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Article
Publication date: 12 February 2025

Wanbin Pan, Xinyue Chen, Wei Liu, Lixian Qiao, Haiying Kuang and Wen Feng Lu

This study aims to improve the stiffness of as-printed handles by finding appropriate printing orientations.

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Abstract

Purpose

This study aims to improve the stiffness of as-printed handles by finding appropriate printing orientations.

Design/methodology/approach

First, a series of benchmark handles is designed using Taguchi method. Then, for each uniformly sampled printing orientation, every benchmark handle is sliced and undergoes stiffness evaluation (i.e. displacement and mean stress) by using finite element analysis (FEA). This generates a substantial batch of handle-orientation-stiffness samples. With the data, an effective stiffness-prediction network is developed based on the artificial neural network. Finally, using the developed network, the particle swarm optimization is adapted to determine the optimized printing orientation for each input handle, aiming to improve its stiffness.

Findings

Compared with the common slicing software, the printing orientations proposed in this study, based on FEA, result in varying degrees of improvement in stiffness for four handles. Specifically, the displacement and mean stress are reduced by 16.86% and 18.14% on average. The experiments show that the approach has the potential to effectively improve the stiffness of a handle.

Originality/value

Although the anisotropic property in mechanics is unavoidable and difficult to formally describe in 3D printing, the proposed approach can effectively characterize the relationship between the stiffness and the printing orientation for each handle. And, it also can determine an optimized printing orientation for each handle to enhance its stiffness after printing.

Details

Rapid Prototyping Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 16 May 2023

Wanbin Pan, Hongyi Jiang, Shufang Wang, Wen Feng Lu, Weijuan Cao and Zhenlei Weng

This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time…

113

Abstract

Purpose

This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material.

Design/methodology/approach

The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time.

Findings

Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX.

Originality/value

A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.

Details

Rapid Prototyping Journal, vol. 29 no. 8
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 29 July 2014

Wanbin Pan, Yigang Wang and Peng Du

The purpose of this paper is to develop an automatic disassembly navigation approach for human interactions in the virtual environment to achieve accurate and effective virtual…

921

Abstract

Purpose

The purpose of this paper is to develop an automatic disassembly navigation approach for human interactions in the virtual environment to achieve accurate and effective virtual assembly path planning (VAPP).

Design/methodology/approach

First, to avoid the error-prone human interactions, a constraint-based disassembly method is presented. Second, to automatically provide the next operable part(s), a disassembly navigation mechanism is adopted. Finally, the accurate assembly path planning can be obtained effectively and automatically by inversing the ordered accurate disassembly paths, which are obtained interactively in the virtual environment aided with the disassembly navigation matrix.

Findings

The applications present that our approach can effectively avoid the error-prone interactive results and generate accurate and effective VAPP.

Research limitations/implications

There are several works that could be conducted to make our approach more general in the future: to further study the basic disassembly direction deducing rules to make the process of determining disassembly direction totally automatic, to consider the hierarchy of the parts in virtual reality system and to consider the space for assembly/disassembly tools or operators.

Originality/value

The approach has the following characteristics: a new approach to avoid the error-prone human interactions for accurate assembly path planning obtaining, a new constraint deducing method for determining the disassembly semantics automatically or semi-automatically is put forward and a new method for automatically identifying operable parts in VAPP is set forward.

Details

Assembly Automation, vol. 34 no. 3
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 27 June 2023

Bin Wang, Wanbin Chen, Shan Gao and Dezhi Wang

This paper aims to prepare a composite film on LY12 aluminum (Al) alloy by immersing in dodecyl phosphate and cerium nitrate solution by self-assembling methods. The effect of…

102

Abstract

Purpose

This paper aims to prepare a composite film on LY12 aluminum (Al) alloy by immersing in dodecyl phosphate and cerium nitrate solution by self-assembling methods. The effect of dipping sequence in dodecyl phosphate and cerium nitrate solution on the corrosion resistance of the composite film is studied.

Design/methodology/approach

The corrosion resistance of the dodecyl phosphate/cerium composite film is investigated by electrochemical measurement and film composition analysis.

Findings

The dipping sequence in dodecyl phosphate and cerium nitrate solutions has a significant impact on the corrosion resistance of the composite film. It shows best corrosion resistance by first dipping in dodecyl phosphate and then dipping in cerium nitrate solution.

Originality/value

The research shown in this work lays a scientific basis of the film preparation for industrial applications in the future.

Details

Anti-Corrosion Methods and Materials, vol. 70 no. 5
Type: Research Article
ISSN: 0003-5599

Keywords

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Article
Publication date: 7 June 2011

Tarek Helmy and Zeehasham Rasheed

Grid computing is gaining more significance in the high‐performance computing world. This concept leads to the discovery of solutions for complicated problems regarding the…

382

Abstract

Purpose

Grid computing is gaining more significance in the high‐performance computing world. This concept leads to the discovery of solutions for complicated problems regarding the diversity of available resources among different jobs in the grid. However, the major problem is the optimal job scheduling for heterogeneous resources, in which each job needs to be allocated to a proper grid's node with the appropriate resources. An important challenge is to solve optimally the scheduling problem, because the capability and availability of resources vary dynamically and the complexity of scheduling increases with the size of the grid. The purpose of this paper is to present a framework which combines the fuzzy C‐mean (FCM) clustering with an ant colony optimization (ACO) algorithm to improve the scheduling decision when the grid is heterogeneous.

Design/methodology/approach

In the proposed model, the FCM algorithm classifies the jobs into appropriate classes, and the ACO algorithm maps the jobs to the appropriate resources. The ACO is characterized by ant‐like mobile agents that cooperate and stochastically explore a network, iteratively building solutions based on their own memory and on the traces (pheromone levels) left by other agents.

Findings

The simulation is done by using historical information on jobs in a grid. The experimental results show that the proposed algorithm can allocate jobs more efficiently and more effectively than the traditional algorithms for scheduling policies.

Originality/value

The paper provides a scheduling model based on FCM clustering and ACO algorithm for grid scheduling. The authors compared the performance of the proposed algorithm with the performance of various job‐scheduling algorithms in the grid computing environment. The comparison results show that the proposed algorithm outperforms other algorithms and gives optimal results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

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