Search Results (136)

Agricultural tractors possess front loaders that are employed for the handling and transportation of materials, but are exposed to mechanical vibrations and shocks from ground undulations and sudden variations in the load. These vibrations are harmful to the durability of the parts, the comfort of the driver, and the longevity of the machine. In this current study, the performance of the hydraulic accumulator to mitigate such vibrations for a Foton 904 wheeled tractor equipped with a TZ10C-824 front loader is studied. Vibration measurements were taken by an experimental Brüel & Kjær 3050-A040 analyzer under various loading configurations (no loading, 180 kg, and 312 kg), with or without a 1.4 L, 50-bar nitrogen gas-charged Fox Opera Mi Italy hydraulic accumulator. Results reveal that maximum accelerations were as much as 6.24 m·s⁻² without an accumulator during testing of a 312 kg load, whereas they were extremely low at 2.66 m·s⁻² when the accumulator was activated. Frequency-domain analysis verified that the main vibrations were within the range of 3–4 Hz, with FFT peak amplitudes dropping from 5.6 m·s⁻² to 2.4 m·s⁻² upon the accumulator’s operation. The observations verify the effectiveness of the accumulator in vibration intensity reduction, absence of high-frequency shock loads, and ride comfort, along with structural safety improvement. The study provides a solid platform for further enhancement in vibration control techniques for agricultural machines and loader system design. Full article

A common technique used in factories to shape metal panels is shot peen forming, where the panel is sprayed with a high-velocity stream of small steel pellets called “shot.” The impacts between the hard steel shot and the softer metal of the panel cause localized plastic deformation, which is used to improve the fatigue properties of the material’s surface. The residual stress distribution imparted by impacts also results in bending, which suggests that a torque is associated with it. In this paper, we model shot peen forming as the application of spatially varying torques to a Kirchhoff plate, opting to use the language of thermoelasticity in order to introduce these torque distributions. First, we derive the governing equations for the thermoelastic thin plate model and show that only a torque-type resultant of the temperature distribution shows up in the bending equation. Next, to calibrate from the shot peen operation, an empirical “effective torque” parameter used in the thermoelastic model, a simple and non-invasive test is devised. This test relies only on measuring the maximum displacement of a uniformly shot peened plate as opposed to characterizing the residual stress distribution. After discussing how to handle the unconventional fully free boundary conditions germane to shot peened plates, we introduce an approach to solving the inverse problem whereby the peening distribution required to obtain a specified plate contour can be obtained. Given that the relation between shot peen distributions and bending displacements at a finite set of points is non-unique, we explore a regularization of the inverse problem which gives rise to shot peen distributions that match the capabilities of equipment in the factory. In order to validate our proposed model, an experiment with quantified uncertainty is designed and carried out which investigates the agreement between the predictions of the calibrated model and real shot peen-forming operations. Full article

Biomass and other solid wastes create potential environmental and health hazards in our modern society. Conversion of the wastes into energy presents a promising avenue for sustainable energy generation. However, the feasibility of the approach is limited by the challenges in material handling because of the special properties of the materials. Despite their critical importance, the complexities of material handling often evade scrutiny until operational implementation. This paper highlights the challenges inherent in standard solid material-handling processes, preceded by a concise review of common solid waste typologies and their physical properties, particularly those related to biomass and biowastes. It delves into the complexities of material flow, storage, compaction, agglomeration, separation, transport, and hazard management. Specialised characterisation techniques essential for informed process design are also discussed to mitigate operational risks. In conclusion, this paper emphasises the necessity of a tailored framework before the establishment of any further conversion processes. Given the heterogeneous nature of biomaterials, material-handling equipment must demonstrate adaptability to accommodate the substantial variability in material properties in large-scale production. This approach aims to enhance feasibility and efficacy of any energy conversion initiatives by using biomass or other solid wastes, thereby advancing sustainable resource utilisation and environmental stewardship. Full article

