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Article
Publication date: 12 September 2016

Taiwen Feng, Di Cai, Zhenglin Zhang and Bing Liu

The purpose of this paper is to examine the joint influence of technological newness (TN) and market newness (MN) on the relationship between customer involvement (CI) and new…

1848

Abstract

Purpose

The purpose of this paper is to examine the joint influence of technological newness (TN) and market newness (MN) on the relationship between customer involvement (CI) and new product performance.

Design/methodology/approach

The authors employed hierarchical moderated regression analysis to test the hypothesized relationships using survey data collected from 214 Chinese manufacturing firms.

Findings

The authors found that the impact of CI on new product performance varies across the different configurations of TN and MN. Specifically, the performance effect of CI is most positive under low TN and high MN, while the performance effect is least positive under low TN and low MN.

Originality/value

This study enriches CI research by identifying different configurations of product innovativeness that augment or limit the value of CI.

Details

Industrial Management & Data Systems, vol. 116 no. 8
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 20 June 2017

Chor Yen Yap, Hongyi Kenneth Tan, Zhenglin Du, Chee Kai Chua and Zhili Dong

Selective laser melting (SLM) is an additive manufacturing technology that is gaining industrial and research interest as it can directly fabricate near full density metallic…

952

Abstract

Purpose

Selective laser melting (SLM) is an additive manufacturing technology that is gaining industrial and research interest as it can directly fabricate near full density metallic components. The paper aims to identify suitable process parameters for SLM of processing of pure nickel powder and to study the microstructure of such products. The study also aims to characterize the microhardness and tensile properties of pure nickel produced by SLM.

Design/methodology/approach

A 24 factorial design experiment was carried out to identify the most significant factors on the resultant porosity of nickel parts. A subsequent experiment was carried out with a laser power of 350 W. The scanning speeds and hatch spacings were varied.

Findings

Scanning speed and hatch spacing have significant effects on the porosity of SLM components. A high relative density of 98.9 per cent was achieved, and microhardness of 140 to 160 Hv was obtained from these samples. A tensile strength 452 MPa was obtained.

Research limitations/implications

As the energy input levels were made in steps of 20 J/mm3 for the optimization study, the true optimal combination of parameters may have been missed. Therefore, researchers are encouraged to test the parameters with smaller variations in energy levels.

Practical implications

The paper provides a set of optimized parameters for the SLM of pure nickel. This study enables the three-dimensional (3D) printing of objects with nickel, which has applications in chemical catalyses and in microelectromechanical systems with its magnetostrictive properties.

Originality value

This research is the first in direct processing of pure nickel using SLM, with the identification of suitable process parameters. The study also provides an understanding of the porosity, microhardness, strength and microstructure of SLM produced nickel parts. This work paves the way for standardization of 3D printed nickel components and enables the applications of pure nickel via SLM.

Details

Rapid Prototyping Journal, vol. 23 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 11 February 2020

Zhenglin Du, Hui-Chi Chen, Ming Jen Tan, Guijun Bi and Chee Kai Chua

In recent years, additive manufacturing techniques have attracted much research attention because of their ability to fabricate customised parts with complex geometry. The range…

Abstract

Purpose

In recent years, additive manufacturing techniques have attracted much research attention because of their ability to fabricate customised parts with complex geometry. The range of composites suitable for laser-based powder bed fusion technique is limited, and has not been investigated yet. This paper aims to study the fabrication of AlSi10Mg reinforced with nAl2O3 using the laser-based powder bed fusion technique.

Design/methodology/approach

An experimental approach was used to investigate the densification of AlSi10Mg–nAl2O3 composites using laser-based powder bed fusion technique. Optimisation of the porosity was performed, and microstructure evolution was evaluated.

Findings

In this study, laser volumetric energy density (approximately 109 J/mm3) was found to be required for the fabrication of AlSi10Mg–nAl2O3 composites with a relative volumetric density approximating 99%. The use of laser volumetric energy density resulted in larger grains. Columnar grain structure was observed via the use of electron backscatter diffraction mapping.

Originality/value

This paper examines the processing of new aluminium composite material suitable for the fabrication via the laser-based powder bed fusion technique.

Details

Rapid Prototyping Journal, vol. 26 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 8 February 2016

Xingxin Liang, Zhenglin Liu, Huanjie Wang, Xuhui Zhou and Xincong Zhou

The purpose of this study is to investigate the effects of partial texture location and dimple depth on load carrying capacity (LCC), friction coefficient and circumferential flow…

Abstract

Purpose

The purpose of this study is to investigate the effects of partial texture location and dimple depth on load carrying capacity (LCC), friction coefficient and circumferential flow of journal bearing.

