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A Generalized Prototyping Framework for Engineering Design and Advanced Manufacturing: From Ideation to Validation

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Prototyping plays a central role in engineering design by supporting creativity, modeling, experimentation, and validation under conditions of uncertainty. However, existing prototyping approaches remain fragmented across disciplines, with limited integration between design activities, fidelity selection, and decision-making processes. This lack of coherence makes it difficult to systematically guide prototyping across different stages of the engineering design lifecycle. This paper proposes a generalized, context-sensitive prototyping framework developed through a structured and critical synthesis of engineering design literature. The framework integrates four iterative stages: creativity and concept generation, modeling and analysis, prototyping strategy and execution, and experimental validation. It further incorporates key dimensions influencing prototyping decisions, including fidelity levels, risk considerations, stakeholder involvement, and uncertainty management. The framework is derived through thematic analysis of peer-reviewed literature spanning foundational prototyping models and recent developments in digital engineering, rapid prototyping, and AI-supported design. Representative case examples are used to illustrate the applicability of the framework across different engineering contexts. The contribution of this work is a unified conceptual and process-oriented framework that clarifies relationships among prototyping activities and provides a structured perspective for understanding prototyping under uncertainty. This study also identifies limitations of current approaches and outlines directions for future research in adaptive and data-driven prototyping systems.
Title: A Generalized Prototyping Framework for Engineering Design and Advanced Manufacturing: From Ideation to Validation
Description:
Prototyping plays a central role in engineering design by supporting creativity, modeling, experimentation, and validation under conditions of uncertainty.
However, existing prototyping approaches remain fragmented across disciplines, with limited integration between design activities, fidelity selection, and decision-making processes.
This lack of coherence makes it difficult to systematically guide prototyping across different stages of the engineering design lifecycle.
This paper proposes a generalized, context-sensitive prototyping framework developed through a structured and critical synthesis of engineering design literature.
The framework integrates four iterative stages: creativity and concept generation, modeling and analysis, prototyping strategy and execution, and experimental validation.
It further incorporates key dimensions influencing prototyping decisions, including fidelity levels, risk considerations, stakeholder involvement, and uncertainty management.
The framework is derived through thematic analysis of peer-reviewed literature spanning foundational prototyping models and recent developments in digital engineering, rapid prototyping, and AI-supported design.
Representative case examples are used to illustrate the applicability of the framework across different engineering contexts.
The contribution of this work is a unified conceptual and process-oriented framework that clarifies relationships among prototyping activities and provides a structured perspective for understanding prototyping under uncertainty.
This study also identifies limitations of current approaches and outlines directions for future research in adaptive and data-driven prototyping systems.

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