Chang Product Design Modeling using CAD/CAE

The Computer Aided Engineering Design Series
1. Auflage 2014
ISBN: 978-0-12-398517-0
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 438 Seiten

Product Design Modeling using CAD/CAE is the third part of a four-part series. It is the first book to integrate discussion of computer design tools throughout the design process. Through this book, you will: - Understand basic design principles and all digital design paradigms - Understand computer-aided design, engineering, and manufacturing (CAD/CAE/CAM) tools available for various design-related tasks - Understand how to put an integrated system together to conduct all-digital design (ADD) - Provides a comprehensive and thorough coverage of essential elements for product modeling using the virtual engineering paradigm - Covers CAD/CAE in product design, including solid modeling, mechanical assembly, parameterization, product data management, and data exchange in CAD - Case studies and tutorial examples at the end of each chapter provide hands-on practice in implementing off-the-shelf computer design tools - Provides two projects showing the use of Pro/ENGINEER and SolidWorks to implement concepts discussed in the book

Dr. Kuang-Hua Chang is a David Ross Boyd Professor and Williams Companies Foundation Presidential Professor for the School of Aerospace and Mechanical Engineering (AME) at the University of Oklahoma. He received his PhD in Mechanical Engineering from the University of Iowa in 1990. His areas of interest include Virtual Prototyping, CAD, Fatigue and Reliability Analysis, Tools and Information Integration for Concurrent Design and Manufacturing, Solid Freeform Fabrication, and bioengineering applications. His research has been published in eight books and more than 150 articles in international journals and conference proceedings.

Autoren/Hrsg.

Chang, Kuang-Hua

Leseproben

Chapter 1

Introduction to e-Design

Abstract

The e-Design paradigm employs IT-enabled technology, including virtual prototyping, early in product development to support cross-functional analysis of performance, reliability, and costs, as well as quantitative trade-offs in decision making. Physical prototypes of the product design are then produced using rapid prototyping and computer numerical control. e-Design has the potential to shorten overall product development, improve product quality, and reduce product costs (1) by bringing together product performance, quality, and cost early in the design phase; (2) by supporting design decision making based on quantitative product performance data; and (3) by incorporating physical prototyping to support design verification and functional prototyping. This chapter introduces the e-Design paradigm and the components it comprises, including knowledge-based engineering and virtual and physical prototyping. Designs of a simple airplane engine and a high-mobility multipurpose wheeled vehicle are offered as illustrations.

Keywords

e-Design paradigmvirtual prototypingCAD parametric product modelmotion simulationproduct performancefatiguefracturereliabilityvirtual manufacturingtool integrationdecision makingproblem formulationdesign sensitivityparametric studytrade-offwhat-ifrapid prototypingCNC machiningairplane enginehigh-mobility multipurpose wheeled vehicleHMMWVhierarchical

Chapter Outline

1.1 Introduction

1.2 The e-Design paradigm

1.3 Virtual prototyping

1.3.1 Parameterized CAD product model

1.3.1.1 Parameterized product model

1.3.1.2 Analysis models

1.3.1.3 Motion simulation models

1.3.2 Product performance analysis

1.3.2.1 Motion analysis

1.3.2.2 Structural analysis

1.3.2.3 Fatigue and fracture analysis

1.3.2.4 Product reliability evaluations

1.3.3 Product virtual manufacturing

1.3.4 Tool integration

1.3.5 Design decision making

1.3.5.1 Design problem formulation

1.3.5.2 Design sensitivity analysis

1.3.5.3 Parametric study

1.3.5.4 Design trade-off analysis

1.3.5.5 What-if study

1.4 Physical prototyping

1.4.1 Rapid prototyping

1.4.2 CNC machining

1.5 Example: simple airplane engine

1.5.1 System-level design

1.5.2 Component-level design

1.5.3 Design trade-off

1.5.4 Rapid prototyping

1.6 Example: High-mobility multipurpose wheeled vehicle

1.6.1 Hierarchical product model

1.6.2 Preliminary design

1.6.3 Detail design

1.6.4 Design trade-off

1.7 Summary

Questions and exercises

References

Sources

Conventional product development employs a design-build-test philosophy. The sequentially executed development process often results in prolonged lead times and elevated product costs. The proposed e-Design paradigm employs IT-enabled technology for product design, including virtual prototyping (VP) to support a cross-functional team in analyzing product performance, reliability, and manufacturing costs early in product development, and in making quantitative trade-offs for design decision making. Physical prototypes of the product design are then produced using the rapid prototyping (RP) technique and computer numerical control (CNC) to support design verification and functional prototyping, respectively.

