Academic literature on the topic 'Knowledge driven CAD'
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Journal articles on the topic "Knowledge driven CAD"
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Liu, De Fang, Bin Wang, and Hong Pan Wu. "Mechanical-Design-Oriented Knowledge-Driven Model." Applied Mechanics and Materials 44-47 (December 2010): 1987–90. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.1987.
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According to the characters of mechanical product design, product design knowledge is classified into explicit knowledge and indefinite knowledge. A knowledge-driven product design system model was proposed based on the knowledge management. To meet the normal product design process, the design system structure was built on four layers. A mixed knowledge reasoning strategy was proposed, which is combined by design cases, models, and rules. The system provides a public integration interface, so different design tools such as UG NX, Catia and Pro-E can be applied. To resolve the design conflict in product design process, a collaborative design technique was put forward that the CAD, CAPP, CAM engineers worked togeth
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Hsu, Yung Yuan. "A Golf Head CAD/KBE Optimization Design System." Advanced Materials Research 338 (September 2011): 304–10. http://dx.doi.org/10.4028/www.scientific.net/amr.338.304.
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The purpose of this study was to construct a knowledge-based CAD/KBE system for the optimal design of golf heads. The inability of conventional CAD systems to identify existing knowledge during design and manufacturing processes is a current development bottleneck. Therefore, this study attempted to effectively introduce and integrate KBE technology into a CAD system, so as to achieve the objective of knowledge driven automation (KDA). This study selected golf iron heads with a complex-design surface as the research subject, adopted commercial CAD software (UG/NX) and its secondary development environment as a platform and applied perturbation vectors in the control of NURBS free-form surfaces. We changed the CAD’s entity shapes and physical properties, integrated the optimal principle of design with a CAD solid model, to automatically drive the CAD solid model of golf iron heads according to the design objectives, and constructed a knowledge-based optimal CAD design technology.
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Li, Min, Y. F. Zhang, and J. Y. H. Fuh. "Retrieving Reusable 3D CAD Models Using Knowledge-Driven Dependency Graph Partitioning." Computer-Aided Design and Applications 7, no. 3 (January 2010): 417–30. http://dx.doi.org/10.3722/cadaps.2010.417-430.
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Nnaji, Bartholomew O., and Tzong-Shyan Kang. "Interpretation of CAD models through neutral geometric knowledge." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 4, no. 1 (February 1990): 15–45. http://dx.doi.org/10.1017/s0890060400002225.
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A generalized approach to fast interpretation of objects and their features has so far eluded researchers. In manufacturing, this interpretation can be approached from the vision point of view or from the CAD data perspective. Presently, CAD systems are widely used in several aspects of manufacturing production. It is therefore more efficient to use CAD data for object reasoning in manufacturing, especially when systems will eventually be data driven. Components can be modelled on a CAD system using various modelling techniques and the representation of their geometric information is still CAD system dependent. However, the advent of the Initial Graphics Exchange Specification (IGES) now makes it possible to represent CAD data in a neutral and standard manner.This paper describes a scheme for recognizing and representing features for CAD data extracted using the IGES interface. The concepts developed are based on graph-based feature representation, where features are represented by a set of faces as well as their topological adjacency.Strategies for classifying features and methods of decomposing a complicated feature into several simpler features for recognition purposes are discussed.
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Han, Guanghui, Xiabi Liu, Nouman Q. Soomro, Jia Sun, Yanfeng Zhao, Xinming Zhao, and Chunwu Zhou. "Empirical Driven Automatic Detection of Lobulation Imaging Signs in Lung CT." BioMed Research International 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/3842659.
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Computer-aided detection (CAD) of lobulation can help radiologists to diagnose/detect lung diseases easily and accurately. Compared to CAD of nodule and other lung lesions, CAD of lobulation remained an unexplored problem due to very complex and varying nature of lobulation. Thus, many state-of-the-art methods could not detect successfully. Hence, we revisited classical methods with the capability of extracting undulated characteristics and designed a sliding window based framework for lobulation detection in this paper. Under the designed framework, we investigated three categories of lobulation classification algorithms: template matching, feature based classifier, and bending energy. The resultant detection algorithms were evaluated through experiments on LISS database. The experimental results show that the algorithm based on combination of global context feature and BOF encoding has best overall performance, resulting inF1score of 0.1009. Furthermore, bending energy method is shown to be appropriate for reducing false positives. We performed bending energy method following the LIOP-LBP mixture feature, the average positive detection per image was reduced from 30 to 22, andF1score increased to 0.0643 from 0.0599. To the best of our knowledge this is the first kind of work for direct lobulation detection and first application of bending energy to any kind of lobulation work.
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Sharma, Shukla, Ludovic Koehl, Pascal Bruniaux, Xianyi Zeng, and Zhujun Wang. "Development of an Intelligent Data-Driven System to Recommend Personalized Fashion Design Solutions." Sensors 21, no. 12 (June 21, 2021): 4239. http://dx.doi.org/10.3390/s21124239.
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In the context of fashion/textile innovations towards Industry 4.0, a variety of digital technologies, such as 3D garment CAD, have been proposed to automate, optimize design and manufacturing processes in the organizations of involved enterprises and supply chains as well as services such as marketing and sales. However, the current digital solutions rarely deal with key elements used in the fashion industry, including professional knowledge, as well as fashion and functional requirements of the customer and their relations with product technical parameters. Especially, product design plays an essential role in the whole fashion supply chain and should be paid more attention to in the process of digitalization and intelligentization of fashion companies. In this context, we originally developed an interactive fashion and garment design system by systematically integrating a number of data-driven services of garment design recommendation, 3D virtual garment fitting visualization, design knowledge base, and design parameters adjustment. This system enables close interactions between the designer, consumer, and manufacturer around the virtual product corresponding to each design solution. In this way, the complexity of the product design process can drastically be reduced by directly integrating the consumer’s perception and professional designer’s knowledge into the garment computer-aided design (CAD) environment. Furthermore, for a specific consumer profile, the related computations (design solution recommendation and design parameters adjustment) are performed by using a number of intelligent algorithms (BIRCH, adaptive Random Forest algorithms, and association mining) and matching with a formalized design knowledge base. The proposed interactive design system has been implemented and then exposed through the REST API, for designing garments meeting the consumer’s personalized fashion requirements by repeatedly running the cycle of design recommendation—virtual garment fitting—online evaluation of designer and consumer—design parameters adjustment—design knowledge base creation, and updating. The effectiveness of the proposed system has been validated through a business case of personalized men’s shirt design.
