Cycle Time Research Articles

Productivity Assessment of Digging and Loading Equipment (Cat 330D2L) and Hauling Equipment (Fuso 220PS) in Coal Mining at PT. Bhumi Sriwijaya Perdana Coal, Musi Banyuasin Regency, South Sumatra

PT. Bhumi Sriwijaya Perdana Coal, a coal mining company located in Musi Banyuasin District, South Sumatra, utilizes Caterpillar 330D2L excavators and Mitsubishi Fuso 220PS dump trucks for coal extraction activities. The company set a production target of 52,612 tons/month for March 2023. However, actual production fell short, with the hauling equipment achieving only 41,260.08 tons/month, despite the loading equipment exceeding the target with 59,086.93 tons/month. This research aims to identify factors hindering the achievement of production targets and propose strategies for improvement. The analysis revealed that the mismatch between the loader and hauler operations, reflected by a low match factor of 0.57, was a significant contributor to inefficiencies. Additional challenges included extended cycle times influenced by front-loading patterns, hauling path conditions, and equipment synchronization. After implementing improvements, including cycle time optimization and increased loading flow, the productivity of the Mitsubishi Fuso 220PS dump trucks increased to 59,732.67 tons/month. The match factor between the Caterpillar 330D2L and the Mitsubishi Fuso 220PS improved to 0.83, demonstrating enhanced operational alignment. These findings highlight the importance of addressing cycle times, optimizing equipment compatibility, and improving workflows to meet production targets effectively.

Quantum error correction below the surface code threshold.

Quantum error correction [1, 2, 3, 4] provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. Here, we present two below-threshold surface code memories on our newest generation of superconducting processors, Willow: a distance-7 code, and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% ± 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of . Our system maintains below-threshold performance when decoding in real time, achieving an average decoder latency of 63 μs at distance-5 up to a million cycles, with a cycle time of 1.1 μs. We also run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms.

Data Digitization in Manufacturing Factory Using Palantir Foundry Solution

This research describes an online solution for the collection and processing of production data, which are gathered from manufacturing and assembly processes at automotive companies. The solution describes the process for live monitoring of the production health and then evaluation through reports, with the option to generate reports for up to six months. Since the data are located in multiple sources, it is challenging to monitor them live or generate reports on demand. The solution described in this research outlines applications that simplify users’ tasks and provide immediate insights into the processes and health of production lines. Research will be divided into three applications which are delivered in one package, which is called Cycle Time Deviation (CTD): (i) workshop application for live monitoring; (ii) for evaluating data older than 24 h, the shift report application; and (iii) for comparing and monitoring the impact of process changes on the analysis, the before and after application—the Plant Improvement Tracker (PIT)—will be presented. The aim of the research is to describe the proposed solution that was implemented in a multinational automotive corporation and to outline the benefits gained from the implementation.

Evaluating Variables’ Influence on Forwarder Performance and Fuel Efficiency in Mountain Salvage Logging Using an Automatic Work-Element Detection Method

Extreme climate events are increasingly damaging forests, particularly in Europe’s Alps. These disturbances lead to more damaged timber, necessitating rapid salvage operations to preserve timber value and protect ecosystems. However, salvage logging, though essential, raises concerns about its environmental impact, especially on soil conservation and forest regeneration. To mitigate these effects, best practices such as leaving logging residues and avoiding wet soils are recommended. Nevertheless, fuel efficiency remains a critical concern. This study focuses on addressing gaps in understanding forwarder productivity in salvage logging, considering factors such as assortment number, extraction distance, and payload. Utilizing Automatic Work-Element Detection (AWED) for data collection, this study enhances fuel efficiency analysis. Findings show that the average cycle time was 27.4 min, with 4.9 L of fuel consumed per cycle. Each cycle covered 241.3 m, extracting 11.7 m3 of timber, yielding a productivity rate of 31.6 m3 per machine hour and a fuel efficiency of 0.4 L per m3 and per 100 m. Traveling was the most time- and fuel-intensive task. Assortment type significantly impacted loading time and fuel consumption, with short sawlogs requiring fewer crane cycles. Key factors influencing productivity and fuel efficiency were average log volume, distance, payload, and slope.

