBR can be formalized and applied in a specialized framework in an integrated knowledge-based environment. We first analyze the CBR process to abstract the steps involved in the development of a CBR system. We then propose a framework in which most of these steps are formalized so that they can be applied in a domain-independent manner. The salient features of this framework, called CASETOOL (CASE-based reasoning TOOL-kit), are then described. The highlight of this approach is the use of a concept called design criticism in the CBR process. The versatility of the tool is demonstrated through an application from the bridge engineering domain.
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Purvis, Lisa, and Pearl Pu. "COMPOSER: A case-based reasoning system for engineering design." Robotica 16, no. 3 (May 1998): 285–95. http://dx.doi.org/10.1017/s0263574798000368.

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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.
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QIN, XIAOLI, and WILLIAM C. REGLI. "A study in applying case-based reasoning to engineering design: Mechanical bearing design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 17, no. 3 (August 2003): 235–52. http://dx.doi.org/10.1017/s0890060403173064.

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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.
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Dissertations / Theses on the topic "Engineering design reasoning"

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Balazs, Marton E. "Design simplification by analogical reasoning." Link to electronic version, 1999. http://www.wpi.edu/Pubs/ETD/Available/etd-0209100-051108/.

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Hounsell, Marcelo da Silva. "Feature-based validation reasoning for intent-driven engineering design." Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/33152.

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Feature based modelling represents the future of CAD systems. However, operations such as modelling and editing can corrupt the validity of a feature-based model representation. Feature interactions are a consequence of feature operations and the existence of a number of features in the same model. Feature interaction affects not only the solid representation of the part, but also the functional intentions embedded within features. A technique is thus required to assess the integrity of a feature-based model from various perspectives, including the functional intentional one, and this technique must take into account the problems brought about by feature interactions and operations. The understanding, reasoning and resolution of invalid feature-based models requires an understanding of the feature interaction phenomena, as well as the characterisation of these functional intentions. A system capable of such assessment is called a feature-based representation validation system. This research studies feature interaction phenomena and feature-based designer's intents as a medium to achieve a feature-based representation validation system.
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Goel, Ashok Kumar. "Integration of case-based reasoning and model-based reasoning for adaptive design problem solving /." The Ohio State University, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487673114115037.

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Vinney, John Edward. "Function based techniques for assisting engineering conceptual design." Thesis, University of the West of England, Bristol, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387937.

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The basic concept of this work is that functional modelling techniques are applicable to and of practical use in, producing a qualitative model of conceptual engineering design. A qualitative function based model of conceptual design has been developed and a computer based implementation has been built and tested. The rationale behind the modelling scheme and the computer implementation are described in detail. In addition to a review of existing models of design the research provides a significant new capability in four main areas: • An ability to generate new concepts with a controlled degree of similarity to existing designs. • A new function based model of engineering conceptual design. • The COncept Design ASsistant (CODAS) system, a computer based implementation of the function based model, has been developed and tested. • A new symbolic representation language. CODAS is a hybrid case-based and function-based modelling system, implemented in the domain of mechanical device design, which demonstrates the practical application of this new model. The CODAS system aims to provide a design support tool which can invent both routine and novel devices based on experience gained from past successful design solutions. Fast and efficient data handling is achieved by utilizing Case Based Reasoning (CBR) technology to store and retrieve past design solutions which are defined in terms of a symbolic representation language. The underlying design model is function based and employs a technique of divergent function to form mapping to produce physical embodiments of the proposed functional solutions.
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Balazs, Marton E. "Design Simplification by Analogical Reasoning." Digital WPI, 2000. https://digitalcommons.wpi.edu/etd-dissertations/60.

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Ever since artifacts have been produced, improving them has been a common human activity. Improving an artifact refers to modifying it such that it will be either easier to produce, or easier to use, or easier to fix, or easier to maintain, and so on. In all of these cases, "easier" means fewer resources are required for those processes. While 'resources' is a general measure, which can ultimately be expressed by some measure of cost (such as time or money), we believe that at the core of many improvements is the notion of reduction of complexity, or in other words, simplification. This talk presents our research on performing design simplification using analogical reasoning. We first define the simplification problem as the problem of reducing the complexity of an artefact from a given point of view. We propose that a point of view from which the complexity of an artefact can be measured consists of a context, an aspect and a measure. Next, we describe an approach to solving simplification problems by goal-directed analogical reasoning, as our implementation of this approach. Finally, we present some experimental results obtained with the system. The research presented in this dissertation is significant as it focuses on the intersection of a number of important, active research areas - analogical reasoning, functional representation, functional reasoning, simplification, and the general area of AI in Design.
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Ma, Yuming. "Qualitative geometric reasoning for thermal design evaluation of die casting dies /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488203552780212.