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Huang, Hong Hui, and Ling Yun Wang. "The Rapid Design System of Stamping Process Based on KBE." Applied Mechanics and Materials 347-350 (August 2013): 3460–64. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3460.
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This paper takes UGNX6.0 as the development platform, by using its UG/KF development tools, fusing feature and knowledge together, so as to realize the process associated with the geometric design knowledge and stamping process design. Based on the features of stamping process, the classification of stamping process knowledge has been studied. With the object-oriented method, the rule-based and instance-based technology for expressing and acquiring the stamping process knowledge is discussed. Based on this, the stamping process model driven by knowledge has been established. It showed the importance of the CAD technology in designing of relatively complex progressive dies. Based on the knowledge engineering process designed, the degree of intelligence stampings process design has been enhanced, design quality and efficiency has been improved, and the dependence of the process design experience of designers has been reduced.
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Wang, Ling Yun, and Hong Hui Huang. "The Application of KBE on Stamping Process Design." Advanced Materials Research 760-762 (September 2013): 1842–46. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1842.
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UGNX6.0 is used as the development platform by its UG/KF development tools, fusing feature and knowledge together, so as to realize the process associated with the geometric design knowledge and stamping process design. Based on the features of stamping process, the classification of stamping process knowledge has been studied. With the object-oriented method, the rule-based and instance-based technology for expressing and acquiring the stamping process knowledge is discussed. Based on this, the stamping process model driven by knowledge has been established. A bending sheet was taken as an example in introducing the designing process of progressive die based on UG_PDW. The process arrangement was mainly introduced, and the bending part feature recognition and modeling were all elaborated and related examples were given in the paper. It showed the importance of the CAD technology in designing of relatively complex progressive dies.
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Tirpak, Thomas M., Lawrence E. Lach, Weimin Xiao, and Juan M. Lopez. "A Distributed Decision-Support System for Virtual Prototyping." Decision Making in Manufacturing and Services 1, no. 2 (October 11, 2007): 137–52. http://dx.doi.org/10.7494/dmms.2007.1.2.137.
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Virtual Prototyping (VP) is a data-driven design process that promotes both knowledge reuse and innovation. High-profile applications in the automotive and aerospace industries have demonstrated its potential to significantly reduce prototype cycles, time to market, and total product cost. This paper addresses VP as a specialized application of Decision-Support Systems, and discusses common requirements for engineering design tools, as well as requirements specific to the design of electronic products, such as mobile phones. Motorola Labs' test bed for VP is introduced in terms of its open, agent-based architecture utilizing Java CORBA. One of the key principles of the VP System is the reuse of expert knowledge across multiple engineering domains. This is highlighted via several use cases, showing that the system can function not only as an Intranet-accessible repository of model services but also as an integral part of decision-making within the native CAD environment.
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Bergs, Christoph, Mohamed Khalil, Marcel Hildebrandt, Michael Heizmann, Roland Wüchner, Kai-Uwe Bletzinger, and Volker Tresp. "Health indication of electric motors using a hybrid modeling approach." tm - Technisches Messen 86, no. 11 (November 26, 2019): 640–50. http://dx.doi.org/10.1515/teme-2019-0082.
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AbstractHealth assessment of electric motors is a research topic of high relevance in the area of structural mechanics. In the early days, the health state of an electric motor was mainly determined by empirical knowledge. But this paradigm is shifting to advanced methods of predicting the health of single components of an electric motor using its physical simulation models from the design phase. However, the process of creating the models to become usable during operation is laborious and in many cases no simulation or even 3D-CAD models from the design phase are available. This article focuses on a combination of a physics-based and data-driven estimation of the motor health, especially for motors where no information from the design phase is available. In particular, the advancements of the development of the hybrid fusion method moSAIc are presented. moSAIc allows to transfer the knowledge inherent in physical degradation models of motors to unknown derivatives. The experiments show that the accuracy and robustness of moSAIc is significantly better compared to results of earlier stages.
Dissertations / Theses on the topic "Knowledge driven CAD"
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Grandicki, Andreas, and Mattias Lokgård. "Parametric CAD Modeling to aid Simulation-Driven Design : An evaluation and improvement of methods used at Scania." Thesis, Linköpings universitet, Maskinkonstruktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138121.
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This report documents a thesis conducted at Scania CV AB in Södertälje, Sweden. The main purpose of the thesis has been to examine and improve upon current practices of parametric CAD-modeling at Scania, with the ultimate goal of increased design automation and simulation-driven design. The thesis was initiated with a literature study, mainly covering the fields of parametric CAD-modeling, design automation and knowledge-based engineering. Furthermore, a questionnaire and multiple interviews were conducted to assess the awareness and mind-set of the employees. Finally, a case-study was carried out to follow current methodologies, and address any deficiencies found. Some of the most important findings were that while parametric modeling has considerable potential in enabling design automation, it is crucial, and most beneficial in terms of automation efficiency, to start with the fundamentals, namely achieving a uniform modeling practice. With these findings, a new proposed methodology has been introduced, as well as a recommended plan for a widespread implementation of parametric modeling at Scania. Such implementation would allow for shorter lead-times, faster adaptation to changing conditions, and reduced development expenditures.
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Machchhar, Raj Jiten. "Automated Model Generation and Pre-Processing to Aid Simulation-Driven Design : An implementation of Design Automation in the Product Development process." Thesis, Linköpings universitet, Maskinkonstruktion, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-168738.
