K. Jagannath, S. Sharma, N. Mohan, Achutha Kini and P. Prabhu
This paper presents manufacturing of metallic composites using stir-casting method. The setup details and manufacturing methodology are explained. Microstructure and…
Abstract
This paper presents manufacturing of metallic composites using stir-casting method. The setup details and manufacturing methodology are explained. Microstructure and characterization of graphite-tin composite is also included. The tensile strength and hardness improvement is observed in tin-graphite MMC with increase in weight percentage of graphite. Metal-matrix composites (MMC's) are now attracting enormous interest. One of the prime reasons for this is that significant advances have been made in recent years on the development of fabrication routes, which are economically attractive and generate material of high micro structural quality. In particular, it is possible to produce composites, which are relatively free from gross defects (Clyne and Mason, 1987; Smith and Froes, 1984; Rodes and Spuurling, 1985; Hunt, 1989; Ted Guo and Tsao, 2000). However, it depends on the ability of synthesizing them with a consistent reproducibility in microstructure and properties. With continual development in fabrication techniques, MMC's have been found to be suitable to replace some of the conventional metallic monolithic alloys.
Details
Keywords
Yong Pan, Qin Molin, Tengxiao Guo, Lin Zhang, Bingqing Cao, Junchao Yang, Wen Wang and Xufeng Xue
This paper aims to give an overview about the state of wireless passive surface acoustic wave (SAW) gas sensor used in the detection of chemical vapor. It also discusses a variety…
Abstract
Purpose
This paper aims to give an overview about the state of wireless passive surface acoustic wave (SAW) gas sensor used in the detection of chemical vapor. It also discusses a variety of different architectures including delay line and array sensor for gas detection, and it is considered that this technology has a good application prospect.
Design/methodology/approach
The authors state the most of the wireless passive SAW methods used in gas sensing, such as CO2, CO, CH4, C2H4, NH3, NO2, et al., the sensor principles, design procedures and technological issues are discussed in detail; their advantages and disadvantages are also summarized. In conclusion, it gives a prospect of wireless passive SAW sensor applications and proposes the future research field might lie in the studying of many kinds of harmful gases.
Findings
In this paper, the authors will try to cover most of the important methods used in gas sensing and their recent developments. Although wireless passive SAW sensors have been used successfully in harsh environments for the monitoring of temperature or pressure, the using in chemical gases are seldom reported. This review paper gives a survey of the present state of wireless passive SAW sensor in gas detection and suggests new and exciting perspectives of wireless passive SAW gas sensor technology.
Research limitations/implications
The authors will review most of the methods used in wireless passive SAW sensor and discuss the current research status and development trend; the potential application in future is also forecasted.
Originality/value
The authors will review most of the methods used in wireless passive SAW sensor and discuss the current research status and development trend; the potential application in future is also forecasted.
Details
Keywords
Liuyu Huang, Dion Hoe-Lian Goh and Stella Xin Yin
Public service announcements (PSAs) have been shown to be effective instruments that raise awareness, educate society, and change behaviors and attitudes. Many governments and…
Abstract
Purpose
Public service announcements (PSAs) have been shown to be effective instruments that raise awareness, educate society, and change behaviors and attitudes. Many governments and organizations have utilized PSAs on social media to promote online safety among children and youth. However, we have limited understanding of the range of topics that these PSAs address and how they present their content to audiences. This study provides an inventory of the types of online safety topics that current PSAs address and a catalogue of the types of persuasive features employed by PSAs.
Design/methodology/approach
A content analysis of 220 YouTube PSA videos on online safety was conducted. Various topics under the umbrella of online safety were identified. Guided by the prospect theory and exemplification theory, different persuasive features employed in the PSAs were sought.
Findings
The findings highlight that the primary focus of these PSAs is on online safety behaviors and general instructions on online hygiene. Interestingly, nearly half of the videos employ a neutral frame, while a significant portion provides no evidential support. Additionally, video length was associated with the number of views and likes it gathered but not with the number of comments.
