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Article
Publication date: 16 January 2017

Xiaotong Jiang, Xiaosheng Cheng, Qingjin Peng, Luming Liang, Ning Dai, Mingqiang Wei and Cheng Cheng

It is a challenge to print a model with the size that is larger than the working volume of a three-dimensional (3D) printer. The purpose of this paper is to present a feasible…

530

Abstract

Purpose

It is a challenge to print a model with the size that is larger than the working volume of a three-dimensional (3D) printer. The purpose of this paper is to present a feasible approach to divide a large model into small printing parts to fit the volume of a printer and then assemble these parts into the final model.

Design/methodology/approach

The proposed approach is based on the skeletonization and the minima rule. The skeleton of a printing model is first extracted using the mesh contraction and the principal component analysis. The 3D model is then partitioned preliminarily into many smaller parts using the space sweep method and the minima rule. The preliminary partition is finally optimized using the greedy algorithm.

Findings

The skeleton of a 3D model can effectively represent a simplified version of the geometry of the 3D model. Using a model’s skeleton to partition the model is an efficient way. As it is generally desirable to have segmentations at concave creases and seams, the cutting position should be located in the concave region. The proposed approach can partition large models effectively to well retain the integrity of meaningful parts.

Originality/value

The proposed approach is new in the rapid prototyping field using the model skeletonization and the minima rule. Based on the authors’ knowledge, there is no method that concerns the integrity of meaningful parts for partitioning. The proposed method can achieve satisfactory results by the integrity of meaningful parts and assemblability for most 3D models.

Details

Rapid Prototyping Journal, vol. 23 no. 1
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 7 March 2016

Zhishi Li, Huajin Wang, Sheng Zhang, Wei Zhao, Qinghuai Jiang, Mingqiang Wang, Jun Zhao and Wei Lu

– This paper aims to discuss how acrylic resin influences the smoke generation of intumescent flame retardant coatings.

237

Abstract

Purpose

This paper aims to discuss how acrylic resin influences the smoke generation of intumescent flame retardant coatings.

Design/methodology/approach

Thermal decomposition kinetics is used in this study to simulate the burning process. The thermal decomposition of acrylic resin can be identified in the intumescent coatings through the multi-peak fitting of derivative thermogravimetric (DTG) curves. The dormant influence of acrylic resin, combined with the smoke density, is calculated.

Findings

Multiple peaks fitting method of DTG curves helps estimate the decomposition process of acrylic resin in flame retardant coating. Combining DTG data with the smoking curve, smoking generation of acrylic resin during the combustion could be evaluated. The decomposition conversion rate of acrylic resin is 21.13 per cent. Acrylic resin generates 34.64 per cent of the total amount of smoke produced during the combustion of intumescent flame retardant coatings.

Research limitations/implications

All the other intumescent flame retardant coating systems could be studied using the same approach as that used in this work to achieve an improved understanding of the smoke generation process during combustion.

Practical implications

The method developed here provided a simple and practical solution to analyse the decomposition and smoking generation of acrylic resin in the coating mixtures. It also can be used to analyse any thermal decomposition process of any mixed compounds.

Originality/value

The analysis method to evaluate resin’s smoking generation of coating’s total generation is novel, and it could be applied in all kinds of coatings and mixtures to estimate the smoking generation of one composition.

Details

Pigment & Resin Technology, vol. 45 no. 2
Type: Research Article
ISSN: 0369-9420

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Article
Publication date: 19 May 2023

Mansour Soufi, Mehdi Fadaei, Mahdi Homayounfar, Hamed Gheibdoust and Hamidreza Rezaee Kelidbari

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as…

293

Abstract

Purpose

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

Design/methodology/approach

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

Findings

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

Originality/value

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.

Details

Management of Environmental Quality: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1477-7835

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Article
Publication date: 26 January 2010

Daren Yu and Xiaowu Lv

In recent years, high‐altitude/long‐endurance airship platforms have generated great interest as a means to provide communications and surveillance capabilities. The purpose of…

1131

Abstract

Purpose

In recent years, high‐altitude/long‐endurance airship platforms have generated great interest as a means to provide communications and surveillance capabilities. The purpose of this paper is to develop a model for airship conceptual design and help provide insight into the viability of high‐altitude/long‐endurance airships.

Design/methodology/approach

A configuration analysis model with the consideration of pressure difference, temperature difference, and helium purity, etc. was developed. The influences of the airship payload, size and area required of solar cell with environment and operation parameters, such as operation latitude, pressure difference, temperature difference, helium purity, seasons, latitude, and wind speed, etc. were analyzed.