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The regulations on emissions from a combustion engine vehicle are getting tougher with increasing awareness on sustainability, requiring the exhaust after-treatment systems to constantly evolve to the changes in the legislation. To establish a leading position in the competitive market, companies must adapt to these changes within a reasonable timeframe. With Scania’s extensive focus on Simulation-driven design, the product development process at Scania is highly iterative. A considerable amount of time is spent on generating a specific model for a simulation from the existing Computer-aided Design (CAD) model and pre-processing it. Thus, the purpose of this thesis is to investigate how design and simulation teams can collectively work to automatically generate a discretized model from the existing CAD model, thereby reducing repetitive work. As an outcome of this project, a method is developed comprising of two automation modules. The first module, proposed to be used by a design engineer, automatically generates a simulation-specific model from the existing CAD model. The second module, proposed to be used by a simulation engineer, automatically discretizes the model. Based on two case study assemblies, it is shown that the proposed method is significantly robust and has the potential to reduce product development time remarkably.
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Rahman, Shah Md Rajiur. "Smart Modeling of Drilling-Well in an Integrated Approach." Master's thesis, 2011. http://hdl.handle.net/10048/1794.
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The current well planning practice is usually done section by section with limited help of some knowledge-based tools. This thesis presents an integrated approach and a software prototype developed for well planning. It considers the geological input, i.e. pore pressure, over burden etc., to generate a step by step interactive drilling plan. The implemented well planning stages include the casing setting depth, casing and hole size determination, casing selection and then drill string design and modeling. The system is integrated with a Computer Aided Design (CAD) system for generating three-dimensional parametric model. The conceptual design and CAD modeling system are integrated in such a way that any changes in the design will be reflected to the CAD model. Such intelligent CAD design practice is new in the drilling industry. An Operational Parameters module is also attached with the system to predict the drilling coefficients by using offset well data and determine the optimum weight on bit, and the drill string rotation that minimizes drilling cost per foot for a single bit run.
Based on this approach, an integrated well planning system can be fully developed and it will be very useful for the decision making of drilling companies.
Books on the topic "Knowledge driven CAD"
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Tyulin, Andrey, and Aleksandr Chursin. Management of competitiveness of products. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1081761.
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The textbook contains the basics of the theory and practice of management by competitiveness of products in the current market conditions. It describes new approaches to management of competitiveness of production taking into account features of knowledge-based industries — the main driving forces of the Russian economy. Considers the practical issues of managing competitiveness in order to enhance the competitiveness of the organization in terms of digitalization of the economy.
Meets the requirements of Federal state educational standards of higher education of the last generation.
For students of educational institutions of higher education studying in areas of training 38.04.02 "Management" (master level) and 38.04.01 "Economy" (master level), as well as graduate students and University professors engaged in training in these areas. Can be recommended to managers and specialists of companies, involved in the process of management competitiveness of the organization products.
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Chuvikov, Dmitriy. Models and algorithms for reconstruction and examination of emergency events of road accidents based on logical artificial intelligence. 2nd ed. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1220729.
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The purpose of the monograph is to create a methodology, combined expert and simulation models, as well as algorithms and software-modeling tools for reconstruction and examination of accident events for automating decision-making by an expert center employee.
The methodology of combining and algorithms of joint work of an expert system based on logical artificial intelligence (mivar approach) and a simulation system for solving problems of reconstruction and examination of road accidents are developed; model reconstruction and examination of the accident in the formalism of the knowledge base bipartite oriented mivar nets, including analysis formulas braking qualities of the vehicle, determining the speed of a car's performance in terms of specific DTS, the formula for calculating different occasions: - slip car when braking, driving on curved sections of the road, hitting a car on the pedestrian in uniform motion and unlimited visibility; a method of generation of interfaces for designer expert systems based on the concept of mivar approach; special software in the form of expert systems "Analysis of road accident" in order to reduce the complexity of the process of calculating the disputed accidents, errors in the calculation and improve the accuracy and objectivity of the results obtained and the speed and quality of the calculations.
It can be useful to specialists of expert institutions, insurance companies, educational institutions in the field of expertise, as well as unmanned vehicles in terms of objective analysis and examination of road accidents.
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Nisbet, Matthew C., and Declan Fahy. New Models of Knowledge-Based Journalism. Edited by Kathleen Hall Jamieson, Dan M. Kahan, and Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.30.
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This chapter elaborates on the need for knowledge-based journalism in politicized science controversies, detailing specific practices and media structures that might enable more constructive debate. In doing so, it analyzes three main models for doing knowledge-based journalism, drawing on examples of veteran journalists who serve as prototypes for new generations of professionals to emulate and for media organizations to invest in. By combining these approaches, journalists and their news organizations can contextualize and critically evaluate expert knowledge and competing claims, facilitate discussion that bridges entrenched ideological divisions, and promote consideration of a broader menu of policy options and technologies. The recent advent of several news ventures focused on deeper forms of explanatory, analytical, and data-driven journalism suggest that at least some news industry leaders and philanthropists have recognized the need for new types of knowledge-based journalism. These ventures, however, are further evidence that dramatic changes are needed in journalism education.
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Fulcoli, F. Gabriella, and Antonio Baldini. Transcriptional regulation of early cardiovascular development. Edited by José Maria Pérez-Pomares, Robert G. Kelly, Maurice van den Hoff, José Luis de la Pompa, David Sedmera, Cristina Basso, and Deborah Henderson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198757269.003.0006.
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The two major cardiac cell lineages of the vertebrate heart, the first and second cardiac fields (FHF and SHF), have different developmental ontogeny and thus different transcription programs. Most remarkably, the fate of cardiac progenitors (CPs) of the FHF is restricted to cardiomyocyte differentiation. In contrast, SHF CPs, which are specified independently, are maintained in a multipotent state for a relatively longer developmental time and can differentiate into multiple cell types. The identity of the transcription factors and regulatory elements involved in progenitor cell programming and fate are only now beginning to emerge. Apparent inconsistencies between studies based on tissue culture and in vivo embryonic studies confirm that the ontogeny of cardiac progenitors is strongly driven or affected by regionalization, and thus by the signals that they receive in different regions. This chapter summarizes current knowledge about transcription factors and mechanisms driving CP ontogeny, with special focus on SHF development.
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Aalberg, Toril, and Stephen Cushion. Public Service Broadcasting, Hard News, and Citizens’ Knowledge of Current Affairs. Oxford University Press, 2016. http://dx.doi.org/10.1093/acrefore/9780190228637.013.38.