This research presents a comprehensive methodology for calibrating Discrete Element Method (DEM) parameters governing rice grain interactions with biodegradable Polylactic Acid (PLA) components in agricultural bucket elevator systems. Rice grains, a critical global food staple requiring efficient post-harvest handling, were modeled as three-sphere clusters to accurately represent their physical dimensions (6.5 mm length), while the Hertz–Mindlin contact model provided the theoretical framework for particle interactions. The calibration process employed a multi-phase experimental design integrating Plackett–Burmann screening, steepest ascent method, and Face Central Composite Design to systematically identify and optimize critical micro-mechanical parameters for agricultural material handling. Statistical analysis revealed the coefficient of static friction between rice and PLA as the dominant factor, contributing 96.49% to system performance—significantly higher than previously recognized in conventional agricultural processing designs. Response Surface Methodology generated predictive models achieving over 90% correlation with experimental results from 3D-printed PLA shear box tests. Validation through comparative velocity profile analysis during bucket elevator discharge operations confirmed excellent agreement between simulated and experimental behavior despite a 20% discharge velocity variance that warrants further investigation into agricultural material-specific phenomena. The established parameter set enables accurate virtual prototyping of sustainable agricultural handling equipment, offering post-harvest processing engineers a powerful tool for optimizing bulk material handling systems with reduced environmental impact. This integrated approach bridges fundamental agricultural material properties with sustainable engineering design principles, providing a scalable framework applicable across multiple agricultural processing operations using biodegradable components. Full article

The consumption of fresh fruit and vegetables is essential for a healthy diet as they contain a diverse composition of vitamins, minerals, fibre, and bioactive compounds. However, cross-contamination during harvest and post-harvest poses a high risk of microbial contamination. Therefore, handling fruit and vegetables during processing and contact with wet equipment and utensil surfaces is an ideal environment for microbial contamination and foodborne illness. Nevertheless, less attention has been paid to some emerging pathogens that are now increasingly recognised as transmissible to humans through contaminated fruit and vegetables, such as Arcobacter and Cronobacter species in various products, which are the main risk in fruit and vegetables. Cronobacter and Arcobacter spp. are recognised food-safety hazards because they pose a risk of foodborne disease, especially in vulnerable groups such as newborns and immunocompromised individuals. Cronobacter spp. have been linked to severe infant conditions—notably meningitis and sepsis—most often traced to contaminated powdered infant formula. Although Arcobacter spp. have been less extensively studied, they have also been associated with foodborne disease, chiefly from dairy products and meat. With this in mind, this review provides an overview of the main chemical and physical sanitisation methods in terms of their ability to reduce the contamination of fresh fruit and vegetable products caused by two emerging pathogens: Arcobacter and Cronobacter. Emerging chemical (organic acid compounds, extracts, and essential oils) and physical methods (combination of UV-C with electrolysed water, ultrasound, and cold atmospheric plasma) offer innovative and environmentally friendly alternatives to traditional approaches. These methods often utilise natural materials, less toxic solvents, and novel techniques, resulting in more sustainable processes compared with traditional methods that may use harsh chemicals and environmentally harmful processes. This review provides the fruit and vegetable industry with a general overview of possible decontamination alternatives to develop optimal and efficient processes that ensure food safety. Full article

Semiconductor device fabrication is conducted through highly precise manufacturing processes. An essential component of the semiconductor package is the lead frame on which the silicon dies are assembled. Impurities such as oxides or organic matter on the surfaces have an impact on the process yield. Plasma cleaning is a vital process in semiconductor manufacturing, employed to enhance production yield through precise and efficient surface preparation essential for device fabrication. This paper explores the various facets of plasma cleaning, with a particular emphasis on its application in the cleaning of lead frames used in semiconductor packaging. To provide comprehensive context, this paper also reviews the critical role of plasma in advanced and emerging packaging technologies. This study investigates the fundamental physics governing plasma generation, the design of plasma systems, and the composition of the plasma medium. A central focus of this work is the comparative analysis of different plasma systems in terms of their effectiveness in removing organic contaminants and oxide residues from substrate surfaces. By utilizing reactive species generated within the plasma—such as oxygen radicals, hydrogen ions, and other chemically active constituents—these systems enable a non-contact, damage-free cleaning method that offers significant advantages over conventional wet chemical processes. Additionally, the role of non-reactive species, such as argon, in sputtering processes for surface preparation is examined. Sputtering is the ejection of individual atoms from a target surface due to momentum transfer from an energetic particle (usually an ion). Sputtering is therefore a physical process driven by momentum transfer. Energetic ions, such as argon (Ar⁺), are accelerated from the plasma to bombard a target surface. Upon impact, these ions transfer sufficient kinetic energy to atoms within the material’s lattice to overcome their surface binding energy, resulting in their physical ejection. This paper also provides a comparative assessment of various plasma sources, including direct current, dielectric barrier discharge, radio frequency, and microwave-based systems, evaluating their suitability and efficiency for lead frame cleaning applications. Furthermore, it addresses critical parameters affecting plasma cleaning performance, such as gas chemistry, power input, pressure regulation, and substrate handling techniques. The ultimate aim of this paper is to provide a concise yet comprehensive resource that equips technical personnel with the essential knowledge required to make informed decisions regarding plasma cleaning technologies and their implementation in semiconductor manufacturing. This paper provides various tables which provide the reader with comparative assessments of the various plasma sources and gases used. Scoring mechanisms are also introduced and utilized in this paper. The scores achieved by both the sources and the plasma gases are then summarized in this paper’s conclusions. Full article