A Study on the Influence of the Rotating Speed and Load on the Grain Structure and Wear Properties of Bearing Steel GCr15 During Bearing Service

In order to study the wear failure mechanism and structure evolution law of bearings under different speeds and contact loads, an elastoplastic model of a 7009AC bearing was established in this paper. The stress, temperature rise and grain size during dry friction and wear of the bearing inner ring were simulated with the finite element method. The effects of the inner ring speed, load pressure and other parameters on the wear rate were studied. The relationship between the grain size and yield strength of GCr15 bearing steel was obtained. The effects of the initial grain size, rotational speed and load pressure on the bearing wear failure were studied. The evolutions of the grain size during service were predicted by means of the dynamic grain recrystallization (DRX), static grain recrystallization (SRX) and grain growth (GG) subprogram. The results show that the contact stress has a more significant effect on the early failure wear than the bearing speed, and the increase in the contact stress will aggravate the wear rate of the bearing inner ring. Under the same working conditions, the smaller the grain size, the more significant the influence of the cycle times on wear was. The heat-affected zone produced a local high temperature in the contact area, temperature flashes of up to 580 °C could occur in the central contact area, and the temperature decreased gradually with the increase in the depth from the contact area. It is noteworthy that both the surface and the subsurface of the material produced grain refinement; the grain size was refined from 20 μm to 0.4–12 μm under different working conditions. And the degree of refinement of the subsurface was higher than that of the surface.

Optimum pricing decision for the retailer with warranty and price-dependent variable demand

Buying inventory on a credit basis is an effective pricing plan, and trade credit is a popular component of market transactions that increase demand. In a dynamic situation, most businesses offer different rewards and services to their consumers under certain terms and conditions during commodity sales. The accompanying companies provide a warranty period facility to increase consumer demand for products. The holding cost often increases over time. This study determines a production model wherein the production rate is proportionate to the price-warranty period based on the demand rate with time-dependent holding cost and trade credit policy. This work leads to three vital conventions: (I) the rate of product demand is considered to be price-warranty period dependent; (II) the non-linear function is considered for the rate of replacement failure, wherein the capital of the manufacturer depends on the warranty period; and (III) the rate of inflation is constant; moreover, the present time value of money also measured. This study aims to find the selling price, cycle time, and warranty period by using an algorithm to optimize the total profit function of the manufacturer. The results are validated by solving three numerical examples with their graphical representation based on different situations and the major parameters, and sensitivity analysis is analyzed with important decision-making implications.

A New Use Strategy of Artificial Intelligence Algorithms for Energy Optimization in Plastic Injection Molding

Plastic injection molding is a widespread industrial process in manufacturing. This article investigates the energy consumption in the injection molding process of fruit containers, proposing a new use strategy for the application of artificial intelligence algorithms. The aim is to optimize the process parameters, such as the mold temperatures, the injector temperatures, and the cycle time, to minimize energy consumption. This new use strategy, a hybrid use strategy, combines an unsupervised autoencoder with the K-Means algorithm to analyze production data and identify factors influencing energy consumption. The results show the capability of discovering different operating modes at different levels of energy requirements. An analysis of the process parameters reveals that the number of parts left to complete production, the current cycle counter, the number of shots left to complete the production, the material needed to complete the production, and the total time dedicated to production, so far, are the most relevant features for the optimization of the energy consumption per single piece. The study demonstrates the potential of common artificial intelligence algorithms if appropriately used to improve the sustainability of the plastic injection molding process.