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Public service broadcasters are a central part of national news media environments in most advanced democracies. Although their market positions can vary considerably between countries, they are generally seen to enhance democratic culture, pursuing a more serious and harder news agenda compared to commercial media . . . But to what extent is this perspective supported by empirical evidence? How far can we generalize that all public service news media equally pursue a harder news agenda than commercial broadcasters? And what impact does public service broadcasting have on public knowledge? Does exposure to public service broadcasting increase citizens’ knowledge of current affairs, or are they only regularly viewed by citizens with an above average interest in politics and hard news?The overview of the evidence provided by empirical research suggests that citizens are more likely to be exposed to hard news, and be more knowledgeable about current affairs, when they watch public service news—or rather news in media systems where public service is well funded and widely watched. The research evidence also suggests there are considerable variations between public broadcasters, just as there are between more market-driven and commercial media. An important limitation of previous research is related to the question of causality. Therefore, a main challenge for future research is to determine not only if public service broadcasting is the preferred news provider of most knowledgeable citizens, but also whether it more widely improves and increases citizens’ knowledge about public affairs.
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Klesges, Lisa M. Cancer Prevention and Public Health Promotion. Edited by David A. Chambers, Wynne E. Norton, and Cynthia A. Vinson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190647421.003.0008.
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In this chapter, four case studies offer practical examples of implementation approaches that can accelerate evidence-based cancer prevention. The applied knowledge from the cases adds to the understanding that culture, context, politics, and partnership are key elements in driving health improvement, and although not always well understood or easily measured, they are a reminder that cancer prevention and care delivery exist within a complex system. In considering transformations in health care, moving from a linear and deconstructed model of delivery to consider complex adaptive models that could drive better outcomes was key to improved outcomes. Similarly, understanding context and complexity is a key consideration for implementing cancer prevention and control interventions into existing multisector social systems, be they health care, community, or statewide systems.
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Volberda, Henk, Frans A. J. Van Den Bosch, and Kevin Heij. Reinventing Business Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198792048.001.0001.
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Although research on business model innovation is flourishing internationally, important questions on the ‘how’, ‘what’, and ‘when’ of this process remain largely unanswered, particularly in regard to the role of top management. Using new knowledge derived from a survey among firms from various industries and several case studies, this book seeks to give us better understanding of ‘how’ firms can innovate their business model, ‘what’ kind of levers management should work on, and ‘when’ management should change the business model. It particularly considers one key question: is it better to replicate existing models or develop new ones? Renewal is especially vital in highly competitive environments. Nonetheless, whatever the environment, high levels of both replication and renewal will be key for a firm to succeed. This book looks at four levers that can be used by managers to innovate their business model: management itself, organizational form, technology, and co-creation with external parties are analysed. Furthermore, specific combinations which strengthen business model innovation are analysed. To help firms, the book also explores the different factors that can either enable or inhibit business model innovation. Through an investigation of replication versus renewal and of strategy-driven versus client-driven change, four distinct modes of business model innovation are identified: exploit and improve (replication which is strategy-driven); exploit and connect (replication which is customer-driven); explore and connect (renewal which is customer-driven); and explore and dominate (renewal which is strategy-driven). This book ends with a list of managerial dos and don’ts for business model innovation.
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Halvorsen, Tor, Hilde Ibsen, and Vyvienne RP M’kumbuzi. Knowledge for a Sustainable World: A Southern African-Nordic contribution. African Minds, 2015. http://dx.doi.org/10.47622/9781928331049.
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The search for answers to the issue of global sustainability has become increasingly urgent. In the context of higher education, many universities and academics are seeking new insights that can shift our dependence on ways of living that rely on the exploitation of so many and the degradation of so much of our planet. This is the vision that drives SANORD and many of the researchers and institutions within its network. Although much of the research is on a relatively small scale, the vision is steadily gaining momentum, forging dynamic collaborations and pathways to new knowledge. The contributors to this book cover a variety of subject areas and offer fresh insights about chronically under-researched parts of the world. Others document and critically reflect on innovative approaches to cross-continental teaching and research collaborations. This book will be of interest to anyone involved in the transformation of higher education or the practicalities of cross-continental and cross-disciplinary academic collaboration. The Southern African-Nordic Centre (SANORD) is a network of higher education institutions from Denmark, Finland, Iceland, Norway, Sweden, Botswana, Namibia, Malawi, South Africa, Zambia and Zimbabwe. Universities in the southern African and Nordic regions that are not yet members are encouraged to join.
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Frodeman, Robert. The Future of Interdisciplinarity. Edited by Robert Frodeman. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198733522.013.1.
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“The Future of Interdisciplinarity” explores the role of interdisciplinarity within the ecology of knowledge production and use. Cultural transformation, much of it driven by information and communication technologies, suggests the need to rethink the theoretical space of interdisciplinarity. Three themes are highlighted here: the rhetorical and policy dimensions of interdisciplinarity, the future of the research university, and issues of accountability and impact. Overall, interdisciplinary challenges should be seen as more a matter of political philosophy than epistemology, with attention concentrated on the ways in which interdisciplinarians can connect disciplinary expertise to community needs, highlighting both the capacities and limitations of knowledge.
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Gleitman, Lila. Sentence First, Arguments Afterward. Edited by Jeffrey Lidz. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780199828098.001.0001.
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This book collects the most significant papers written by Lila R. Gleitman, spanning 50 years of research on language and its acquisition. The book traces the roots of developmental psycholinguistics while presenting empirically driven arguments in favor of a rationalist theory of language acquisition. Gleitman’s work simultaneously shows how learners acquire knowledge richer than what can be found in the environment and how they use their input to acquire a specific language. The book also includes a foreword by Noam Chomsky and an introductory chapter by Jeffrey Lidz contextualizing Gleitman’s work in the transition from structuralism to mentalist architectures in linguistics.
Book chapters on the topic "Knowledge driven CAD"
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Iraqi, Mehdi, and Lionel Roucoules. "From Functional Analysis to CAD Modelling Based on Knowledge Transformation Driven by the Design Process." In Product Lifecycle Management. Towards Knowledge-Rich Enterprises, 458–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35758-9_41.
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Renn, Ortwin. "Risk Governance: From Knowledge to Regulatory Action." In Knowledge for Governance, 93–111. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47150-7_5.
