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\"This text demonstrates that symbolic representation, and related problem-solving methods, offer significant opportunities to clarify and articulate concepts of design\"--Provided by publisher.

Finite Element Analysis (FEA) has been widely implemented by the automotive industry as a productivity tool for design engineers to reduce both development time and cost. This essential work serves as a guide for FEA as a design tool and addresses the specific needs of design engineers to improve productivity. It provides a clear presentation that will help practitioners to avoid mistakes. Easy to use examples of FEA fundamentals are clearly presented that can be simply applied during the product development process. The FEA process is fully explored in this fundamental and practical approach that includes: Understanding FEA basics; Commonly used modeling techniques; Application of FEA in the design process; Fundamental errors and their effect on the quality of results; Hands-on simple and informative exercises. This indispensable guide provides design engineers with proven methods to analyze their own work while it is still in the form of easily modifiable CAD models. Simple and informative exercises provide examples for improving the process to deliver quick turnaround times and prompt implementation.

The one-stop guide to SketchUp for architects, designers, and builders. SketchUp is the tool of choice for architects, interior designers, and construction professionals. Though the basics are simple to understand, getting the most out of it requires deeper instruction and guidance.

The present volume comprises a collection of peer-reviewed papers covering manufacture and production, engineering materials, CAD/CAM/CAE, robotics, automation and control, environment-friendly design and manufacture, web/internet technologies, artificial intelligence and smart computing in design and manufacture, enterprise, management, and other related topics. This work will therefore be invaluable to production and research engineers, but also to research students and academics interested in the field.

Finite Element Analysis (FEA) has been widely implemented by the automotive industry as a productivity tool for design engineers to reduce both development time and cost. This essential work serves as a guide for FEA as a design tool and addresses the specific needs of design engineers to improve productivity. It provides a clear presentation that will help practitioners to avoid mistakes. Easy to use examples of FEA fundamentals are clearly presented that can be simply applied during the product development process. The FEA process is fully explored in this fundamental and practical approach that includes: Understanding FEA basicsCommonly used modeling techniquesApplication of FEA in the design processFundamental errors and their effect on the quality of resultsHands-on simple and informative exercisesThis indispensable guide provides design engineers with proven methods to analyze their own work while it is still in the form of easily modifiable CAD models. Simple and informative exercises provide examples for improving the process to deliver quick turnaround times and prompt implementation.

Purpose: The purpose of this study is to characterize, analyze, and demonstrate machine-understandable semantic process for validating, integrating, and processing technical design information. This establishes both a vision and tools for information reuse and semi-automatic processing in engineering design projects, including virtual machine laboratory applications with generated components. Design/methodology/approach: The process model has been developed iteratively in terms of action research, constrained by the existing technical design practices and assumptions (design documents, expert feedback), available technologies (pre-studies and experiments with scripting and pipeline tools), benchmarking with other process models and methods (notably the RUP and DITA), and formal requirements (computability and the critical information paths for the generated applications). In practice, the work includes both quantitative and qualitative components. Findings: Technical design processes may be greatly enhanced in terms of semantic process thinking, by enriching design information, and automating information validation and transformation tasks. Contemporary design information, however, is mainly intended for human consumption, and needs to be explicitly enriched with the currently missing data and interfaces. In practice, this may require acknowledging the role of technical information or knowledge engineer, to lead the development of the semantic design information process in a design organization. There is also a trade-off between machine-readability and system complexity that needs to be studied further, both empirically and in theory. Research limitations/implications: The conceptualization of the semantic process is essentially an abstraction based on the idea of progressive design. While this effectively allows implementing semantic processes with, e.g., pipeline technologies, the abstraction is valid only when technical design is organized into reasonably distinct tasks. Practical implications: Our work points out a best practice for technical information management in progressive design that can be applied on different levels. Social implications: Current design processes may be somewhat impaired by legacy practices that do not promote information reuse and collaboration beyond conventional task domains. Our work provides a reference model to analyze and develop design activities as formalized work-flows. This work should lead into improved industry design process models and novel CAD/CAM/PDM applications, thereby strengthening industry design processes. Originality/value: While extensively studied, semantic modeling in technical design has been largely dominated by the idea of capturing design artifacts without a clear rationale why this is done and what level of detail should be favored in models. In the semantic process presented in this article, the utility and the chief quality criteria of semantic models (of technical information and artifacts) are explicitly established by the semantic processing pipeline(s). This constructively explains the significance of semantic models as communication and information requirement interfaces, with concrete use cases.

Various topics relating to the following subject areas are covered: New Materials and Advanced Materials; Material Processing Technology; Product Design and Manufacturing Technology; Automation and Mechatronics; Environment & Energy.