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This article discusses the problem of evaluating performance and optimising the design of Automated Storage/Retrieval Systems (AS/RS) in a steady state, with a focus on the dual cycle in the bidirectional flow-rack (BFR) AS/RS. To accomplish this, two well-known approaches (discrete and continuous) are utilised to model the dual cycle time. The developed models reveal that the system is near optimal when designed to be square in time. Furthermore, the continuous models are shown to be relatively accurate compared to the discrete counterparts, with discrepancies under 6%. Subsequently, the optimal dimensions of the system are identified through design optimisation aimed at minimising the cycle time. The findings indicate the optimal depth decreases as load rate increases, while optimal height and length follow a cubic root function of system volume. Approximate formulas are derived, allowing for direct calculation of optimal dimensions based on the system size and its load rate. Finally, the article evaluates the system's overall performance by calculating its throughput, providing a tool to estimate capacity. These findings provide an essential tool for optimising the system's performance in a steady state during the upstream design and installation phase, prior to making significant investments. [ABSTRACT FROM AUTHOR]

O and Nb are two representative alloying elements of Ti to form high-temperature and corrosion resistance α Ti alloys. The investigation on the thermodynamic characteristics of α Ti–O and Ti–Nb has attracted much attention in recent years. However, in this regard, a satisfied experimental technique or modeling scheme is still yet to be developed due to the appearance of a variety of oxides in Ti–O and the mechanical instability present in Ti–Nb. Herein, we combined first-principles calculations with the cluster expansion method to investigate the ground-state characteristics for α Ti–O and α Ti–Nb systems. The atomic bonding interactions in these two systems were first revealed based on the calculated electronic structures. Afterward, the Debye–Grüneisen model and Monte Carlo simulations were employed together to investigate the thermodynamic properties of α phases in these two systems, and the effect of vibrational entropy on the order–disorder transition temperatures of the phases in α Ti–O system was first examined. A good agreement with experimentally reported phase boundaries is obtained in the Ti–Nb system by handling the mechanical instabilities introduced by the highly distorted structures. In addition, the cluster expansion coefficients for the Ti–O and Ti–Nb system offer a good starting point to investigate the phase equilibrium in Ti–Nb–O ternary alloy. We also believe the insights provided here would be helpful for those who would like to seek an efficient scheme they are confident with to investigate the phase thermodynamic properties of other hcp Ti-based alloys. [ABSTRACT FROM AUTHOR]

This paper introduces a novel autonomous vehicle-based storage and retrieval system that utilizes movable lifts (AVS/RS/ML), proposed as an alternative to the tier-captive shuttle-based storage and retrieval system (SBS/RS). The newly proposed system aims to provide an affordable solution with highly utilised AGVs, that can also perform operations out of warehouse. The performance of this novel system is compared with the equivalent tier-captive SBS/RS warehouse design, where each shuttle is dedicated in a specific tier in that design. The comparison is based on the initial system investments costs, throughput rates, and average utilisation of lifts/MLs in the system. Collision prevention rules are also applied to AVS/RS/ML, and its performance is tested through simulation. The results show that the tier-captive SBS/SR system becomes cost-efficient under high throughput rate requirements, while the AVS/RS/ML technology is preferred for relatively moderate and low process rate requirements. The unit-cost per month performance metric of AVS/RS/ML is less sensitive to an increase in number of tiers in the system, compared to the tier-captive SBS/RS case, indicating that AVS/RS/ML may be promising for high-tier warehouse system designs. [ABSTRACT FROM AUTHOR]

The evaluation of thermoelectric materials relies significantly on the thermoelectric figure of merit, ZT, which serves as a crucial parameter in assessing their properties. The accurate prediction of ZT values can be accomplished by utilizing machine learning models to learn material characteristics. However, factors such as the size of the dataset, model hyperparameters, and data quality can all impact the accuracy of machine learning. In contrast to previous research where high-dimensional features were simply discarded to transform them into low-dimensional ones, deep learning models such as autoencoder can extract more effective information. Therefore, in this article, the combination of autoencoders and the Light Gradient Boosting Machine (LightGBM) is employed to learn the chemical characteristics and ZT values of various materials. The reliability of the model was confirmed by achieving an R2 score of 0.94 during tenfold cross-validation. 130 000 materials were predicted and screened, the temperature dependence of the screened materials was studied in depth, and 13 materials with high ZT values were identified. Four of the 13 most promising candidates identified are existing thermoelectric materials, while nine are ideal candidates for future experimental studies and validation. This work utilizes autoencoders for extensive prediction and screening of promising materials, providing an effective approach for handling high-dimensional material data. [ABSTRACT FROM AUTHOR]