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AbstractRisk governance is used to refer to a body of scholarly ideas and concepts for collective decision making involving uncertain consequences of events or actions. The risk governance concept developed by the International Risk Governance Council in Geneva provides guidance for constructing comprehensive assessment and management strategies to cope with risk. Its crafters integrate three types of scientific input: classic, curiosity-driven research; strategic, goal-oriented research: and catalytic, process-related investigations. In this paper, I demonstrate how these three knowledge pools can assist risk assessors and managers to improve their understanding of complex risk situations.
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Leydesdorff, Loet. "Subdynamics in Knowledge-Based Systems." In Qualitative and Quantitative Analysis of Scientific and Scholarly Communication, 175–93. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59951-5_9.
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AbstractUsing a set of six equations, I propose to model “interactions,” the “organization of meaning,” and “self-organization” as three coordination mechanisms among expectations; three further equations can be derived to operationalize “double contingency,” “identity,” and “reflection.” One can expect that the subdynamics update one another in co-evolutions as feedbacks and feed-forwards. Interfaces among two (sub)dynamics can be expected to operate with time differences (At). Interactions among horizontal and vertical time differences can generate hyper-incursivity in interhuman communications. Hyper-incursion enables us to reconstruct expectations. The social system is probably the only system which can be expected to carry “strong” anticipation while being reproduced as expectations. A system of expectations is not alive, is not constrained by a life-cycle, and does not need to “exist” otherwise than as expectations. The dynamics against the arrow of time are “cultural”: they rest on codes as the pillars of discursive knowledge driven upward into horizons of meaning.
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Németh, Renáta, and Júlia Koltai. "The Potential of Automated Text Analytics in Social Knowledge Building." In Pathways Between Social Science and Computational Social Science, 49–70. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-54936-7_3.
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AbstractThere are still many sociologists who are skeptical of the findings of big data-based analysis of social-data, questioning the potential of this knowledge production and its contribution to the scientific discourse of sociology.The chapter shows that this tension can be addressed through the redefinition of the research methodological basis of sociology, by the organic incorporation of data science know-how into its methods; the combined application of qualitative and quantitative analysis; and, the use of knowledge-driven science instead of the data-driven approach.The theoretical, methodological, and topical pathways between traditional and computational sociology emerge gradually along the chapter, which also includes plenty of illustrative examples of research situated at the interplay between sociology and data science. As our overview shows, there are new possibilities for sociological research, which are, in some sense, just by-products of information science. We introduce recently developed methods, which can be applied to specific sociological problems outside the scope of business applications. We present sociological topics not yet studied in this area and show new insights the approach can offer to classical sociological questions. As our aim is to encourage sociologists to enter this field, we discuss the new methods on the base of the classic quantitative approach, using its concepts and terminology and addressing the question of how traditionally trained sociologists can acquire new skills.
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Zhang, Chao, and Jiawei Han. "Data Mining and Knowledge Discovery." In Urban Informatics, 797–814. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_42.
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AbstractOur physical world is being projected into online cyberspace at an unprecedented rate. People nowadays visit different places and leave behind them million-scale digital traces such as tweets, check-ins, Yelp reviews, and Uber trajectories. Such digital data are a result of social sensing: namely people act as human sensors that probe different places in the physical world and share their activities online. The availability of massive social-sensing data provides a unique opportunity for understanding urban space in a data-driven manner and improving many urban computing applications, ranging from urban planning and traffic scheduling to disaster control and trip planning. In this chapter, we present recent developments in data-mining techniques for urban activity modeling, a fundamental task for extracting useful urban knowledge from social-sensing data. We first describe traditional approaches to urban activity modeling, including pattern discovery methods and statistical models. Then, we present the latest developments in multimodal embedding techniques for this task, which learns vector representations for different modalities to model people's spatiotemporal activities. We study the empirical performance of these methods and demonstrate how data-mining techniques can be successfully applied to social-sensing data to extract actionable knowledge and facilitate downstream applications.
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Leydesdorff, Loet. "Knowledge-Based Innovations and Social Coordination." In Qualitative and Quantitative Analysis of Scientific and Scholarly Communication, 1–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59951-5_1.
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AbstractThree themes have been central to my research program: (1) the dynamics of science, tech-nology, and innovation; (2) the scientometric operationalization and measurement of these dynamics; and (3) the Triple Helix (TH) of university-industry-government relations. In this introductory chapter, I relate these three themes first from an autobiographical perspective to (i)) Luhmann’s sociological theory about meaning-processing in communications with (ii) information-theoretical operationalizations of the possible synergies in Triple-Helix relations, and with (iii) anticipation as a selection mechanism in cultural evolutions different from “natural selection.” Interacting selection mechanisms can drive the development of redundancy; that is, options that are available, but have not yet been used. An increasing number of options is crucial for the viability of innovation systems more than is past performance. A calculus of redundancy different from and complementary to information calculus is envisaged.
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Muhammed, Shahnawaz, William J. Doll, and Xiaodong Deng. "Impact of Knowledge Management Practices on Task Knowledge." In Dynamic Models for Knowledge-Driven Organizations, 282–301. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2485-6.ch017.
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Organizational level studies of knowledge management have been hampered by the lack of measures of individual level knowledge management practices and outcomes that can be used as success criteria to determine whether, or to what degree, specific organizational knowledge management practices enhance individual knowledge creation, sharing, and application at the individual level. This paper explores how the knowledge management practices of individuals are related to the task knowledge they use to complete their work processes. The measures presented can be used as one way to evaluate the success of organizational knowledge management practices. Specifically, the paper explores the individual practices of knowledge creation, knowledge sharing, and knowledge application and how these practices are related to the task knowledge (conceptual, contextual, and operational knowledge) of individuals. A model of the relationships among knowledge management practices and task knowledge components is proposed and tested. Structural equation modeling is used. Results suggest that engaging in knowledge creation enhances an individual’s task knowledge through the practices of sharing and applying knowledge. Knowledge sharing and application enhance operational knowledge indirectly through changes in conceptual and contextual knowledge.
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Carbonara, Nunzia. "Knowledge-Driven Agglomeration Processes." In Relational Methodologies and Epistemology in Economics and Management Sciences, 373–96. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9770-6.ch014.