Originality/value
The inventory of PSAs can help researchers, practitioners, and policymakers better understand the type of content being produced and disseminated online as well as identify topics that are either over or under-represented. Further, the catalogue of the types of persuasive features employed by PSAs would be helpful in guiding research, practice, and policymaking in the context of creating effective online safety videos.
Details
Keywords
Saba Khurshid, Shumaila Khurshid and Hafsa Khalil Toor
The rapid advancement of AI in education brings both significant challenges and opportunities. In Pakistan, where the educational system is facing numerous issues, AI integration…
Abstract
Purpose
The rapid advancement of AI in education brings both significant challenges and opportunities. In Pakistan, where the educational system is facing numerous issues, AI integration has raised significant concerns. Therefore, this study aims to explore the challenges AI poses to the Pakistani education system in the era of digital transformation.
Design/methodology/approach
A focus group was conducted with 13 participants, including educators and heads of departments from universities located in Rawalpindi and Islamabad. Thematic analysis was used to generate themes from the data.
Findings
The study findings indicated that AI integration in education can provide personalized and adaptive learning and teaching experiences by bridging the educational divide through easy access to quality education. Participants also highlighted the anxieties related to the digital divide as a great challenge for Pakistan. The integration of AI and automation in education is also raising concerns about job displacement for educators.
Originality/value
It highlighted that the integration of AI into the educational system can also bring both challenges and opportunities. To tackle these issues, potential strategies such as professional development and training programs to develop AI literacy among educators need to be introduced.
Details
Keywords
Mechanical properties are highly sensitive to the microstructure, and these are indirectly related to solidification parameters and processing conditions. AA7075 possesses…
Abstract
Purpose
Mechanical properties are highly sensitive to the microstructure, and these are indirectly related to solidification parameters and processing conditions. AA7075 possesses lightweight and excellent properties as structural material which can be optimized with SiCp addition and a good fabrication technique.
Design/methodology/approach
7000 series aluminium alloys exhibit the highest mechanical properties. They are used for high-strength structural applications such as aircraft parts and sporting goods. The desirable properties of these alloys are: low density, high stiffness, specific strength, good wear resistance and creep resistance. The focus of this work is to investigate the microstructure of composites formed by the dispersion of silicon carbide particles (SiC) into AA7075 by stir casting processes. 7075 Al alloy is reinforced with 10 and 15 wt.% SiCp of size 10–20 µm by stir casting process. The composites have been characterized by X-ray diffraction and scanning electron microscopy, differential thermal analysis and electron probe microscopic analysis.
Findings
SiCp distribution and interaction with AA7075 matrix have been studied. AA7075/10 wt.%/SiCp (10–20 µm) and AA7075/15 wt.%/SiCp (10–20 µm) composites microstructure showed excellent SiCp distribution into AA7075 matrix. In addition, no evidence of secondary chemical reactions has been observed in X-ray diffraction and electron probe microscopic analysis.
Originality/value
Little experimental work has been reported so far about effect of addition of 10 and 15 wt.% SiCp of size (10–20 µm) on the microstructure of 7075 Al alloy fabricated by stir casting process. The present investigation has been carried out to study the microstructure and carry out XRD, DTA and EPMA analysis of 7075 Al alloy, 10 and 15 wt.% SiCp of size (10–20 µm) composite and detect the interfacial reactions with the objective to minimize the formation of Al4C3.
Details
Keywords
Hamad Al Jassmi, Mahmoud Al Ahmad and Soha Ahmed
The first step toward developing an automated construction workers performance monitoring system is to initially establish a complete and competent activity recognition solution…
Abstract
Purpose
The first step toward developing an automated construction workers performance monitoring system is to initially establish a complete and competent activity recognition solution, which is still lacking. This study aims to propose a novel approach of using labor physiological data collected through wearable sensors as means of remote and automatic activity recognition.
Design/methodology/approach
A pilot study is conducted against three pre-fabrication stone construction workers throughout three full working shifts to test the ability of automatically recognizing the type of activities they perform in-site through their lively measured physiological signals (i.e. blood volume pulse, respiration rate, heart rate, galvanic skin response and skin temperature). The physiological data are broadcasted from wearable sensors to a tablet application developed for this particular purpose, and are therefore used to train and assess the performance of various machine-learning classifiers.