EVALUASI CYCLE TIME TERHADAP KONDISI MEDAN PADA PROYEK PEMBANGUNAN AKSES JALAN SAMOTA LANJUTAN KABUPATEN SUMBAWA

The Samota Road access development project continued in Sumbawa Regency is one part of the Samota area development project which acts as access to mobilization and supports the acceleration of development, economy, social and culture. In large-scale road works, heavy equipment is needed to facilitate work in a relatively shorter time. Errors in the operating time of heavy equipment and differences in the work field will affect cycle time and have an impact on productivity. This study aims to determine the amount of heavy equipment cycle time, heavy equipment productivity, and the effect of cycle time on heavy equipment productivity. The methods used in this research are time study and correlation methods. The time study method is a measurement of work by collecting data based on the time needed to complete a job so that productivity can be calculated, while the correlation method is an analysis to determine the level of relationship between the independent variable (X) and the dependent variable (Y).Based on data analysis, the value of cycle time, productivity and the effect of cycle time on heavy equipment productivity were obtained. In segment 1, the cycle time of the motor grader is 303,247 seconds with a productivity of 916,037 m2/hour and the cycle time of the vibratory roller is 612,345 seconds with a productivity of 1061,400 m3/hour. For the effect of cycle time on the productivity of the motor grader, the correlation test result is 0,986 and the vibratory roller is 0,999. In segment 4, the motor grader cycle time is 316,107 seconds with a productivity of 831,112 m2/ hour and the vibratory roller cycle time is 655,370 seconds with a productivity of 988,200 m3/hour. For the effect of cycle time on motor grader productivity, the correlation test results were obtained at 0,975 and vibratory roller at 0,999. In both segments, there is a very strong influence and relationship between variable X (cycle time) and variable Y (productivity).

Mxene and GaIn Alloy Nanostructures Regulate Zn Surface Ion Deposition for High-Performance Zinc-Ion Battery.

Zinc is an ideal energy storage material because of its low toxicity, nonflammability, and good biocompatibility. However, the commercial application is seriously hindered due to problems such as dendrite growth, hydrogen evolution, and interface passivation caused by "dead zinc" in the process of cyclic deposition. Herein, a nanoscale deposition dispersion model is designed in order to achieve directional deposition and uniform distribution of zinc ions for the growth of interfacial dendrites. Liquid metal GaIn was combined with Mxene for this nanostructure, which provides a rapid ion transfer channel to achieve lower overpotentials, a more uniform electric field distribution, and stronger corrosion resistance in a core-shell structure to achieve interface reaction suppression. The material was coated on the surface of the zinc metal as an artificial protective layer. It has a better cycle life at 1 mA·cm-2 compared with the bare Zn metal anode, achieving a long cycle time of 1100 h and an ultralow voltage lag (28.1 mV). It maintains the stability for 1000 cycles at 1 mA·cm-2 after assembling the complete battery. This provides a way to improve the performance of zinc-ion secondary batteries and paves the way for the next generation of energy storage devices.

A Νew Heuristic Optimization Approach to the Single Hoist Cyclic Scheduling Problem

This paper introduces an innovative heuristic optimization approach, referred to as Optimization Approach-Single Hoist Cyclic Scheduling Problem (OA-SHCSP), which aims to minimize the cycle time of the Single Hoist Scheduling Problem (SHCSP). The effectiveness of this proposed heuristic is compared with a previously established heuristic, the Earliest Starting Time (EST). The comparison results reveal that the proposed OA-SHCSP heuristic consistently outperforms the EST heuristic in minimizing cycle time, particularly when more than two products are produced simultaneously. Moreover, as the number of part tasks soaked during a cycle increases, OA-SHCSP demonstrates significantly improved computational efficiency over the EST heuristic. The reduction in average cycle time achieved by OA-SHCSP ranges from 28.73% to 60.29%, underscoring its effectiveness and potential for application in high-volume production environments.

Automation of multiplex biochemical assays to enhance productivity and reduce cycle time using a modular robotic platform

Pharmaceutical and biotechnology companies are increasingly being challenged to shorten the cycle time between design, make, test, and analyze (DMTA) compounds. Automation of multiplex assays to obtain multiparameter data on the same robotic run is instrumental in reducing cycle time. Consequently, an increasing need in automated systems to streamline laboratory workflows with the goal to expedite assay cycle time and enhance productivity has grown in industrial and academic institutions in the past decades. Herein, we present a customized robotic platform with operational modularity and flexibility, designed to automate entire assay workflows involving multistep reagent dispensing, mixing, lidding/de-lidding, incubation, centrifugation, and final readout steps by linking spinnaker robot with various peripheral instruments. Compared to manual workflows, the system can seamlessly execute processes with high efficiency, evaluated by standard assay validation protocols for robustness and reproducibility. Furthermore, the system can perform multiple, independent protocols in parallel, and has high-throughput capacity. In this publication, we demonstrate that the modular robotic platform can fully automate multiplex assay workflows through ‘one-click-and-run’ solution with tremendous benefits in liberating manual intervention, boosting productivity while producing high-quality data combined with reduced cycle time (>20%), as well as expanding the capacity for higher throughput.