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According to the economic geography literature, firms tend to geographically cluster when agglomeration economies exist. These are positive externalities associated with the co-location of firms within a bounded geographic area. Traditionally, the agglomerative advantages have been expressed in terms of pecuniary externalities and they have been identified as one of the key sources of the geographical clusters' competitive advantage. However, in the last years the basics of competition are changed and the ability of firms to create new knowledge is more crucial for success rather than the efficiency in production. This has shifted the attention of scholars on the role of knowledge and learning for the competitiveness and success of geographical clusters. In line with these studies, the chapter suggests that agglomeration economies are related to both pecuniary externalities and knowledge-based externalities. The latter are benefits that co-located firms can gain in terms of development of knowledge. To investigate whether knowledge-based externalities affect geographical clustering of firms, an agent-based model is developed. By using this model, a simulation analysis is carried out.
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Baporikar, Neeta. "Drivers of Innovation." In Knowledge Management for Competitive Advantage During Economic Crisis, 250–70. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6457-9.ch014.
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Innovation helps organizations to grow. Growth, though measured in turnover and profit, can also occur in knowledge, experience, efficiency, and quality. Innovation is the process of making changes to existing, and it can be radical or incremental, applied to products, processes, or services. It can happen at all levels, from management teams to departments to individual. Various factors encourage and drive an organization to innovate. Each of these drivers demands continuity and learning. These drivers create a sense of urgency to create new organizational goals and generate new ideas for meeting these goals. The term innovation is often associated with products, but can also occur in processes that make products, services, or deliver products and services, including intangibles. This chapter focuses on innovation in the organizational context, describes concepts underlying innovation, and tries to understand the core of the innovation process: What drives innovation in organizations?
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Ganguly, Anirban, Ali Mostashari, and Mo Mansouri. "Measuring Knowledge Management/Knowledge Sharing (KM/KS) Efficiency and Effectiveness in Enterprise Networks." In Dynamic Models for Knowledge-Driven Organizations, 318–36. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2485-6.ch019.
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Knowledge Management (KM) is critical in ensuring process efficiency, outcome effectiveness and improved organizational memory for the modern day business enterprises. Knowledge Sharing (KS) is fast becoming a rapidly growing area of interest in the domain of knowledge management. The purpose of this paper is to enlist a set of generalized metrics that can be used to evaluate the efficiency and the effectiveness of knowledge sharing in an enterprise network. The metrics proposed in this research are those that can be readily measured by various types of enterprise knowledge sharing systems, and link usage information to organizational outputs. The paper uses an illustrative case example of how an enterprise might make use of the metrics in measuring the efficiency and effectiveness of its knowledge sharing system.
Conference papers on the topic "Knowledge driven CAD"
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Zhu, Lijuan, Uma Jayaram, Sankar Jayaram, and OkJoon Kim. "Ontology-Driven Integration of CAD/CAE Applications: Strategies and Comparisons." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87768.
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In this paper we present a detailed exploration of ontology-driven approaches and strategies for integrating product data between CAD/CAE applications. We structure the ontology model into three layers: General Domain Ontology, Domain Specific Ontology, and Application Specific Ontology. In particular, Application Specific Ontologies are built for PRO/E, CATIA, and a virtual assembly design tool called VADE. This allows the integration processes to be demonstrated for a) two applications in the common domain of product design, and b) two applications in different domains, one in the product design domain and the other in an assembly simulation domain. In addition, these ontology-driven strategies are compared with two other approaches. The first study focuses on the knowledge modeling aspect and compares the ontology approach with a standard modeling language, UML. The second study focuses on data integration and translation aspect and compares the ontology-driven approach with a traditional one. It is concluded that an ontology-driven approach is superior for solving heterogeneous data problems involving multiple applications by managing data on semantic level.
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Remy, Sébastien, Florent Laroche, Alexandre Durupt, and Alain Bernard. "Knowledge Based Reverse Engineering Methodology." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82927.
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In Reverse Engineering, commercial solutions such as Geomagic™ or RapidForm™ or CAD software such as CATIA™ provide very efficient toolboxes that enable to rebuild geometry. Moreover, some of them provide segmentation algorithms, sketchers and/or many other facilities rebuilding tools in order to help to recover the original surface. Those software’s enable to rebuild the geometry of a technical object as a set of functions (protrusion, revolution, sweep…), they enable to add colours and textures, and they enable realistic kinematical animation and many other things. Unfortunately, all those toolboxes present a lack of geometry analysis tools. The geometry of a given product is the consequence of a complete process, it is important, considering Reverse Engineering activities, to try to recover any evidence of its past life (including socio-economical aspects, the design intents of the former designer, its different uses…) from its geometry in order to produce a good quality 3D model. Such models can provide important possibilities for Reverse Engineering. It enables to study the product more efficiently than a geometrical model based on a mesh or on free form surfaces. This paper proposes approaches and methodologies for using knowledge to rebuild CAD model to the best closer to the original CAD model that could have been obtained by the original designer. Such a model is feature based. They can be functional features or manufacturing features. For a good rebuilt of 3D model, the geometry of these features is driven by parameters, rules and relationships that are provided by the former designer.
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Gopinath, Varun, Mehdi Tarkian, Johan Ölvander, and William Gaziza. "Template Driven Conceptual Design of High Speed Trains." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34045.
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Conceptual design of multidisciplinary systems begins with a description of requirements and proceeds with a solution at a high abstraction level. A systematic and rigorous approach is required to evaluate complex systems and can be achieved by mapping the interactions between disciplines. Research has shown that the use of geometry in the early stages act as enablers for high fidelity analyses as required information can be extracted from the model. In the paper, Knowledge Based Engineering is used with the aim of managing the added complexity as it supports design automation and reuse. This article describes a configuration tool, which allows for quick generation of train geometry using High Level CAD Templates. The tool was created as part of a research project, with the primary objective of the development of a robust framework for a Multidisciplinary Design Optimization process which can support design of high-speed trains.
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Harding, Bruce A. "A Simple Mechanism to Teach a Complex Practitioner Knowledge Set." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80481.