e-Design holds potential for shortening the overall product development cycle, improving product quality, and reducing product costs. It offers three concepts and methods for product development:

• Bringing product performance, quality, and manufacturing costs together early in design for consideration.

• Supporting design decision making based on quantitative product performance data.

• Incorporating physical prototyping techniques to support design verification and functional prototyping.

Introduction

A conventional product development process that is usually conducted sequentially suffers the problem of the design paradox (Ullman 1992). This refers to the dichotomy or mismatch between the design engineer's knowledge about the product and the number of decisions to be made (flexibility) throughout the product development cycle (see Figure 1.1). Major design decisions are usually made in the early design stage when the product is not very well understood. Consequently, engineering changes are frequently requested in later product development stages, when product design evolves and is better understood, to correct decisions made earlier.

FIGURE 1.1The Design Paradox.

Conventional product development is a design-build-test process. Product performance and reliability assessments depend heavily on physical tests, which involve fabricating functional prototypes of the product and usually lengthy and expensive physical tests. Fabricating prototypes usually involves manufacturing process planning and fixtures and tooling for a very small amount of production. The process can be expensive and lengthy, especially when a design change is requested to correct problems found in physical tests.

In conventional product development, design and manufacturing tend to be disjointed. Often, manufacturability of a product is not considered in design. Manufacturing issues usually appear when the design is finalized and tests are completed. Design defects related to manufacturing in process planning or production are usually found too late to be corrected. Consequently, more manufacturing procedures are necessary for production, resulting in elevated product cost.

With this highly structured and sequential process, the product development cycle tends to be extended, cost is elevated, and product quality is often compromised to avoid further delay. Costs and the number of engineering change requests (ECRs) throughout the product development cycle are often proportional according to the pattern shown in Figure 1.2. It is reported that only 8% of the total product budget is spent for design; however, in the early stage, design determines 80% of the lifetime cost of the product (Anderson 1990). Realistically, today's industries will not survive worldwide competition unless they introduce new products of better quality, at lower cost, and with shorter lead times. Many approaches and concepts have been proposed over the years, all with a common goal—to shorten the product development cycle, improve product quality, and reduce product cost.

A number of proposed approaches are along the lines of virtual prototyping (Lee 1999), which is a simulation-based method that helps engineers understand product behavior and make design decisions in a virtual environment. The virtual environment is a computational framework in which the geometric and physical properties of products are accurately simulated and represented. A number of successful virtual prototypes have been reported, such as Boeing's 777 jetliner, General Motors' locomotive engine, Chrysler's automotive interior design, and the Stockholm Metro’s Car 2000 (Lee 1999). In addition to virtual prototyping, the concurrent engineering (CE) concept and methodology have been studied and developed with emphasis on subjects such as product life cycle design, design for X-abilities (DFX), integrated product and process development (IPPD), and Six Sigma (Prasad 1996).

FIGURE 1.2Cost/ECR versus Time in a Conventional Design Cycle.

Although significant research has been conducted in improving the product development process and successful stories have been reported, industry at large is not taking advantage of new product development paradigms. The main reason is that small and mid-size companies cannot afford to develop an in-house computer tool environment like those of Boeing and the Big-Three automakers. On the other hand, commercial software tools are not tailored to meet the specific needs of individual companies; they often lack proper engineering capabilities to support specific product development needs, and most of them are not properly integrated. Therefore, companies are using commercial tools to support segments of their product development without employing the new design...