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Wolmarans, Nicolette Sarah. "The nature of professional reasoning: An analysis of design in the engineering curriculum." Doctoral thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/25654.

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Access to the practice of a profession is controlled by formal education structures. These structures are intended to induct future professionals into the specialised knowledge, skills and values that underpin that profession. Yet, despite meeting the academic requirements of a professional degree, many graduates struggle to 'apply' specialised knowledge when confronted with problems in professional practice. This is a study of the nature of knowledge as it is mobilised in professional reasoning. The case studied was located in engineering education, because knowledge relations tend to be more explicit in education than in practice. The data were collected from design projects located in two differently structured curricula in civil and mechanical engineering curricula. The research questions that directed the study were: 1. What is the nature of the reasoning involved when specialised disciplinary knowledge is recruited to develop specific, often concrete, artefacts? 2. What is the logic of progression in a trajectory of engineering design tasks in terms of the relation between knowledge and artefact? The study draws on two intellectual fields: models of professional reasoning and design thinking on one hand, and social realism in the sociology of education on the other. These traditions take different positions on professional reasoning. Design thinking is concerned with contextual detail and case precedent, while social realism in the sociology of education is concerned with conceptual coherence within knowledge specialisations and the power of generalisation. Both offer important insights into professional reasoning, but alone neither is adequate. The analysis was done using the semantics dimension of Legitimation Code Theory, LCT (Semantics), which required an adaptation in order to fully describe the significance of contextual detail evident in the data. The findings showed that specialised knowledge and contextual detail interact far more dialectically than previously assumed. This provides empirical insights for structuring curricula. Students can be more intentionally inducted into recontextualising academic knowledge for the purpose of solving contextually emergent problems. Theoretically the study contributes to the social realist school within the sociology of education by revealing its blindness to contextual detail and consequently offering a fuller understanding of the nature of regions. This has implications for other studies of professional knowledge and education.
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Ouyang, Jun. "Case-based reasoning for the creative design of electromagnetic devices." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=107659.

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Design is concerned with the question of how to construct an artifact or system to meet the desired specification and is normally categorized as either routine, non-routine or creative. Up until now, the study of knowledge-based design has concentrated on routine or non-routine design. In order to explore creativity in design, a new computational model based on the combination of case based reasoning (an approach to solving new problems based on the solutions of similar past problems) and soft computing techniques (such as machine learning, data mining and optimization), is proposed in this thesis. The new model is able to deal with the four challenging issues related to creativity: generation of a design prototype from incomplete requirements, judgment and improvement of system performance given a sparse initial case base library, extraction of pivotal features from a given feature space, adaptation of retrieved previous solutions to similar problems for deriving a new innovative solution to a given design task. The core principle underlying this model is that different knowledge from various level cases can be explicitly explored and integrated into a practical design process.In addition, in order to demonstrate the practical significance of our proposed computational model, a design system for electromagnetic devices which is capable of deriving a new design prototype from a real-world device case base with high dimensionality has been developed.
La conception en général s'intéresse à savoir comment construire un objet ou un système à partir d'une spécification et est normalement classée soit comme routine, non-routine ou créative. Jusqu'à présent, l'étude de la conception basée sur la connaissance est largement concentrée sur la conception routine et non routine. Afin d'explorer la classe créative de la conception, un nouveau modèle computationnel basé sur la combinaison de raisonnement par cas en fonction (une approche pour résoudre de nouveaux problèmes avec l'aide d'une base de solution à des problèmes similaires) et des techniques du «soft computing» (tels que l'apprentissage automatique, l'exploration de données et d'optimisation) est proposé dans cette thèse. Ce nouveau modèle est capable de traiter quatre difficultés associées à la conception créative: la génération d'un prototype à partir d'une spécification incomplète, le raisonnement et l'amélioration de la performance d'un système avec un manqué d'exemple dans la bibliothèque de base de cas, l'extraction de caractéristiques clés d'un espace central de caractéristique donnée, l'adaptation de solutions trouvées à des problèmes similaires pour proposer une nouvelle solution innovante pour une tâche de conception donnée. Le principe de base au sein de ce modèle est que la connaissance de différents cas à des différents niveaux peuvent être précisément exploré et intégré dans un processus de conception pratique. En outre, afin de démontrer l'importance pratique de notre modèle computationnel proposé, un système pour la conception des dispositifs électromagnétiques capable de générer un prototype de conception nouveau à partir d'une base de cas réel à haute dimensionnalité a été développé.
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Marshall, Carolynne Therese. "The design and implementation of comparative reasoning tools for fermentations." Thesis, University College London (University of London), 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389624.