Design, Development, and Testing of a Cassava Storage Root-Cutting Robot Utilizing a Stewart Platform and Mask R-CNN for Precision Agriculture

Separating cassava storage root from its stem, known as cassava storage root cutting, represents a pivotal stage in cassava harvesting. It has become increasingly challenging due to a shortage of skilled labor. This research introduces an innovative solution: a cassava storage root-cutting robot (CSRCR) utilizing computer vision technology. The Mask-RCNN model is employed for precise cutting alignment detection. The moving mechanism utilizes a Stewart platform, and the cutting action is performed by a cylinder saw integrated into the robot. The specifications of these components, including dimensions, load capacity, and speed, were meticulously defined and calculated based on a physical survey of cassava plants. The robot's performance was evaluated through a three-step process. First, motion performance was assessed, and the results demonstrated acceptable levels of accuracy, repeatability, and workspace. Second, the optimal moving speed and the cutter's speed were determined. In the third step, the robot was integrated with computer vision technology. The integration achieved a remarkable success rate of 100%. The average loss and trash were minimized to 1.44% and 0.66%, respectively, and the cycle time was 32.43 seconds. This successful integration not only demonstrates the robot's ability to cut cassava stems accurately in various orientations but also significantly improves efficiency by reducing loss and trash. The research findings pave the way for enhanced traditional cassava harvesting practices.

Analysis of work productivity and compatibility of excavation-loading equipment and transport equipment in soil salvaging activities at Katala Hill area of PT. Amman

Abstract PT. Amman Mineral Internasional Tbk in Katala Hill, West Nusa Tenggara Province, Indonesia, is an open-pit mining company producing copper as its main commodity, followed by gold and silver. The initial stage of mining involves soil removal in land clearing activities for reclamation, waste disposal areas, and construction of other infrastructure. In soil salvaging activities, it is essential to understand the influential factors to productivity and the match factor in mechanical equipment, including work efficiency, delay time, cycle time, fill factor, and swell factor. The objective of this study is to determine the productivity and match factor values of the digging-loading equipment and transportation equipment in soil salvaging activities in the Katala Hill area. This study applied the descriptive quantitative method, involving direct field observations of the digging-loading and transportation equipment activities and interviews with mining workers. Based on the results, the actual work efficiency of the digging-loading equipment was 59% and the transportation equipment was 76%, the actual productivity of the digging-loading equipment was 825.00Bcm/h, the transportation equipment productivity was 611.17 Bcm/h, and the compatibility factor value is 0.7408. After increasing the work efficiency of the conveyance by 83%, the conveyance productivity was 667.46 Bcm/h with the match factor increasing to 0.8090.

Experimental analysis on the prototype of decentralised air handling unit with ball-packed regenerator

Decentralised, wall mounted ventilation is one of alternative to typical – cross flow or “heat wheel” recovery air handling units (AHU) system when it is not possible to install it. It solves problems such as the need for more space, power consumption of fans, and investment costs. This experimental study aims to analyse the performance of the unique constructed decentralised air handling unit (DAHU) prototype that has a special balls-packed regenerative heat exchanger. The development of the DAHU also aimed to simplify the operation and production of the unit to make it more affordable and easier to manufacture. As the DAHU is constructed from individually sized components, the pressure losses of the diffuser, the regenerator, the screens to hold the balls, the filter and the fan were measured and the actual DAHU airflow was determined. The general operation of the DAHU was tested in a climatic chamber to determine the appropriate cycle times for this type of device, as well as the heat recovery efficiency at different outdoor air temperatures. Five different DAHU operating cycles were analysed. It was found that the duration of supply air must be longer than the duration of extract air to achieve higher efficiency. Therefore, DAHU's subsequent heat exchanger studies were performed for four airflows. The highest DAHU heat recovery efficiency was achieved (above 70%) with a supply and extract duration of 150 s. It has been found that the efficiency of this DAHU increases with decreasing outdoor air temperature because of the storage properties of the balls. The analysis showed that this type of DAHU could be suitable for use in cooler and colder climates.