Findings
A promising result of up to 88% accuracy level for activity recognition was achieved by using an artificial neural network classifier. Nonetheless, special care needs to be taken for some activities that evoke similar physiological patterns. It is expected that blending this method with other currently developed camera-based or kinetic-based methods would yield higher activity recognition accuracy levels.
Originality/value
The proposed method complements previously proposed labor tracking methods that focused on monitoring labor trajectories and postures, by using additional rich source of information from labors physiology, for real-time and remote activity recognition. Ultimately, this paves for an automated and comprehensive solution with which construction managers could monitor, control and collect rich real-time data about workers performance remotely.
Details
Keywords
Saket Shanker, Hritika Sharma and Akhilesh Barve
The purpose of this study is to analyse various risks associated with third-party logistics (3PL) in the coffee supply chain and to present a framework that computes the influence…
Abstract
Purpose
The purpose of this study is to analyse various risks associated with third-party logistics (3PL) in the coffee supply chain and to present a framework that computes the influence of these risks on the critical success factors of the coffee supply chain.
Design/methodology/approach
The risks have been identified through a comprehensive literature review and validation by industry experts. The paper utilises an interpretive structural modelling (ISM) methodology for developing a hierarchical relationship among the CSFs. Furthermore, fuzzy MICMAC analysis is carried out to categorise these CSFs based on their driving power and dependence value. The fuzzy technique for order preferences by the similarity of an ideal solution (fuzzy-TOPSIS) approach has been applied to prioritise the risks associated with 3PL based on their ability to influence the CSFs of the coffee SC. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.
Findings
This study illustrates ten risks associated with 3PL and five CSFs in the coffee supply chain. The analysis revealed that coffee enterprises need to develop a balanced pricing strategy to ensure a sustainable competitive advantage, whereas the lack of direct customer communication is the most dominant 3PL risk affecting the CSFs.
Practical implications
This research provides coffee enterprises with a generalised framework with set parameters that can be used to attain a successful coffee supply chain in any developing nation.
Originality/value
The study contributes to the literature by being the first kind of study, which has used fuzzy ISM-MICMAC to analyse the CSFs of the coffee supply chain and fuzzy-TOPSIS for analysing the impact of various risks associated with the 3PL in the coffee supply chain. Thus, this work can be considered a benchmark for future research and advancement in the coffee business field.
Details
Keywords
This paper aims to investigate hypothesized relationships between the Internet of things (IoT) and big data analytics (BDA) with supply chain visibility (SCV) and operational…
Abstract
Purpose
This paper aims to investigate hypothesized relationships between the Internet of things (IoT) and big data analytics (BDA) with supply chain visibility (SCV) and operational performance (OP) in the pharmaceutical manufacturing sector in Jordan. The paper also aims to test the conceptual model related to the indirect effects of SCV.
Design/methodology/approach
To achieve the objectives of this paper, a conceptual model was developed through a review of the current literature. Data analysis was performed by covariance-based structural equation modelling using Amos 25 software, and the convergent validity, discriminant validity, reliability and confirmatory factor analysis were verified. Then the hypotheses were tested.
Findings
The results of the study indicate that there is a positive and statistically significant relationship between the IoT and BDA on SCV and OP. The relationship was positive and statistically significant between SCV and OP. In addition, support for the mediation hypothesis that SCV mediates the relationship among IoT, BDA and OP was confirmed.
Originality/value
This paper provides new theoretical and managerial contributions that have not been covered in previous studies, and it is considered the first study that uses this conceptual model with this mechanism in terms of the theoretical lens and empirical application. This paper contributes to understanding the dynamic mechanisms of the IoT and BDA in enhancing OP, which contributes to creating a supply chain capable of facing various environmental fluctuations and pressures. This study presents new implications that can be used in the supply chain literature.