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Ulrich, Karl T. "Computation and Pre-Parametric Design." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/6845.

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My work is broadly concerned with the question "How can designs bessynthesized computationally?" The project deals primarily with mechanical devices and focuses on pre-parametric design: design at the level of detail of a blackboard sketch rather than at the level of detail of an engineering drawing. I explore the project ideas in the domain of single-input single-output dynamic systems, like pressure gauges, accelerometers, and pneumatic cylinders. The problem solution consists of two steps: 1) generate a schematic description of the device in terms of idealized functional elements, and then 2) from the schematic description generate a physical description.
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Books on the topic "Engineering design reasoning"

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1947-, Brown David C., ed. Engineering design: Representation and reasoning. 2nd ed. New York: Cambridge University Press, 2012.

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Andrzej, Kraslawski, ed. Case based design: Applications in process engineering. Berlin: Springer, 2008.

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1953-, Balachandran M., and Zhang Dong Mei, eds. Case-based reasoning in design. Mahwah, N.J: Lawrence Erlbaum Associates, 1995.

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Wang, Charlie C. L. Geometric Modeling and Reasoning of Human-Centered Freeform Products. London: Springer London, 2013.

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Kaufmann, Matt. Computer-Aided Reasoning: ACL2 Case Studies. Boston, MA: Springer US, 2000.

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Kunz, Wolfgang. Reasoning in Boolean Networks: Logic Synthesis and Verification using Testing Techniques. Boston, MA: Springer US, 1997.

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J, Berndt Donald, and Kandel Abraham, eds. Automated database applications testing: Specification representation for automated reasoning. Singapore: World Scientific, 2010.

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Panagiotis, Manolios, and Moore J. Strother 1947-, eds. Computer-aided reasoning: An approach. Boston: Kluwer Academic Publishers, 2000.

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Matt, Kaufmann, Manolios Panagiotis, and Moore J. Strother 1947-, eds. Computer-aided reasoning: ACL2 case studies. Boston: Kluwer Academic Publishers, 2000.

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LPAR (Conference) (17th 2010 Yogyakarta, Indonesia). Logic for programming, artificial intelligence, and reasoning: 17th international conference, LPAR-17, Yogyakarta, Indonesia, October 10-15, 2010 : proceedings. Berlin: Springer, 2010.

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Book chapters on the topic "Engineering design reasoning"

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Balazs, Marton E., and David C. Brown. "Design Simplification by Analogical Reasoning." In From Knowledge Intensive CAD to Knowledge Intensive Engineering, 29–44. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-0-387-35494-1_3.

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Alnusair, Awny, and Tian Zhao. "Using Ontology Reasoning for Reverse Engineering Design Patterns." In Models in Software Engineering, 344–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12261-3_32.

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Plappert, Stefan, Paul Christoph Gembarski, and Roland Lachmayer. "Decision-Making with Probabilistic Reasoning in Engineering Design." In Lecture Notes in Computer Science, 56–65. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59491-6_6.

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Leake, David B., Larry Birnbaum, Kristian Hammond, Cameron Marlow, and Hao Yang. "Integrating Information Resources: A Case Study of Engineering Design Support⋆." In Case-Based Reasoning Research and Development, 482–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48508-2_35.