Unveiling the effect of cycle time and ambient temperature on the failure mechanisms of commercial LiCoO2/artificial graphite pouch cells

Many efforts have been devoted to investigate failure mechanisms of LiCoO2-based lithium-ion batteries at ≥4.55 vs. Li+/Li. However, most of these works are conducted on coin-type half-cells and rarely consider the effects of cycle time and ambient temperature on mechanisms. So, it calls an alarming demand for making clear the cyclabilities of cells at different temperatures, then differentiating the root causes for their capacity degradations. Herein, the cyclabilities of an ~3.1 Ah commercial LiCoO2/artificial graphite pouch cell at 3–4.45 V are compared at 25 and 60 °C. It is found that the cycle lives at 25 and 60 °C are 2944 and 122 cycles, respectively. The structural variations of the cycled electrodes are systematically studied. Results reveal that the main cause for the capacity beginning to decline after 3000 cycles at 25 °C is the damage of LiCoO2 structure, while its impedance growth and other side reactions are not severe. Differently, the capacity dropping upon cycling at 60 °C is caused by the parasitic reactions including successive electrolyte decomposition, severe cobalt dissolution and Li deposition. Obviously, these findings can provide a theoretical basis for further optimizing of LiCoO2 cells.

Single and multi-objective real-time optimisation of an industrial injection moulding process via a Bayesian adaptive design of experiment approach

Minimising cycle time without inducing quality defects is a major challenge in injection moulding (IM). Design of Experiment methods (DoE) have been widely studied for optimisation of injection moulding, however existing methods have limitations, including the need for a large number of experiments within a pre-determined search space. Bayesian adaptive design of experiment (ADoE) is an iterative process where the results of the previous experiments are used to make an informed selection for the next design. In this study, an experimental ADoE approach based on Bayesian optimisation was developed for injection moulding using process and sensor data to optimise the quality and cycle time in real-time. A novel approach for the real-time characterisation of post-production shrinkage was introduced, utilising in-mould sensor data on temperature differential during part cooling. This characterisation approach was verified by post-production metrology results. A single and multi-objective optimisation of the cycle time and temperature differential (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta T$$\\end{document}) in an injection moulded component is proposed. The multi-objective optimisation techniques, composite desirability function and Nondominated Sorting Genetic Algorithm (NSGA-II) using the Response Surface Methodology (RSM) model, are compared with the real-time novel ADoE approach. ADoE achieved almost a 50\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} reduction in the number of experiments required for the single optimisation of \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta T$$\\end{document}, and an almost 30\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} decrease for the optimisation of \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta T$$\\end{document} and cycle time together compared to composite desirability function and NSGA-II. The optimal settings identified by ADoE for multiobjective optimisation were similar to the selected Pareto optimal solution found by NSGA-II.

Performance assessment of hybrid adsorption/humidification-dehumidification desalination cycle powered by dish/stirling concentrated solar power system for sustainable freshwater production maximization

To achieve sustainable development, it is crucial to prioritize green polygeneration systems capable of generating diverse energy outputs, including electricity, heat, and distilled water, with enhanced efficiencies, reduced costs, and environmentally friendly advantages. Therefore, this study explores an innovative integration for a solar-powered desalination system to present an eco-friendly desalination system that agrees with sustainability goals of eco-friendly clean water and net-zero energy. The proposed system utilizes the waste heat from the solar dish Stirling power engine to drive the adsorption desalination system that is combined with two ejectors, humidification-dehumidification desalination. The humidification-dehumidification utilizes the waste energy from the silica gel-based adsorption desalination system process to enhance the freshwater productivity of the designed integrated system. Comprehensive modeling for the hybrid system components has been formulated using MATLAB to assess the electrical performance and freshwater production of the proposed system. The study also expresses the effect of evaporative-condenser heat recovery in enhancing the freshwater productivity of the hybrid system. Moreover, the effects of cycle time, and evaporator pressure on the performances of the system with and without heat recovery. The findings indicate that the proposed system has the capability to generate an electrical power output of approximately 23.42 kW, achieving a solar-to-electricity efficiency of 23.40 %. Moreover, the proposed system also produces a water production of 47.42 L/hr with a gained output ratio of 2.74. At the same time, the cost estimate revealed that the price of generated freshwater by the planned desalination facility utilizing the heat recovery loop was approximately 0.54 $/m3.