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Mechanical engineering technology graduates must exhibit a number of skills as industrial practitioners. While certain skills are learned on the job, fundamental knowledge acquired in school coursework actually forms the basis for successful development of that necessary skills set. Within the skill set, one given great emphasis is that of communications. At Purdue University, the emphasis on communications skills crosses many courses but is divided among four veins: 1) written communications dealing with papers, reports, etc.; 2) oral communications dealing with effective presentations and interpersonal relationships; 3) computational communications, mathematical problem-solving, be it via hand, calculator or computer; and 4) graphics communications dealing with 3D modeling and the development and interpretation of specifications documented on engineering drawings. This paper describes a project where a simple mechanical device is used to teach complex topics, bridging multiple communications veins. In this case the project centers on the design and modification of an arbor press, but could be based on any number of devices. The simple arbor press forms the foundation for the development of a complex industry-driven knowledge set. Included are topics common to practitioners employed in design, manufacturing and quality - all of which are typical industrial assignments for MET graduates. The assignment is part of Production Design & Specifications (PD&S), a core course and the second in a two-course CAD-based freshman sequence. Where the first course teaches 3D modeling skills, PD&S concentrates on the cognitive aspects of problem-solving using modeling, calculations and extracted drawings. Students complete the project in three phases over an eight-week period. Each phase is driven by an Engineering Change Order (ECO), a common industrial practice. Contained in the ECOs are both detailed requirements and open-ended requirements. While fulfilling the ECOs, students must make decisions on interconnected requirements that ripple through design, manufacturing, and quality assurance. Requirements include: • Design based on ISO preferred numbers. • Selection of standard parts and stock materials. • Determination of cost/benefit ratios. • Manufacturing tolerances and tolerance stack-ups. • Fits calculations based on ASME B4.2 standards. • Calculation of mass properties. • Use of geometric dimensioning & tolerancing. • Documentation of product lifecycle changes. Together, these and other varied topics, when woven around the simplicity of an arbor press, give students real-world experiences without the process becoming daunting due to the sheer complexity of the mechanism.
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Musuvathy, Suraj R., David E. Johnson, H. James de St. Germain, Elaine Cohen, Chimiao Xu, Richard F. Riesenfeld, and Thomas C. Henderson. "Integrating Multiple Engineering Resources in a Virtual Environment for Reverse Engineering Legacy Mechanical Parts." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85462.
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Reverse engineering is a time-consuming and technically formidable process that is increasingly becoming an economic imperative due to replacement costs. The Multiple Engineering Resources aGent Environment (MERGE) system, introduced in this paper, is a new approach toward reverse engineering whose architecture and modules are driven specifically by the requirements of legacy engineering. Legacy engineering scenarios presume availability of multiple (possibly incomplete or inconsistent) sources of information, lack of digital descriptions of the parts, constrained time restrictions and need for significant domain knowledge expertise. The reverse engineering process must yield modern CAD models capable of driving state-of-the art CAM processes. The MERGE system aims at making the reverse engineering process more effective, using both intuitive interaction and visualization as key components, by enabling quick identification and resolution of inconsistencies among various resources in a unified environment. The MERGE system also aims at simplifying the reverse engineering process by integrating various computational agents to assist the reverse engineer in processing information and in creating the desired CAD models.
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Pegemanyfar, Nima, Michael Pfitzner, Ruud Eggels, Ralf von der Bank, and Marco Zedda. "Development of an Automated Preliminary Combustion Chamber Design Tool." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90430.
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The preliminary design of a new combustion chamber requires the combination of many elements of know-how in terms of combustor design rules, aerothermal calculations and preliminary design tools. To use this knowledge more efficiently pre-competitive work on an automated knowledge-based combustor design methodology is done within the European project INTELLECT D.M. (Integrated Lean Low Emission Combustor Design Methodology) in order to set up a KBE (Knowledge Based Engineering) system. In the method presented here, the rules and calculation routines are implemented into an automated preliminary design system using an Excel-driven database to generate a parametric Unigraphics CAD model. The utilized design rules represent state-of-the-art combustor design and will be extended later by lean combustion design rules, which are currently developed within INTELLECT D.M.. The database contains all design parameters and rules to provide CAD, CFD and optimization tools with the required information. Based on a set of performance parameters the system automatically generates the parametric geometry of a combustor containing the liners with cooling devices (optionally Z-ring or effusion cooling) and mixing holes, heat shield, cowl, casings and (pre)diffusor. To estimate the required cooling air, one-dimensional heat transfer equations including convection, radiation and conduction are solved. The generated CAD model visualizes the calculated combustor geometry and forms the basis for an automated CFD mesh generation utilizing the grid generator ICEM CFD.
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Prasad, Brian, and Jeff Rogers. "A Knowledge-Based System Engineering Process for Obtaining Engineering Design Solutions." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85561.
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Designing and developing highly engineered products requires direct (and more dynamic) associations between customers’ specifications and product characteristics (or its behaviors). In order to meet the specified customer performance, cost, and integrity goals, a multitude of specialized analyses, heuristics, shortcuts, look-up tables, equations, algorithms, finite elements, and material substitution at multiple levels (system, subsystems, components and parts) are ought to be performed. The product geometries of such engineered product are often complex and many parts are designed interactively from scratch using a 3D commercial computer-aided design (CAD) — lately often referred as Product Life-cycle Management (PLM) system. Today, this very “PLM-based” engineered product-design process is often “static”, very “feature or geometry-dependent,” “knowledge-intensive,” and therefore, engineers often takes considerable time (months) to complete this manual process. Today, more and more companies want to quickly reengineer a product from a multitude of family solutions (corresponding to various design trade-off studies). They are interested in some dynamic form of a decision-based system that could automatically filter through a multitude of historical product solutions and quickly reconfigure one that meets the customer requirements with the least cost, weight, and time investment. Such decision-based product automation is not an easy task by any means. Product definitions without knowing specific geometry are hard to conceive, capture generically, and reuse widely (via any generative tool). A typical product development process —by its nature—is highly dynamic, nonlinear, discrete, feature-dependent, and part-dependent. The solution is not easy, since problem formulation is time-bound, has numerous discrete inputs, topologies, and several mathematical discontinuities. This paper discusses the system architecture of the Knowledge-driven Automation (KDA) program — established at Parker in 2002. It addresses many of the above product development issues and problems. In particular, authors describe a Knowledge-based System Engineering Process for Obtaining Engineering Design Solutions in a Commercial PLM Setting. The architecture and solutions use a number of innovative knowledge-based engineering (KBE) concepts and procedures. Through strategic use of generative modeling, spreadsheet tables, part and assembly templates, system engineering concepts, and our proprietary “smart part concepts,” authors were able to engineer-to-configure a family of hydraulic actuators automatically from their customer specifications using a set of PLM (CATIA V5 and its underlying knowledgeware) tools.