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Hertkorn, Peter, and Stephan Rudolph. "Exploiting Similarity Theory for Case-Based Reasoning in Real-Valued Engineering Design Problems." In Artificial Intelligence in Design ’98, 345–62. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5121-4_18.

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Rehman, Fayyaz, and Xiu-Tian Yan. "Using Context Knoledge Based Reasoning to Support Functional Design." In Perspectives from Europe and Asia on Engineering Design and Manufacture, 69–78. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2212-8_6.

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Shelesh-Nezhad, K., and E. Siores. "A Case-Based Reasoning Approach in Injection Molding Process Design." In Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 775. London: CRC Press, 2022. http://dx.doi.org/10.1201/9780429332111-133.

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Honecker, Fabian, and Axel Schulte. "Automated Online Determination of Pilot Activity Under Uncertainty by Using Evidential Reasoning." In Engineering Psychology and Cognitive Ergonomics: Cognition and Design, 231–50. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58475-1_18.

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Edmondson, James, and Aniruddha Gokhale. "Design of a Scalable Reasoning Engine for Distributed, Real-Time and Embedded Systems." In Knowledge Science, Engineering and Management, 221–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25975-3_20.

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Germani, Michele, Marco Mandolini, Marco Marconi, Alessandro Morbidoni, and Marta Rossi. "A Case-Based Reasoning Approach to Support the Application of the Eco-Design Guidelines." In Re-engineering Manufacturing for Sustainability, 81–86. Singapore: Springer Singapore, 2013. http://dx.doi.org/10.1007/978-981-4451-48-2_13.

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Conference papers on the topic "Engineering design reasoning"

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Summers, Joshua D. "Reasoning in Engineering Design." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85334.

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Peirce, the American philosopher of the late 19th and early 20th centuries, is credited with first observing the triple of reasoning (deductive, inductive, and abductive). These three types of reasoning are discussed as they relate to the engineering design process. The reasoning classes are based upon distinctions between what is given and what is derived with respect to the grounds, the warrants, and the conclusions. Simple definitions are synthesized that agree well with the literature, while distinctions are made where overlapping and often conflicting definitions are found. This distinction leads to the need for separating abductive reasoning and retroductive reasoning. A generalized description of design agrees well with the definition for retroductive reasoning, as is demonstrated in this paper. A brief survey of “traditional” design reasoning methods (rule based reasoning, analogy based reasoning, simulation based reasoning, and constraint based reasoning) is developed to show that these design methods are equivalent or decomposable into the fundamental reasoning classes. This paper provides a discussion in a common framework for comparing design reasoning strategies found in automation systems based upon the fundamental classes.
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Lees, B. "Engineering design support through case-based reasoning." In IEE Colloquium on Intelligent Design Systems. IEE, 1997. http://dx.doi.org/10.1049/ic:19970121.

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Lees, Brian, Meer Hamza, and Chris Irgens. "Case-based reasoning support for engineering design." In Intelligent Systems and Smart Manufacturing, edited by Bhaskaran Gopalakrishnan and Angappa Gunasekaran. SPIE, 2000. http://dx.doi.org/10.1117/12.403672.

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Navaneethakrishnan, Ravisrinivas, Kristin L. Wood, and Richard H. Crawford. "An Object-Oriented Formalism for Geometric Reasoning in Engineering Design and Manufacture." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0403.

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Abstract Geometry is a language for representing and communicating mechanical design information. To enhance the integration of design and manufacturing tasks, a representation of product geometry at appropriate levels of abstraction for geometric reasoning is necessary. In addition, a mechanism to perform reasoning with the representation is needed. This paper describes a computational formalism for representing and manipulating geometry at different abstraction levels. Geometry is abstracted in terms of form features. Spatial relationships between features, which are important components for geometric reasoning, are represented using a modification of a previously developed technique — the intermediate geometry language (IGL). To enable geometric reasoning, information abstracted using features and the IGL is transformed into a data model based on object-oriented modeling technology. An object algebra is defined to query the data model for information.
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Wang, Eric, and Yong Se Kim. "Feature-Based Assembly Mating Reasoning." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/cie-1341.