Design/methodology/approach

Based on the Navier-Stokes equation, the methodology used computational fluid dynamics (CFD). A phase change boundary condition was applied on fluid domain, and the negative pressure at divergent region of oil film was considered.

Findings

It has been found that texture located at lubricant inlet area can improve the performance of the bearing, and the effect of shallow dimples is superior to the deep ones. However, the bearing performance will be reduced due to the texture located at the maximum pressure area. When texture is located at the lubricant outlet area, there will be two different situations: the part of the texture located within the oil film divergent area can improve the LCC, while the part that is beyond the divergent region will make the LCC decrease.

Originality/value

The lower-half oil film model was established only in this study to analyze the hydrodynamic lubrication performance of partial textured journal bearing, and the lower-half oil film was divided into three parts. A new cavitation algorithm was introduced to deal with the negative pressure. The formula for calculating the friction of liquid film is refined, including the consideration of vapor phase. The simulation results show that the location of partial texture have a great influence on the bearing performance.

Details

Industrial Lubrication and Tribology, vol. 68 no. 1
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 9 May 2023

Junchao Zhu, GuangCheng Wei, Chen Zong and DaKuan Xin

This paper aim to take the ship shaft stern bearing as the research object, and studies the influence of journal axial vibration on bearing dynamic characteristics under different…

Abstract

Purpose

This paper aim to take the ship shaft stern bearing as the research object, and studies the influence of journal axial vibration on bearing dynamic characteristics under different misaligned angles and rotation speeds.

Design/methodology/approach

Computational fluid dynamics (CFD) and harmonic excitation method were used to build bearing unstable lubrication model, and the dynamic mesh technology was used in calculation.

Findings

The results indicate that journal axial vibration has a significant effect on bearing dynamic characteristics, like maximum oil film pressure, bearing stiffness and damping coefficients, and the effect is positively correlated with journal misaligned angle. The effect of shaft rotation speed and journal axial vibration on bearing dynamics characteristics are independent; they have no coupling. Bearing axial stiffness is mainly affected by the journal axial displacement, bearing axial damping is mainly affected by journal axial velocity and they are positively correlated with the misaligned angle. The influence of rotational speed on bearing axial stiffness and axial damping is not obvious.

Originality/value

This paper establishes the bearing dynamic model by CFD and harmonic excitation method with consideration of cavitation effect and analyzing the influence of journal axial vibration on the dynamic characteristics. The results are benefit to the design of ship propulsion shaft and the selection of stern bearing. Also, they are of great significance to improve the operation stability of the shaft bearing system and the vitality of the ship.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0337/

Details

Industrial Lubrication and Tribology, vol. 75 no. 5
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 13 November 2019

David Kimera and Fillemon Nduvu Nangolo

The purpose of this paper is to review maintenance practices, tools and parameters for marine mechanical systems that can be classified as plant, machinery and equipment (PME). It…

Abstract

Purpose

The purpose of this paper is to review maintenance practices, tools and parameters for marine mechanical systems that can be classified as plant, machinery and equipment (PME). It provides an insight for the maintenance crew on which maintenance parameters and practices are critical for a given PME systems.

Design/methodology/approach

The review paper characterizes the various maintenance parameters and maintenance practices used onshore and offshore for PME and identifies the possible gaps.

Findings

A variety of maintenance techniques are being used in the marine industry such as corrective maintenance, preventive maintenance and condition-based maintenance. As marine vehicles (MV) get older, the most important maintenance parameters become maintenance costs, reliability and safety. Maintenance models that have been developed in line with marine mechanical systems have been validated using a single system, whose outcome could be different if another PME system is used for validation.

Research limitations/implications

There is a limited literature on MV maintenance parameters and maintenance characterization regarding mechanical systems. The maintenance practices or strategies of marine mechanical systems should be based on maintenance parameters that suit the marine industry for a given PME.

Originality/value

Based on the available literature, the paper provides a variety of maintenance framework, parameters and practices for marine mechanical systems. The paper further gives an insight on what maintenance parameters, strategies and platforms are given preference in the shipping industry.

Details

Journal of Quality in Maintenance Engineering, vol. 26 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 29 April 2014

Wael M. El-Medany

With the rapid development in wired and wireless networks, the demand for network security system is rising rapidly due to more and more new applications introduced. The main…

Abstract

Purpose

With the rapid development in wired and wireless networks, the demand for network security system is rising rapidly due to more and more new applications introduced. The main factors that rate the encryption algorithms are its ability to secure and protect data against attacks, its speed and efficiency. In this paper, a reconfigurable network security design using multi-mode data encryption standard (DES) algorithm has been implemented with low complexity and low cost, which will also reduce the speed. The paper aims to discuss these issues.

