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Jarsh Safety received an order of 500 units of its Model S helmet. However, the order must be delivered within 15 days. Jarsh Safety was founded by three engineering college peers, who conceptualized air-conditioned, industrial safety helmets. This innovative revolutionary product offered industrial workers not only safety but aesthetics and comfort. The founders hoped that the product could change the perception of safety helmets from mandatory wear to desired wear. The case details the production process, staffing, raw material required and procurement lead time.

The purpose of this paper is to examine the mechanical characteristics and optimization of wear parameters of hybrid (TiO₂ + Y₂O₃) nanoparticles with Al matrix using squeeze casting technique.

The hybrid aluminium matrix nanocomposites (HAMNCs) were fabricated with varying concentrations of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃), from 2.5 to 10 Wt.% in 2.5 Wt.% increments. Dry sliding wear test variables were optimized using the Taguchi method.

The introduction of hybrid nanoparticles in the aluminium (Al) matrix was evenly distributed in contrast to the base matrix. HAMNC6 (5 Wt.% TiO₂ + 5 Wt.% Y₂O₃) reported the maximum enhancement in mechanical properties (tensile strength, flexural strength, impact strength and density) and decrease in porosity% and elongation% among other HAMNCs. The results showed that the optimal combination of parameters to achieve the lowest wear rate was A3B3C1, or 15 N load, 1.5 m/s sliding velocity and 200 m sliding distance. The sliding distance showed the greatest effect on the dry sliding wear rate of HAMNC6 followed by applied load and sliding velocity. The fractured surfaces of the tensile sample showed traces of cracking as well as substantial craters with fine dimples and the wear worn surfaces were caused by abrasion, cracks and delamination of HAMNC6.

Squeeze-cast Al-reinforced hybrid (TiO₂+Y₂O₃) nanoparticles have been investigated for their impact on mechanical properties and optimization of wear parameters.

Saudi Arabia's 2030 vision targets an increase of 34% in non-oil revenue participation in the GDP, thus the need for automation and digital transformation. The Company ER is a market leader producing high-quality dairy products in the Kingdom and is a pioneer in the production industry. The company has recently increased the capacity of its milk factory to meet its vision. An investment was made to automate the pallet handling procedures at the milk factory to provide increased production for daily consumption. The new automation transition in Company ER's milk factory provides a unique opportunity to utilize lean management tools to improve the current automated processes before commercialization.

OEE (overall equipment effectiveness) will monitor losses for different operational losses in the new automated system and indicate system improvements, with 85% as the target. Based on DMADV (design, measure, analyze, design and validate) methodology, this study analyzes the entire automated pallet handling system. It uses lean tools to identify areas for improvement, identify waste elements and propose solutions to achieve Company ER's OEE targets.

In this paper, the outcomes will be presented as documented solutions that address the losses encountered in the production system, showing a 12.8% increase in the system's OEE.

Owing the time and resource constraint, this study only involved automated pallet handling procedures in a milk production facility. Hence, the generalization of the result is slightly limited. More studies in several different processes and sectors are required.

This study provided a valuable tool for researchers for gaining deeper understanding regarding the lean manufacturing and its implementation. For practitioners, it is useful to evaluate the degree of lean manufacturing tools in their material handling systems.

This study is the first attempt to develop lean manufacturing constructs for evaluating the automated pallet handling procedures in a milk production facility.

Magnet spot is the primary method to develop the automated guided vehicle (AGV) guidance system for many automated container terminals (ACT). Aiming to improve the high flexibility of AGV operation in ACT, this paper aims to address the problem of technical stability leading to ACT production paralysis and propose a mini-terminal AGV robot for testing laser simultaneous location and mapping (SLAM)-based methods in ACT operation scenarios.

This study developed a physical simulation robot for terminal AGV operations, providing a platform to test technical solutions for applying laser navigation-related technologies in ACTs. Then, the terminal-AGV navigation system framework is designed to apply the laser-SLAM-based method in the physical simulation robot. Finally, the experiment is conducted in the terminal operation scenario to verify the feasibility of the proposed framework for lased-SLAM-based method testing and analyze the performance of the different mini-terminal AGV robots.

A series of experiments are conducted to analyze the performance of the proposed mini-terminal AGV robot for laser-SLAM-based method testing. The experimental results show the validity and effectiveness of the AGV robot and AGV navigation system framework with better local map matching, loopback and absolute positional error.

The proposed mini-terminal AGV robot and AGV navigation system framework can provide a platform for innovative laser-SLAM-based method testing in ACTs applications. Therefore, this study can effectively meet the high requirements of ACT for maturity and stability of the laser navigation technical.

Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.

This paper establishes a quality model for automation assembly of range hood impeller based on generalized grey relational degree, it improves the debugging efficiency of the newly developed assembly workstation.

First, spot check the trial production impellers and obtain three indexes that reflect the assembly quality of the impellers. Then, analyze the parameters that affect the assembly quality of the impeller using grey relational analysis (GRA), establish a model for the assembly quality of the range hood impeller based on the generalized grey relational degree and identify the main parameters. After that, analyze the transmission structure of automation assembly workstation, identify the reasons that affect parameters and propose improvement plans. Finally, a trial production is conducted on the automation assembly workstation after adopting the improved plan to verify the quality model of impeller automation assembly.

The research shows that compared to manual assembly, the automation assembly quality of the impeller using GRA model has been improved, shortening the debugging cycle of the newly developed assembly workstation.

The newly developed automation equipment will have some problems in the trial production stage, which often rely on the experience of engineers for debugging. In this paper, the automation assembly quality model of range hood impeller based on GRA is established, which can not only ensure the quality of finished impeller but also shorten the debugging cycle of the equipment. In addition, GRA can be widely used in the commissioning of other automation equipment.

This study has developed a set of impeller automation assembly workstation. The debugging method in the trial production stage is beneficial to shorten the trial production time and improve the economic benefits.

This paper aims to illustrate the growing role of robots in the electronics industries.

Following a short introduction, this paper discusses robotic applications and products in three sectors of the electronics industry: semiconductor processing, printed circuit manufacture and electronic product assembly. Finally, conclusions are drawn.

The major application in semiconductor manufacture is the handling of silicon wafers during both front- and back-end processes and products include cleanroom certified multi-axis robotic arms, some mounted on mobile platforms, and automated guided vehicles. Applications in printed circuit board production include component handling and insertion, soldering, inspection, testing and packing. These exploit Cartesian, SCARA and six-axis articulated robots and cobots play an important role where automated and manual processes operate in close proximity. Electronic product assembly applications include part handling, soldering, bonding and sealing, screw driving, test and inspection and packaging. Cobots offer the benefits of a small footprint which allows deployment in the often limited space and use in proximity to humans. As yet, robotic assembly of complex electronic products such as smartphones and computers has not been realised for technical reasons.

This study provides a detailed review of robotic products and applications in three key sectors of the electronics industries.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

This study aims to investigate the role of regional environmental transparency on corporate environmental disclosure.

This study uses the introduction of a nationwide automated air pollution monitoring network in China as a quasi-natural experiment and employs regression analysis. Robustness checks, including parallel trend test and placebo test, are performed to test the robustness of the results.

Sharing air pollution data with the public can improve corporate environmental disclosure. Firms with poorer environmental, social and governance (ESG) performance prefer to disclose less informative information after the automated network is implemented compared with firms with better ESG performance. The relationship between information sharing and corporate environmental transparency is more pronounced when local air pollution is severer, firms face stronger investor scrutiny and firms are from heavily polluting industries. The mechanism tests suggest the automated system can draw public environmental attention and improve governments’ aspiration for environmental governance. Finally, corporate environmental disclosure can reduce stock price crash risk and cost of equity.

Real-time pollution data reporting is an important solution to raising public environmental awareness and then enhancing the effectiveness of pollution control.

This study has implications for policy-making regarding environmental governance and environmental disclosure.

This study confirms that pollution information transparency can motivate firms to increase environmental disclosure.

This paper aims to examine the causation linking financial technology to economic growth in the East African Community states from 1997 to 2019.

Autoregressive distributed lag is used. Gross domestic product per capita proxies economic growth, automated teller machines, point of sale, debit card ownership and mobile banking measure financial technology.

The results unveil a significant relationship between financial technology and economic growth. The findings show bidirectional causality between automated teller machine and economic growth, with unidirectional causation from economic growth to point of sales and internet banking, mobile banking and government effectiveness to economic growth. The error correction term is negatively significant, demonstrating a long-term convergence between Fintech measures and economic growth.

The governments should effectively enact and implement policies that protect investments in financial technologies to boost economic growth in the East African Community countries. The government should reduce taxes on financial technology equipment and related services. The use of automated teller machine, debit card ownership and internet banking should be encouraged through cashless transactions. Financial institutions should adopt cashless operation policies to encourage the use of financial technologies.

Research results on the bond between financial technology and economic growth are not conclusive. These studies demonstrate that technological innovations are double edged-swords, with both positive and negative sides. The results are conflicting; some reveal positive relationships, while others show negative links. Hence, research is required to fill the lacuna.