Search results

1 – 6 of 6
Article
Publication date: 14 June 2018

Yicha Zhang, Alain Bernard, Ramy Harik and Georges Fadel

This paper aims to introduce a new nesting scheme to better describe and solve the single-layer-part packing problem in additive manufacturing (AM).

Abstract

Purpose

This paper aims to introduce a new nesting scheme to better describe and solve the single-layer-part packing problem in additive manufacturing (AM).

Design/methodology/approach

Parallel nesting scheme using two-dimensional (2D) changeable projection profiles is developed. At first, a feature-based orientation optimization method is used to identify a set of practical alternative build orientations for each part to ensure the part quality. Then, 2D polygons are used to represent each part’s projection profiles under its alternative build orientations. Finally, a parallel layout searching algorithm is developed to identify the optimal part layout by using 2D changeable projection profiles.

Findings

The proposed nesting scheme can both guarantee the production quality for each part and search the optimal part layout with larger probability but less computational time.

Originality/value

With the use of changeable 2D projection profiles, this method conducts 2D computation to solve the single-layer-part packing problem with five degrees of freedom, which saves much computation cost and, at the same time, guarantees the production quality of each part. By adding specific nesting objectives or constraints and heuristic searching knowledge to the proposed nesting scheme, practical nesting software can be developed to meet the specific nesting or packing requirements for industrial AM machines.

Details

Rapid Prototyping Journal, vol. 24 no. 5
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 14 December 2018

Yicha Zhang, Ramy Harik, Georges Fadel and Alain Bernard

For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and…

556

Abstract

Purpose

For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination.

Design/methodology/approach

The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined.

Findings

A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency.

Originality/value

The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.

Details

Rapid Prototyping Journal, vol. 25 no. 1
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 21 March 2016

Yicha Zhang, Alain Bernard, Ravi Kumar Gupta and Ramy Harik

The purpose of this paper is to present research work based on the authors’ conceptual framework reported in the VRAP Conference 2013. It is related with an efficient method to…

1320

Abstract

Purpose

The purpose of this paper is to present research work based on the authors’ conceptual framework reported in the VRAP Conference 2013. It is related with an efficient method to obtain an optimal part build orientation for additive manufacturing (AM) by using AM features with associated AM production knowledge and multi-attribute decision-making (MADM). The paper also emphasizes the importance of AM feature and the implied AM knowledge in AM process planning.

Design/methodology/approach

To solve the orientation problem in AM, two sub-tasks, the generation of a set of alternative orientations and the identification of an optimal one within the generated list, should be accomplished. In this paper, AM feature is defined and associated with AM production knowledge to be used for generating a set of alternative orientations. Key attributes for the decision-making of the orientation problem are then identified and used to represent those generated orientations. Finally, an integrated MADM model is adopted to find out the optimal orientation among the generated alternative orientations.

Findings

The proposed method to find out an optimal part build orientation for those parts with simple or medium complex geometric shapes is reasonable and efficient. It also has the potential to deal with more complex parts with cellular or porous structures in a short time by using high-performance computers.

Research limitations/implications

The proposed method is a proof-of-concept. There is a need to investigate AM feature types and the association with related AM production knowledge further so as to suite the context of orientating parts with more complex geometric features. There are also research opportunities for developing more advanced algorithms to recognize AM features and generate alternative orientations and refine alternative orientations.

Originality/value

AM feature is defined and introduced to the orientation problem in AM for generating the alternative orientations. It is also used as one of the key attributes for decision-making so as to help express production requirements on specific geometric features of a desired part.

Details

Rapid Prototyping Journal, vol. 22 no. 2
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 2 March 2015

Ramy Harik, Alipio Nicolas, Mohamed Dassouki and Alain Bernard

Biomimetic study existing natural biological elements to produce engineering products with similar performance and abilities. The purpose of this paper is to highlight biomimetic…

Abstract

Purpose

Biomimetic study existing natural biological elements to produce engineering products with similar performance and abilities. The purpose of this paper is to highlight biomimetic studies to produce a new type of airplanes: adding remiges, bending ability and flapping mechanisms.

Design/methodology/approach

The used methodology was to thoroughly investigate the literature, to define the proper endurance and fatigue parameters, to perform a series of numerical studies and report improvement percentages relevant to defined parameters.

Findings

By adding remiges and the bending mechanism, the authors managed to reach – numerically – the preset desired structure goal. Efficiency increased using remiges with less drag force. In addition, with the help of the bending wing technique, the drag force was improved. The flapping mechanism showed high vibration rates. Last but not least, applying multiple winglets gave a better optimization of the endurance parameter.

Research limitations/implications

Research is conducted at a university without any research facilities. No laboratories exist, and acquiring research papers is mostly difficult and costly.

Originality/value

The research study is original in the sense of its numerical investigation. Proposing biomimetic was at the heart of the airplane invention and cannot be stated as an original contribution. Rather the field has been recently abandoned, and performing this major literature review can be considered as original in a sense it summarizes recent to somewhat old advancement.

Details

Engineering Computations, vol. 32 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Content available
498

Abstract

Details

Engineering Computations: International Journal for Computer-Aided Engineering and Software, vol. 32 no. 1
Type: Research Article
ISSN: 0264-4401

Abstract

Details

A Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education
Type: Book
ISBN: 978-1-78973-900-8

1 – 6 of 6