Design/methodology/approach

The design can be easily reconfigured to 3DES (triple DES) which is more secure and more powerful in encryption and decryption, as one of the trick in designing 3DES is to reuse three instances of DES. The design can be used for wired and wireless network applications, and it has been described using VHDL and implemented in a reconfigurable Programmable System-on-Chip (PSoC). The hardware implementation has targeted Xilinx Spartan XC3S700-AN FPGA device.

Findings

The main idea of reducing the complexity for the hardware implementation is by optimizing the number of logic gates and LUTs of the design. The number of logic gates can be decreased by changing the way of writing the VHDL code and by optimizing the size of the chip.

Originality/value

The design has been tested in simulation and hardware levels, and the simulation results and performance are discussed.

Details

Journal of Engineering, Design and Technology, vol. 12 no. 2
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 10 August 2021

Deepa S.N.

Limitations encountered with the models developed in the previous studies had occurrences of global minima; due to which this study developed a new intelligent ubiquitous…

233

Abstract

Purpose

Limitations encountered with the models developed in the previous studies had occurrences of global minima; due to which this study developed a new intelligent ubiquitous computational model that learns with gradient descent learning rule and operates with auto-encoders and decoders to attain better energy optimization. Ubiquitous machine learning computational model process performs training in a better way than regular supervised learning or unsupervised learning computational models with deep learning techniques, resulting in better learning and optimization for the considered problem domain of cloud-based internet-of-things (IOTs). This study aims to improve the network quality and improve the data accuracy rate during the network transmission process using the developed ubiquitous deep learning computational model.

Design/methodology/approach

In this research study, a novel intelligent ubiquitous machine learning computational model is designed and modelled to maintain the optimal energy level of cloud IOTs in sensor network domains. A new intelligent ubiquitous computational model that learns with gradient descent learning rule and operates with auto-encoders and decoders to attain better energy optimization is developed. A new unified deterministic sine-cosine algorithm has been developed in this study for parameter optimization of weight factors in the ubiquitous machine learning model.

Findings

The newly developed ubiquitous model is used for finding network energy and performing its optimization in the considered sensor network model. At the time of progressive simulation, residual energy, network overhead, end-to-end delay, network lifetime and a number of live nodes are evaluated. It is elucidated from the results attained, that the ubiquitous deep learning model resulted in better metrics based on its appropriate cluster selection and minimized route selection mechanism.

Research limitations/implications

In this research study, a novel ubiquitous computing model derived from a new optimization algorithm called a unified deterministic sine-cosine algorithm and deep learning technique was derived and applied for maintaining the optimal energy level of cloud IOTs in sensor networks. The deterministic levy flight concept is applied for developing the new optimization technique and this tends to determine the parametric weight values for the deep learning model. The ubiquitous deep learning model is designed with auto-encoders and decoders and their corresponding layers weights are determined for optimal values with the optimization algorithm. The modelled ubiquitous deep learning approach was applied in this study to determine the network energy consumption rate and thereby optimize the energy level by increasing the lifetime of the sensor network model considered. For all the considered network metrics, the ubiquitous computing model has proved to be effective and versatile than previous approaches from early research studies.

Practical implications

The developed ubiquitous computing model with deep learning techniques can be applied for any type of cloud-assisted IOTs in respect of wireless sensor networks, ad hoc networks, radio access technology networks, heterogeneous networks, etc. Practically, the developed model facilitates computing the optimal energy level of the cloud IOTs for any considered network models and this helps in maintaining a better network lifetime and reducing the end-to-end delay of the networks.

Social implications

The social implication of the proposed research study is that it helps in reducing energy consumption and increases the network lifetime of the cloud IOT based sensor network models. This approach helps the people in large to have a better transmission rate with minimized energy consumption and also reduces the delay in transmission.

Originality/value

In this research study, the network optimization of cloud-assisted IOTs of sensor network models is modelled and analysed using machine learning models as a kind of ubiquitous computing system. Ubiquitous computing models with machine learning techniques develop intelligent systems and enhances the users to make better and faster decisions. In the communication domain, the use of predictive and optimization models created with machine learning accelerates new ways to determine solutions to problems. Considering the importance of learning techniques, the ubiquitous computing model is designed based on a deep learning strategy and the learning mechanism adapts itself to attain a better network optimization model.

Details

International Journal of Pervasive Computing and Communications, vol. 18 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

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