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Abstract It is desirable to provide computer-based tools to assist designers and manufacturing engineers in the difficult task of geometric reasoning to achieve fast product development and flexible manufacturing. In the domain of assembly reasoning and planning, numerous methods have been developed to analyze a user-specified assembly configuration of parts. Fewer efforts have been made to systematically obtain the assembly configuration itself from underlying information. As a step in this direction, we present an assembly mating reasoning method that determines feasible assembly configurations directly from part geometry. Our method recognizes form features from the boundary representations of the components, then treats the form features as assembly features and identifies mating relations between them. Assembly configurations are constructed by using Boolean operations on the components to simulate the assembly process. A heuristic backtracking search is used to traverse the space of feasible component assembly operations. The result of the search is an enumeration of feasible assembly configurations.
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Tseng, Winger S. W. "Perceptual uncertainty supports design reasoning." In INTERNATIONAL CONFERENCE ON CIVIL, MECHANICAL AND MATERIAL ENGINEERING: ICCMME 2018. Author(s), 2018. http://dx.doi.org/10.1063/1.5041410.

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Jayasuriya, Dhanushka B., and Indika Perera. "Ontology Based Software Design Documentation For Design Reasoning." In 2019 Moratuwa Engineering Research Conference (MERCon). IEEE, 2019. http://dx.doi.org/10.1109/mercon.2019.8818813.

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Siddique, Zahed, and Rajeshwar Adupala. "Product Family Architecture Reasoning." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85340.

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Designing family of products, instead of single products, using a common platform approach has gained momentum in various industries. One of the main challenges faced by companies includes specifying a product family architecture to support the varieties. Designers need to consider different viewpoints related to product, assembly, manufacturing, etc. during the development of the product family architecture. The purpose of this paper is to present a configuration reasoning method to develop a product family architecture that not only satisfy, but also has improved characteristics for different viewpoints. This paper attempts to accomplish these objectives by developing representations for components, modules, product family architecture, and assembly process. The paper also presents mathematical formulations to generate feasible product family architectures, indices for architecture evaluation, rules to ensure feasibility and improve from multiple viewpoints. The application of this configuration reasoning framework is illustrated using identifying product family architecture for a set of coffeemakers.
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9

Siddique, Zahed, and Rajeshwar Reddy Adupala. "Product Family Architecture Reasoning." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49380.

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Specifying the product platform and family architecture to support product varieties can be a challenging task for companies. Especially when various viewpoints have to be considered which include product variety, materials, manufacturing complexity, assembly complexity, average component count commonality, assembly sequence and late point differentiation. Consequently there is a need for reasoning to balance multiple viewpoints in the case of product families for the development of good architecture. In this paper we present a product family architecture design approach that can be applied to develop efficient product family architectures for a given set of product functions, while considering multiple viewpoints. In order to identify the efficient product family architecture(s) a three phase approach is presented: (1) Generating a set of feasible module architectures of options for each product function; (2) Combining the feasible module architectures and evaluating the product family architectures to identify candidate product family architectures with high evaluation scores; and (3) Improving the selected product family architecture. The product family architecture design approach is demonstrated using a coffeemaker product family.
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10

Zhu, Lijuan, Uma Jayaram, Sankar Jayaram, and OkJoon Kim. "Querying and Reasoning With Product Engineering Ontologies: Moving Past Modeling." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-29052.

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Much of the work in ontologies for product engineering has focused on the modeling of these ontologies. A key characteristic of an ontology model is that it uses a logic-based and formal specification to represent the information model, thus allowing querying and reasoning. In order to take advantage of this, we seek to move past ontology modeling and focus on developing meaningful reasoning mechanisms that are applicable for the domain of product engineering — a) to allow the user to make basic inferences such as checking consistency for definitions of concepts, b) to query and retrieve existing product data information, and c) to derive new product data information not explicitly expressed in knowledge bases. A typical semantic application architecture consisting of knowledge base layer, logic reasoning layer, and application interface layer is adopted. Reasoning units are deployed in the logic reasoning layer of this architecture. These reasoning units act on the knowledge base for product engineering, specifically, the domain of product assembly constraint. SWRL & SQWRL are used to define the retrieval specifications and inference rules. User interfaces are also developed to help users submit the reasoning tasks, view the results, and thus assess the knowledge base indirectly and transparently. It is concluded that the reasoning mechanism exploits and extends the semantic representation made possible through ontology and holds promise for improved knowledge discovery and understanding.
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