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Song, Ruoyu, Yanglong Lu, Cassandra Telenko, and Yan Wang. "Manufacturing Energy Consumption Estimation Using Machine Learning Approach." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67679.
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Environmental impacts of manufacturing are often significant and influenced by part and process parameters. Energy consumption is one of the most critical factors for the overall environmental impact of manufacturing. To achieve energy reduction, one must estimate the manufacturing energy consumption throughout the design stage. This paper presents an efficient data-driven approach to utilize machine learning to estimate energy consumption of a manufacturing process from a CAD model. The approach enables quick cost estimation with limited knowledge about the exact process parameters. A case study of fused deposition modeling is used to illustrate the feasibility of this framework and test potential regression methods. Lasso and elastic net regressions were compared in this study. The potential application of this framework to other manufacturing processes is also discussed.
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Taelman, Ruben, and Ruben Verborgh. "Declaratively Describing Responses of Hypermedia-Driven Web APIs." In K-CAP 2017: Knowledge Capture Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3148011.3154467.
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Nielsen, Eric H., John R. Dixon, and George E. Zinsmeister. "Capturing and Using Designer Intent in a Design-With-Features System." In ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0035.
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Abstract The goal of “intelligent” computer-aided-design (CAD) systems is to provide greater support for the process of design, as distinguished from drafting and analysis. More supportive design systems should provide a quick and simple means of creating and modifying design configurations, automating evaluation procedures (e.g., for manufacturing), and automating interfaces to analysis procedures. In this paper we are concerned with the issues of representing in-progress designs so that such goals can be met. A feature-based representation is proposed in which features are defined as possessing not only form but also certain designer intentions regarding geometric relationships. A working experimental version of a design-with-features system using this representation for thin-walled components illustrates its use in composing a design as a configuration of feature-forms, in modifying the design geometry through automatic, intelligent incorporation and propagation of designer-initiated geometry changes, and in providing for the generation of user-defined features. In contrast to constraint-driven simultaneous equation solving methods, this system uses an intent-driven knowledge-based method to propagate and incorporate geometry modifications not only in fully-constrained designs, but also in over- and under-constrained designs. Issues of manageability, extensibility, and computationally efficiency were considered in the development of the core services of the system.
Reports on the topic "Knowledge driven CAD"
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Richmond, Paul, Adam Potter, David Looney, and William Santee. Terrain coefficients for predicting energy costs of walking over snow. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41602.
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Predicting the energy costs of human travel over snow can be of significant value to the military and other agencies planning work efforts when snow is present. The ability to quantify, and predict, those costs can help planners determine if snow will be a factor in the execution of dismounted tasks and operations. To adjust predictive models for the effect of terrain, and more specifically for surface conditions, on energy costs, terrain coefficients (ƞ) have been developed. By applying knowledge gained from prior studies of the effects of terrain and snow, and by leveraging those existing dismounted locomotion models, we seek to outline the steps in developing an improved terrain coefficient (ƞ) for snow to be used in predictive modeling. Using published data, methods, and a well-informed understanding of the physical elements of terrain, e.g., characterization of snow sinkage (z), this study made adjustments to ƞ-values specific to snow. This review of published metabolic cost methods suggest that an improved ƞ-value could be developed for use with the Pandolf equation, where z=depth (h)*(1 - (snow density (ρ0)/1.186)) and ƞ=0.0005z3 + 0.0001z2 + 0.1072z + 1.2604. This paper provides data-driven improvements to models that are used to predict the energy costs of dismounted movements over snow.
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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, July 2020. http://dx.doi.org/10.52012/tyob9090.
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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden engineering participation. Knowledge generated around using peer-facilitated instruction at two-year colleges can improve underrepresented students' success and participation in engineering across a broad range of institutions. Students in the program participated in peer-facilitated recitation sessions linked to fundamental engineering courses, such as engineering analysis, statics, and dynamics. These courses have the highest failure rate among women and underrepresented minority students. As a mixed-methods evaluation study, student engagement was measured as students' comfort with asking questions, collaboration with peers, and applying mathematics concepts. SPSS was used to analyze pre-and post-surveys for statistical significance. Qualitative data were collected through classroom observations and focus group sessions with recitation leaders. Semi-structured interviews were conducted with faculty members and students to understand their experiences in the program. Findings revealed that women students had marginalization and intimidation perceptions primarily from courses with significantly more men than women. However, they shared numerous strategies that could support them towards success through the engineering pathway. Women and underrepresented students perceived that they did not have a network of peers and faculty as role models to identify within engineering disciplines. The recitation sessions had a positive social impact on Hispanic women. As opportunities to collaborate increased, Hispanic womens' social engagement was expected to increase. This social engagement level has already been predicted to increase women students' persistence and retention in engineering and result in them not leaving the engineering pathway. An analysis of quantitative survey data from students in the three engineering courses revealed a significant effect of race and ethnicity for comfort in asking questions in class, collaborating with peers outside the classroom, and applying mathematical concepts. Further examination of this effect for comfort with asking questions in class revealed that comfort asking questions was driven by one or two extreme post-test scores of Asian students. A follow-up ANOVA for this item revealed that Asian women reported feeling excluded in the classroom. However, it was difficult to determine whether these differences are stable given the small sample size for students identifying as Asian. Furthermore, gender differences were significant for comfort in communicating with professors and peers. Overall, women reported less comfort communicating with their professors than men. Results from student metrics will inform faculty professional development efforts to increase faculty support and maximize student engagement, persistence, and retention in engineering courses at community colleges. Summative results from this project could inform the national STEM community about recitation support to further improve undergraduate engineering learning and educational research.