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Article
Publication date: 12 March 2018

Jingbin Hao, Xin Chen, Hao Liu and Shengping Ye

To remanufacture a disused part, a hybrid process needs to be taken in part production. Therefore, a reasonable machining route is necessary to be developed for the hybrid…

Abstract

Purpose

To remanufacture a disused part, a hybrid process needs to be taken in part production. Therefore, a reasonable machining route is necessary to be developed for the hybrid process. This paper aims to develop a novel process planning algorithm for additive and subtractive manufacturing (ASM) system to achieve this purpose.

Design/methodology/approach

First, a skeleton of the model is generated by using thinning algorithm. Then, the skeleton tree is constructed based on topological structure and shape feature. Further, a feature matching algorithm is developed for recognizing the different features between the initial model and the final model based on the skeleton tree. Finally, a reasonable hybrid machining route of the ASM system is generated in consideration of the machining method of each different sub-feature.

Findings

This paper proposes a hybrid process planning algorithm for the ASM system. Further, it generates new process planning insights on the hybrid process service provider market.

Practical implications

The proposed process planning algorithm enables engineers to obtain a proper hybrid machining route before product fabrication. And thereby, it extends the machining capability of the hybrid process to manufacture some parts accurately and efficiently.

Originality/value

This study addresses one gap in the hybrid process literature. It develops the first hybrid process planning strategy for remanufacturing of disused parts based on skeleton tree matching, which generates a more proper hybrid machining route than the currently available hybrid strategy studies. Also, this study provides technical support for the ASM system to repair damaged parts.

Details

Rapid Prototyping Journal, vol. 24 no. 2
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 3 May 2016

Liya Wang, Yang Zhao, Yaoming Zhou and Jingbin Hao

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

Abstract

Purpose

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

Design/methodology/approach

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Findings

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

Research limitations/implications

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

Originality/value

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

Details

Circuit World, vol. 42 no. 2
Type: Research Article
ISSN: 0305-6120

Keywords

Article
Publication date: 8 March 2011

Jingbin Hao, Liang Fang and Robert E. Williams

Rapid prototyping (RP) of large‐scale solid models requires the stereolithographic (STL) file to be precisely partitioned. Especially, the selection of cutting positions is…

1014

Abstract

Purpose

Rapid prototyping (RP) of large‐scale solid models requires the stereolithographic (STL) file to be precisely partitioned. Especially, the selection of cutting positions is critical for the fabrication and assembly of sub‐models. The purpose of this paper is to present an efficient curvature‐based partitioning for selecting the best‐fit loop and decomposing the large complex model into smaller and simpler sub‐models with similar‐shaped joints, which facilitate the final assembly.

Design/methodology/approach

The partition algorithm is benefited from curvature analysis of the model surface, including extracting the feature edges and constructing the feature loops. The efficiency enhancement is achieved by selecting the best‐fit loop and constructing the similar‐shape joints. The utility of the algorithm is demonstrated by the fabrication of large‐scale rapid prototypes.

Findings

By using the proposed curvature‐based partition algorithm, the reasonability and efficiency of STL model partition can be greatly improved, and the complexity of sub‐models has been reduced. It is found that the large‐scale model is efficiently partitioned and the sub‐models are precisely assembled using the proposed partitioning.

Originality/value

The curvature‐based partition algorithm is used in the RP field for the first time. Based on the curvature‐based partitioning, the reasonability and efficiency of large‐scale RP is addressed in this paper.

Details

Rapid Prototyping Journal, vol. 17 no. 2
Type: Research Article
ISSN: 1355-2546

Keywords

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