Construction of Lamellar CoFe-LDHs@MoS2 to Promote Permonosulfate Properties Leading to Effective Photocatalytic Degradation of Norfloxacin

The utilization of the photo catalytic activation of permonosulfate (PMS) for the combined breakdown of pollutants has become a focal point in research. Layered double hydroxides (LDHs) have a unique layered structure which is conducive to the adsorption and diffusion of reactants, and can provide more active sites for photocatalytic reactions. The anions between the layers can be exchanged with a variety of substances so that specific catalytically active species can be introduced as needed. LDHs themselves have certain catalytic activity, which can produce synergistic catalysis between LDHs and the supported photocatalytic active substances, and further improve the degradation effect of antibiotics. In actual wastewater treatment, LDHs as a catalyst carrier have a good application prospect. However, the poor activation effect is attributed to the low separation efficiency of catalyst carriers and insufficient active sites. In this study, a dual active site system consisting of Co and Fe, known as CoFe-LDHs@MoS2, was developed as a catalyst to facilitate the synergistic degradation of norfloxacin (NOF) by PMS under visible light. The findings demonstrate that the material possesses an effective capacity for the synergistic degradation of NOF. A comprehensive investigation was conducted to assess the impact of different catalysts, PMS dosage, degradation systems (Vis, PMS, or Vis PMS), catalyst dosage, NOF concentration, pH, and cycle times on the degradation performance. The active free radicals, degradation pathways, and intermediate toxicity were elucidated through capture experiments, Electron Paramagnetic Resonance Spectrometer (ESR) analysis, a liquid mass spectrometry (LC-MS) toxicity assessment, and theoretical calculations. This research offers a novel approach for designing catalysts with exposed high activity sites for the effective removal of NOF from environmental water.

Preparation of water-soluble CdSeS alloy quantum dots with small particle size and high fluorescence lifetime by using hydrodynamic cavitation technology and their application in Ag+ detection

In this study, hydrodynamic cavitation (HC) is used as a novel and simple large-scale preparation technique. Water-soluble CdSeS alloy quantum dots (QDs) were successfully prepared by using Cd(NO3)2·4H2O, Na2S·9H2O and selenium powder as cadmium, sulfur and selenium sources. The effects of cycle time, reaction temperature, inlet pressure and Se/S molar ratio on the morphology, size and optical properties of CdSeS QDs were investigated. The prepared CdSeS QDs were characterized by X-ray diffractometer, X-ray photoelectron spectroscopy, transmission electron microscopy, UV–vis absorption spectra, fluorescence emission spectra and fluorescence attenuation curves. Finally, under the conditions of 12 h cycle time, 3.0 bar inlet pressure, 60 °C reaction temperature and 0.5/0.5 Se/S molar ratio, the ternary alloy CdSeS QDs with 2.62 nm average particle size and 482.62 ns fluorescence lifetime was obtained. Furthermore, a mechanism of preparing CdSeS QDs by using the HC method was proposed to explain the process of CdSeS precipitates conversion to CdSeS QDs. In addition, it is also found that Ag+ has a quenching effect on the prepared CdSeS QDs, which means that CdSeS QDs can be used as a fluorescence probe to specifically detect Ag+. This work not only provides a new possibility for large-scale preparation of high-performance QDs but also helps to understand the mechanism of CdSeS QDs as a metal ion selective fluorescence probe.

Main Heat Transfer Mechanisms in Hot Stamping Processes: a Review

Objectives: The article reviews heat transfer mechanisms in the hot stamping process, highlighting models to calculate the interfacial heat transfer coefficient (IHTC), crucial for optimizing the cooling and quality of formed products. Theoretical Framework: In hot stamping of high-strength steels, the IHTC is affected by variables such as contact pressure, roughness and temperature. Cooling efficiency directly impacts the temperature distribution and martensitic microstructure of the material, essential for structural strength. Method: The review compares IHTC calculation methods, such as inverse heat conduction analysis and Newton's law of cooling, detailing the convection, radiation and conduction mechanisms at each stage of the process: transfer, positioning and forming. Results and Discussion: The inverse heat conduction analysis proved to be the most accurate for determining the IHTC, compared to the finite element method (FEM). The study suggests that efficient cooling channels and high conductivity materials in the matrix reduce cooling time and improve the quality of the final product. Research Implications: Findings provide a basis for improving thermal management in hot stamping, reducing cycle time and increasing productivity. Originality/Value: This work contributes a comprehensive reference on IHTC, assisting researchers and engineers in optimizing heat transfer and production efficiency in the manufacture of automotive components.