Details
Keywords
Ammar Aamer, Chelinka Rafiesta Sahara and Mohammed Ali Al-Awlaqi
There is an increasing interest in the supply chain’s digitalization, yet the topic is still in the preliminary stages of academic research. The academic literature has no…
Abstract
Purpose
There is an increasing interest in the supply chain’s digitalization, yet the topic is still in the preliminary stages of academic research. The academic literature has no consensus and is still limited to research assessing the supply chain’s digitalization of organizations. This study aims to explore the supply chain digitalization drivers to understand the emerging phenomena. More specifically, the authors devised from the literature the most common factors in assessing the readiness in scaling supply chain digitalization.
Design/methodology/approach
This study followed a five-phased systematic literature review (SLR) methodology in this research: designing, analyzing, conducting, writing and assessing the quality of the review. The SLR is beneficial for justifying future research regardless of the complex process that requires dealing with high-level databases, information filtering and relevancies of the content. Through analysis of 347 titles and abstracts and 40 full papers, the authors showed and discussed the supply chain digitalization: transformation factors.
Findings
The results generated three main themes: technology, people and processes. The study also generated ten subthemes/primary drivers for assessing the readiness for supply chain digitalization in organizations: IT infrastructure, cybersecurity systems, digitalization reskilling and upskilling, digitalization culture, top management support, digitalization and innovation strategy, integrated supply chain, digital innovation management, big data management and data analytics and government regulations. The importance of each factor was discussed, and future research agenda was presented.
Research limitations/implications
While the key drivers of the supply chain digitalization were identified, there is still a need to study the statistical correlation to confirm the interrelationships among factors. This study is also limited by the articles available in the databases and content extraction.
Practical implications
This study supports decision-makers in understanding the critical drivers in digitalizing the supply chain. Once these factors are studied and comprehended, managers and decision-makers could better anticipate and allocate the proper resources to embark on the digitalization journey and make informed decisions.
Originality/value
The digitalization of the supply chain is more critical nowadays due to the global disruptions caused by the Coronavirus (COVID-19) pandemic and the surge of organizations moving toward the digital economy. There is a gap between the digital transformation pilot studies and implementation. The themes and factors unearthed in this study will serve as a foundation and guidelines for further theoretical research and practical implications.
Details
Keywords
Zihao Ye, Georgios Kapogiannis, Shu Tang, Zhiang Zhang, Carlos Jimenez-Bescos and Tianlun Yang
Built asset management processes require a long transition period to collect, edit and update asset conditions information from existing data sets. This paper aims to explore and…
Abstract
Purpose
Built asset management processes require a long transition period to collect, edit and update asset conditions information from existing data sets. This paper aims to explore and explain whether and how digital technologies, including asset information model (AIM), Internet of Things (IoT) and blockchain, can enhance asset conditions assessment and lead to better asset management.
Design/methodology/approach
Mixed methods are applied to achieve the research objective with a focus in universities. The questionnaire aims to test whether the integration of AIM, IoT and blockchain can enhance asset condition assessment (ACA). Descriptive statistical analysis was applied to the quantitative data. The mean, median, mode, standard deviation, variance, skewness and range of the data group were calculated. Semi-structured interviews were designed to answer how the integration of AIM, IoT and blockchain can enhance the ACA. Quantitative data was analysed to define and explain the essential factors for each sub-hypothesis. Meanwhile, to strengthen the evaluation of the research hypothesis, the researcher also obtained secondary data from the literature review.
Findings
The research shows that the integration of AIM, IoT and blockchain strongly influences asset conditions assessment. The integration of AIM, IoT and blockchain can improve the asset monitoring and diagnostics through its life cycle and in different aspects, including financial, physical, functional and sustainability. Moreover, the integration of AIM, IoT and blockchain can enhance cross-functional collaboration to avoid misunderstandings, various barriers and enhance trust, communication and collaboration between the team members. Finally, costs and risk could be reduced, and performance could be increased during the ACA.
Practical implications
The contribution of this study indicated that the integration of AIM, IoT and blockchain application in asset assessment could increase the efficiency, accuracy, stability and flexibility of asset assessment to ensure the reliability of assets and lead to a high-efficiency working environment. More importantly, a key performance indicator for ACA based on the asset information, technology and people experience could be developed gradually.
Originality/value
This study can break the gap between transdisciplinary knowledge to improve the integration of people, technology (AIM, IoT and blockchain) and process value-based ACA in built asset management within universities.