Roll-to-roll (R2R) manufacturing processes demand precise control of web or yarn velocity and tension, alongside robust mechanisms for handling system failures. This paper presents an integrated approach combining high-performance control with reliable fault detection for an experimental R2R system. A model-based cascade control strategy is designed, incorporating system identification, radius compensation for varying roll diameters, and a Kalman filter to mitigate load sensor noise, ensuring accurate regulation of yarn velocity and tension under normal operating conditions. In parallel, a data-driven fault detection layer uses Gaussian Process Regression (GPR) models, trained offline on healthy operating data, to predict yarn tension and motor speeds. During operation, discrepancies between measured and GPR-predicted values that exceed predefined thresholds trigger an immediate shutdown of the system, preventing material loss and equipment damage. Experimental trials demonstrate tension regulation within ±0.02 N and velocity errors below ±5 rad/s across varying roll diameters, while yarn-break and motor-fault scenarios are detected within a single sampling interval (<100 milliseconds) with zero false alarms. This study validates the integrated system’s capability to enhance both the operational precision and resilience of R2R processes against critical failures. Full article

Water regeneration in PVC production is a key issue to consider, given the high freshwater consumption rate of the process. This research evaluates the inherent safety of poly(vinyl chloride) (PVC) production via suspension polymerization by implementing mass and energy integration strategies in combination with wastewater regeneration under a zero-liquid-discharge (ZLD) approach. The impact of these integrations on process safety was examined by considering the risks associated with the handling of hazardous materials and critical operations, as well as the reduction in waste generation. To this end, the Inherent Safety Index (ISI) methodology was employed, which quantifies hazards based on factors such as toxicity and flammability, enabling the identification of risks arising from system condition changes due to the implementation of sustainable water treatment technologies. Although the ISI methodology has been applied to various chemical processes, there are few documented cases of its specific application in PVC plants that adopt circular production strategies and water resource sustainability. Therefore, in this study, ISI was used to thoroughly evaluate each stage of the process, providing a comprehensive picture of the safety risks associated with the use of sustainable technologies. The assessment was carried out using simulation software, computer-aided process engineering (CAPE) methodologies, and information obtained from safety repositories and expert publications. Specifically, the Chemical Safety Index score was 22 points, with the highest risk associated with flammability, which scored 4 points, followed by toxicity (5 points), explosiveness (2 points), and chemical interactions, with 4 points attributed to vinyl chloride monomer (VCM). In the toxicity sub-index, both VCM and PVC received 5 points, while substances such as sodium hydroxide (NaOH) and sodium chloride (NaCl) scored 4 points. In the heat of reaction sub-index, the main reaction scored 3 points due to its high heat of reaction (−1600 kJ/kg), while the secondary reactions from PVA biodegradation scored 0 points for the anoxic reaction (−156.5 kJ/kg) and 3 points for the aerobic reaction (−2304 kJ/kg), significantly increasing the total index. The Process Safety Index scored 15 points, with the highest risk found in the inventory of hazardous substances within the inside battery limits (ISBL) of the plant, where a flow rate of 3241.75 t/h was reported (5 points). The safe equipment sub-index received 4 points due to the presence of boilers, burners, compressors, and reactors. The process structure scored 3 points, temperature 2, and pressure 1, reflecting the criticality of certain operating conditions. Despite sustainability improvements, the process still presented significant chemical and operational risks. However, the implementation of control strategies and safety measures could optimize the process, balancing sustainability and safety without compromising system viability. Full article

This paper examines the impact of two storage policies—dedicated storage (D-SLAP) and randomized storage (R-SLAP)—on warehouse operational efficiency. It integrates the Storage Location Assignment Problem (SLAP) with the unrelated parallel machine scheduling problem (UPMSP), which represents the scheduling of the material handling equipment (MHE). This integration is intended to elucidate the interplay between storage strategies and scheduling performance. The considered evaluation metrics include transportation cost, average waiting time, and total tardiness, while accounting for product arrival and demand schedules, precedence constraints, and transportation expenses. Additionally, considerations such as MHE eligibility, resource requirements, and available storage locations are incorporated into the analysis. Given the complexity of the combined problem, a tailored Non-dominated Sorting Genetic Algorithm (NSGA-II) was developed to assess the performance of the two storage policies across various randomly generated test instances of differing sizes. Parameter tuning for the NSGA-II was conducted using the Taguchi method to identify optimal settings. Experimental and statistical analyses reveal that, for small-size instances, both policies exhibit comparable performance in terms of transportation cost and total tardiness, with R-SLAP demonstrating superior performance in reducing average waiting time. Conversely, results from large-size instances indicate that D-SLAP surpasses R-SLAP in optimizing waiting time and tardiness objectives, while R-SLAP achieves lower transportation cost. Full article