Findings

The results show that the area of solar cell required for stratospheric airship is very large under the condition of low altitude, high latitude, wind, and in winter, etc. which might make the design of high‐altitude/long‐endurance airship an elusive goal. They also show that the solar cell efficiency is the key technology in the control of solar cell area required for airships, and the technology advances in regenerative fuel cells and propeller efficiency have significant effects among on the airship payload, size, and solar cell area required for airship.

Originality/value

The paper analyses the energy balance of the high‐altitude/long‐endurance airship.

Details

Aircraft Engineering and Aerospace Technology, vol. 82 no. 1
Type: Research Article
ISSN: 0002-2667

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Article
Publication date: 2 February 2015

Shuo Xiao, Yang Zhao, Yuan Cao, Haifeng Jiang and Wenliang Zhu

– This paper aims to deduce a set of theory computational formula, and optimize and improve the heat conductivity of vias in printed circuit boards of electrical power apparatus.

267

Abstract

Purpose

This paper aims to deduce a set of theory computational formula, and optimize and improve the heat conductivity of vias in printed circuit boards of electrical power apparatus.

Design/methodology/approach

The authors adopted numerical simulation and experimental measurement to verify the reliability of this formula.

Findings

Research result showed that 0.45 mm was the optimal bore diameter of vias; the conductivity had no obvious improvement when filling material was FR4 or Rogers, but if it was filled with texture of high thermal conductivity like soldering tine, the conductivity would improve a lot; the plating thickness of vias had a greater influence on thermal conductivity.

Originality/value

Through the theory computational formula, this paper studied the influence of aperture of vias, filled materials and thickness of copper plated on vias on thermal conductivity.

Details

Circuit World, vol. 41 no. 1
Type: Research Article
ISSN: 0305-6120

Keywords

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Article
Publication date: 22 June 2022

Suvarna Abhijit Patil and Prasad Kishor Gokhale

With the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network…

92

Abstract

Purpose

With the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network and by reducing the latency of transmitted data. The communications in IIoT and Industry 4.0 requires handshaking of multiple technologies for supporting heterogeneous networks and diverse protocols. IIoT applications may gather and analyse sensor data, allowing operators to monitor and manage production systems, resulting in considerable performance gains in automated processes. All IIoT applications are responsible for generating a vast set of data based on diverse characteristics. To obtain an optimum throughput in an IIoT environment requires efficiently processing of IIoT applications over communication channels. Because computing resources in the IIoT are limited, equitable resource allocation with the least amount of delay is the need of the IIoT applications. Although some existing scheduling strategies address delay concerns, faster transmission of data and optimal throughput should also be addressed along with the handling of transmission delay. Hence, this study aims to focus on a fair mechanism to handle throughput, transmission delay and faster transmission of data. The proposed work provides a link-scheduling algorithm termed as delay-aware resource allocation that allocates computing resources to computational-sensitive tasks by reducing overall latency and by increasing the overall throughput of the network. First of all, a multi-hop delay model is developed with multistep delay prediction using AI-federated neural network long–short-term memory (LSTM), which serves as a foundation for future design. Then, link-scheduling algorithm is designed for data routing in an efficient manner. The extensive experimental results reveal that the average end-to-end delay by considering processing, propagation, queueing and transmission delays is minimized with the proposed strategy. Experiments show that advances in machine learning have led to developing a smart, collaborative link scheduling algorithm for fairness-driven resource allocation with minimal delay and optimal throughput. The prediction performance of AI-federated LSTM is compared with the existing approaches and it outperforms over other techniques by achieving 98.2% accuracy.

Design/methodology/approach

With an increase of IoT devices, the demand for more IoT gateways has increased, which increases the cost of network infrastructure. As a result, the proposed system uses low-cost intermediate gateways in this study. Each gateway may use a different communication technology for data transmission within an IoT network. As a result, gateways are heterogeneous, with hardware support limited to the technologies associated with the wireless sensor networks. Data communication fairness at each gateway is achieved in an IoT network by considering dynamic IoT traffic and link-scheduling problems to achieve effective resource allocation in an IoT network. The two-phased solution is provided to solve these problems for improved data communication in heterogeneous networks achieving fairness. In the first phase, traffic is predicted using the LSTM network model to predict the dynamic traffic. In the second phase, efficient link selection per technology and link scheduling are achieved based on predicted load, the distance between gateways, link capacity and time required as per different technologies supported such as Bluetooth, Wi-Fi and Zigbee. It enhances data transmission fairness for all gateways, resulting in more data transmission achieving maximum throughput. Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation.

Findings

Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. It also shows that AI- and IoT-federated devices can communicate seamlessly over IoT networks in Industry 4.0.

Originality/value

The concept is a part of the original research work and can be adopted by Industry 4.0 for easy and seamless connectivity of AI and IoT-federated devices.

Details

International Journal of Pervasive Computing and Communications, vol. 20 no. 4
Type: Research Article
ISSN: 1742-7371

Keywords

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