Chapter 10
Tube Hydro-Forming Process Design
Based on Knowledge-Based Engineering
Yulong Ge and Zhiwei Ye
Abstract The principal objectives of a knowledge-based engineering (KBE) system
are to solve a particular problem by reusing experience and knowledge in a flexible
way meanwhile retain the new ones for future problems. This work presents KBE
methodology for tube hydro-forming process design. Hydro-formed tubular parts are
more complicated than common metal stamped parts because they are composed of
groups bending, expansion and local forming features. Hydro-forming process design
identifies and sequences the necessary operations and then producing appropriate
die sets. Case-based reasoning (CBR) is employed into forming process planning
to generate a hybrid KBE system for reuses existing cases to develop new designs.
A part is defined using a feature-based representation composed of geometric and
material parameters. Self-organized map algorithm is used as the retrieval engine in
CBR. Combining the common rules of tube hydro-forming, the process route and the
die layout can be determined quickly. This methodology can accelerate the design
and manufacturing efficiently and assist engineers in preserving tacit knowledge of
tube hydro-forming and accelerates the parts design and manufacturing.
Keywords Tube hydroforming · Process planning · Case-based reasoning ·
Self-organized map · Feature extraction
10.1 Introduction
The tube hydro-forming (THF) is a near net shape forming process technology which
is widely adopted to produce tubular parts in aviation and automotive industries. It
can raise the strength-weight ratio and rigidity with less post-processes [1].
Y. Ge (B)
School of Vehicle and Mobility, Tsinghua University, Beijing 100003, China
e-mail: aaronge88@126.com
Z. Ye
Guangxi Automobile Holdings Limited, Liuzhou 545000, China
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
J. Xu and K. M. Pandey (eds.), Mechanical Engineering and Materials,
Mechanisms and Machine Science 100,
https://doi.org/10.1007/978-3-030-68303-0_10
115
Tube Hydro-Forming Process Design
Based on Knowledge-Based Engineering
Yulong Ge and Zhiwei Ye
Abstract The principal objectives of a knowledge-based engineering (KBE) system
are to solve a particular problem by reusing experience and knowledge in a flexible
way meanwhile retain the new ones for future problems. This work presents KBE
methodology for tube hydro-forming process design. Hydro-formed tubular parts are
more complicated than common metal stamped parts because they are composed of
groups bending, expansion and local forming features. Hydro-forming process design
identifies and sequences the necessary operations and then producing appropriate
die sets. Case-based reasoning (CBR) is employed into forming process planning
to generate a hybrid KBE system for reuses existing cases to develop new designs.
A part is defined using a feature-based representation composed of geometric and
material parameters. Self-organized map algorithm is used as the retrieval engine in
CBR. Combining the common rules of tube hydro-forming, the process route and the
die layout can be determined quickly. This methodology can accelerate the design
and manufacturing efficiently and assist engineers in preserving tacit knowledge of
tube hydro-forming and accelerates the parts design and manufacturing.
Keywords Tube hydroforming · Process planning · Case-based reasoning ·
Self-organized map · Feature extraction
10.1 Introduction
The tube hydro-forming (THF) is a near net shape forming process technology which
is widely adopted to produce tubular parts in aviation and automotive industries. It
can raise the strength-weight ratio and rigidity with less post-processes [1].
Y. Ge (B)
School of Vehicle and Mobility, Tsinghua University, Beijing 100003, China
e-mail: aaronge88@126.com
Z. Ye
Guangxi Automobile Holdings Limited, Liuzhou 545000, China
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
J. Xu and K. M. Pandey (eds.), Mechanical Engineering and Materials,
Mechanisms and Machine Science 100,
https://doi.org/10.1007/978-3-030-68303-0_10
115