In this research work, two distinct types of three-dimensional (3D) capacitors were successfully fabricated, each with its own unique features and advantages. The first type of capacitor is centered around a 3D nanoporous structure. This structure is formed on a nickel substrate through anodic oxidation. After undergoing high-temperature thermal oxidation, a monolithic Ni-NiO-Pt metal–insulator–metal (MIM) capacitor with a nanoporous dielectric architecture is achieved. Structurally, this innovative design brings about several remarkable benefits. Due to the nanoporous structure, it has a significantly increased surface area, which can effectively store more charges. As a result, it exhibits an equivalent capacitance density of 69.95 nF/cm², which is approximately 18 times higher than that of its planar, non-porous counterpart. This high capacitance density enables it to store more electrical energy in a given volume, making it highly suitable for applications where miniaturization and high energy storage in a small space is crucial. The second type of capacitor makes use of Through-Glass Via (TGV) technology. This technology is employed to create an interdigitated blind-via array within a glass substrate, attaining an impressively high aspect ratio of 22.5:1 (with a via diameter of 20 μm and a depth of 450 μm). By integrating atomic layer deposition (ALD), a conformal interdigital electrode structure is realized. Glass, as a key material in this capacitor, has outstanding insulating properties. This characteristic endows the capacitor with a high breakdown field strength exceeding 8.2 MV/cm, corresponding to a withstand voltage of 5000 V. High breakdown field strength and withstand voltage mean that the capacitor can handle high-voltage applications without breaking down easily, which is essential for power-intensive systems like high-voltage power supplies and some high-power pulse-generating equipment. Moreover, due to the low-loss property of glass, the capacitor can achieve an energy conversion efficiency of up to 95%. Such a high energy conversion efficiency ensures that less energy is wasted during the charge–discharge process, which is highly beneficial for energy-saving applications and systems that require high-efficiency energy utilization. Full article

Conveyor belts are critical in various industries, particularly in the barrier eddy current separator systems used in recycling processes. However, hidden issues, such as belt misalignment, excessive heat that can lead to fire hazards, and the presence of sharp or irregularly shaped materials, reduce operational efficiency and pose serious threats to the health and safety of personnel on the production floor. This study presents an intelligent monitoring and protection system for barrier eddy current separator conveyor belts designed to safeguard machinery and human workers simultaneously. In this system, a thermal camera continuously monitors the surface temperature of the conveyor belt, especially in the area above the magnetic drum—where unwanted ferromagnetic materials can lead to abnormal heating and potential fire risks. The system detects temperature anomalies in this critical zone. The early detection of these risks triggers audio–visual alerts and IoT-based warning messages that are sent to technicians, which is vital in preventing fire-related injuries and minimizing emergency response time. Simultaneously, a machine vision module autonomously detects and corrects belt misalignment, eliminating the need for manual intervention and reducing the risk of worker exposure to moving mechanical parts. Additionally, a line-scan camera integrated with the YOLOv11 AI model analyses the shape of materials on the conveyor belt, distinguishing between rounded and sharp-edged objects. This system enhances the accuracy of material separation and reduces the likelihood of injuries caused by the impact or ejection of sharp fragments during maintenance or handling. The YOLOv11n-seg model implemented in this system achieved a segmentation mask precision of 84.8 percent and a recall of 84.5 percent in industry evaluations. Based on this high segmentation accuracy and consistent detection of sharp particles, the system is expected to substantially reduce the frequency of sharp object collisions with the BECS conveyor belt, thereby minimizing mechanical wear and potential safety hazards. By integrating these intelligent capabilities into a compact, cost-effective solution suitable for real-world recycling environments, the proposed system contributes significantly to improving workplace safety and equipment longevity. This project demonstrates how digital transformation and artificial intelligence can play a pivotal role in advancing occupational health and safety in modern industrial production. Full article

An important process in the mining industry is material handling, where trucks are responsible for transporting materials extracted by shovels to different locations within the mine. The decision about the destination of a truck is very important to ensure an efficient material handling operation. Currently, this decision-making process is managed by centralized systems that apply dispatching criteria. However, this approach has the disadvantage of not providing accurate dispatching solutions due to the lack of awareness of potentially changing external conditions and the reliance on a central node. To address this issue, we previously developed a multi-agent system for truck dispatching (MAS-TD), where intelligent agents representing real-world equipment collaborate to generate schedules. Recently, we extended the MAS-TD (now MAS-TDRL) by incorporating learning capabilities and compared its performance with the original MAS-TD, which lacks learning capabilities. This comparison was made using simulated scenarios based on actual data from a Chilean open-pit mine. The results show that the MAS-TDRL generates more efficient schedules. Full article

The activity of moving LPG gas cylinders at PT XYZ is carried out manually The unloading of 3 kg LPG gas cylinders from the truck to the floor occurs repeatedly. Workers must bend down when moving the cylinder, and a twisting body, so it can cause injuries such as musculoskeletal disorders (MSDs). This activity involved four workers, but those observed were workers 2 and 4 who were tasked with unloading gas cylinders from the truck. This research aims to analyze the MSDs of worker complaints using the Nordic Body Map (NBM) questionnaire, determine the level of risk using the National Institute for Occupational Safety and Health (NIOSH) Multi-Task Method, and provide suggestions for improvement. The research results show that the NBM values for workers 2 and 4 are 59 and 61, respectively, in the medium category, which means they require immediate corrective action. Meanwhile, in the CLI (Composite Lifting Index) origin for the second worker, all gas cylinder stacks are >3, whereas in the CLI destination, all stacks are >2. During the CLI origin and destination of the fourth worker, all stacks have a value of >3, which means the risk of injury is high..Recommendations for improvement are given by reducing the horizontal lifting distance, reducing asymmetrical angles, and using material handling equipment such as the hand trolley. Full article

In the aluminum electrolysis production workshop, heavy-load overhead cranes equipped with multi-functional operation terminals are responsible for critical tasks such as anode replacement, shell breaking, slag removal, and material feeding. The real-time monitoring of these four types of operation terminals is of the utmost importance for ensuring production safety. High-resolution cameras are used to capture dynamic scenes of operation. However, the terminals undergo morphological changes and rotations in three-dimensional space according to task requirements during operations, lacking rotational invariance. This factor complicates the detection and recognition of multi-form targets in 3D environment. Additionally, operations like striking and material feeding generate significant dust, often visually obscuring the terminal targets. The challenge of real-time multi-form object detection in high-resolution images affected by smoke and dust environments demands detection and dehazing algorithms. To address these issues, we propose the YOLOv8n-Al-Dehazing method, which achieves the precise detection of multi-functional material handling terminals in aluminum electrolysis workshops. To overcome the heavy computational costs associated with processing high-resolution images by using YOLOv8n, our method refines YOLOv8n through component substitution and integrates real-time dehazing preprocessing for high-resolution images, thereby reducing the image processing time. We collected on-site data to construct a dataset for experimental validation. Compared with the YOLOv8n method, our method approach increases inference speed by 15.54%, achieving 120.4 frames per second, which meets the requirements for real-time detection on site. Furthermore, compared with state-of-the-art detection methods and variants of YOLO, YOLOv8n-Al-Dehazing demonstrates superior performance, attaining an accuracy rate of 91.0%. Full article

The building sector accounts for more than one-third of final energy consumption worldwide. Green retrofitting, which is part of the green building activities, is one of the main factors in achieving the target of zero carbon emissions by 2060. Green retrofitting is a viable way to reduce greenhouse gas (GHG) emissions and energy consumption. The risks in green retrofitting work activities have not been studied much, even though the risks in green retrofitting projects are likely to be greater and more complex than the risks in conventional projects. This is reflected in the small application of customization in developing countries, one of which is Indonesia. Through the calculation of the risk matrix between probability and impact, a high risk was obtained from the relationship between risk and correlated resources, and it had a positive impact on the work breakdown structure (WBS). The results obtained show that complexity factors consisting of labor, materials, equipment, work activities, work methods, and scope/work package affect the success of the project, then the risk handling strategy that needs to be implemented is to set the right priorities. A focused project team allocates resources wisely. Knowing the probability of events and impacts arising from the non-implementation of the WBS, we identified sources of risk factors and high risk in the implementation of green retrofitting work based on the WBS based on the Greenship Existing Building Rating Tools and PUPR RI Regulation Number 21 of 2021 applicable in Indonesia, its effect on resource planning, and cost accuracy. Full article