Dynamic facility layout planning (DFLP) involves determining an appropriate arrangement scheme of the elements making up the production system for each time period into which the planning horizon is divided. When formulating the problem as an optimisation model, using the traditional top-down approach is usual, which firstly determines the block layout (BL) and then the detailed layout (DL) of each work cell. However by this approach, the BL generates area constraints in the detailed phase, which sometimes limit its implementation. In this context, the present paper presents a multi-objective mixed integer non-linear programming (MOMINLP) model that allows the problem to be addressed by considering an alternative approach, known in the literature as the bottom-up approach. The proposed model, called bottom-up mDFLP, considers three objective functions: (1) minimise the total material handling cost (TMHC) and the total rearrangement cost (TRAC); (2) maximise the total closeness rating (TCR) between departments; (3) maximise the area utilisation ratio (AUR). The original MOMINLP is transformed into a more computationally efficient multi-objective mixed integer linear programming (MOMILP) model. The proposed model is applied and validated in a case study of a company in the metal-mechanic sector with 12 departments for three 4-month periods. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) provides new opportunities to improve manufacturing lines' performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains' fleet was improved, and (iii) the daily path was minimized. [ABSTRACT FROM AUTHOR]

Previous research on automated guided vehicles (AGVs) and Industry 4.0 has mainly focused on technical aspects, while the humans who work with AGVs as well as the influences on the organisation have received limited attention. This paper aims to explore human- and organisation-related challenges in the introduction of AGVs in production facilities. Two cases are examined and analysed using the Human, Technology, and Organisation (HTO) model, which highlights the interactions between the three subsystems: human, technology, and organisation. The paper shows that several human- and organisation-related challenges arise when introducing AGVs, such as supporting the AGVs with new work procedures for managing AGV errors, determining what different operators need to know about AGVs, and developing acceptance among employees. The identified challenges complement the technical focus in previous research. Actions are proposed to facilitate the introduction of AGVs to avoid or manage the identified challenges. The findings of this study can help managers involved in the introduction of AGVs to consider human- and organisation-related aspects to improve AGV performance and employee well-being. [ABSTRACT FROM AUTHOR]

This paper deals with mobile-rack automated storage/retrieval systems (AS/RS) that are a particular physical configuration of unit-deep AS/RS, i.e. the class of systems where each cell is designed to contain a single load. There are two main contributions in this paper: the first one is the analytical modelling of the average single-cycle time for mobile-rack AS/RS. The approach adopted for modelling is based on a continuous approximation, which is not recent, however, the approach proposed here for the transition from the discrete to the continuous models is different from those used previously in the literature. In a certain way, the multi-aisle and unit-load configurations can be seen as special cases of the mobile-rack configuration. This allows to deduce analytical models for the average single-cycle time for these two configurations from the one developed for mobile rack. The second main contribution of this paper is to find the dimensions of the AS/RS that minimise the average single-cycle time. The optimisation has been studied formally for the multi-aisle and unit-load configurations, and numerically for the mobile-rack configuration. [ABSTRACT FROM AUTHOR]

In material processing and handling processes, premixed interlayer often replace the ideal Ni/Al interface, which would become a new origin of alloying reaction. This work investigates shock-induced reaction mechanism and kinetics of premixed Ni/Al nanolaminates with molecular dynamics simulations and theoretical analysis. The reaction is found to be driven by the crystallization evolution in premixed interlayer and the diffusion of premixed atoms. Among them, multi-stage reaction patterns are strongly manifested by the crystallization evolution characteristics. Specifically, "crystallization-dissolution-secondary growth" and "crystallization-dissolution" of B2 phase respectively correspond to the solid-state and solid-liquid reaction cases, where crystallizations are fitted well by Johnson–Mehl–Avrami kinetics model. Interestingly, the different growth mechanisms of B2 grain are revealed, namely nuclei coalescence and atomic diffusion. Moreover, the analysis of microscopic diffusion theory indicates a certain non-random diffusion nature for solid-state reaction initiation, but near-purely random diffusion for solid-liquid reaction initiation. The diffused Al atoms possess a limited diffusion coefficient and enhanced diffusion correlation, resulting in extremely slow mixing rate in Ni layer. In addition, the influence law of Ni concentration in premixed interlayer on reactivity parameters can be quantitatively described by a quadratic function. [ABSTRACT FROM AUTHOR]

Markerless motion capture has been made available by the development of pose estimation algorithms that provide both an estimate of the location of body keypoints in two-dimensional images and its associated confidence. It seems relevant to use this additional information for three-dimensional (3D) point reconstruction. Yet, it has been little described, nor has its influence on 3D point reconstruction. Eight participants performed a manual material handling task, which was recorded by 10 video cameras. Each video was processed using OpenPose. Different 3D point reconstruction methods were compared: direct linear transform (DLT) and weighted DLT (wDLT), with 10 cameras and with a subset of 4 cameras. For each keypoint, confidence and position deviation from the 3D reconstructed point with 10 cameras projected in the image reference frame were assessed. Results suggest that using confidence information reduces both average and maximum 3D distance between 3D points reconstructed with 4 and 10 cameras. [ABSTRACT FROM AUTHOR]

The current paper focuses on developing and designing a not actively driven module for material handling operations in the field of intra-logistic. This device, belonging to the class of systems known as smart surfaces, is planned to be assembled with others to create manipulative arrays. As a novel feature, the reported concept aims to generate the frictional forces required for surface operation avoiding motors and with a simplified design. The article not only presents the design of the concept, but also the analytic models used to describe its operation and handling forces. In addition, a characterization of the fundamental parameters and the validation of the mentioned analytic descriptions together with the functioning itself are reported. As result, the analysis and the measurements presented show a real solution for a not actively driven concept, along with a methodology to characterize it and predict its handling capabilities. Specifically, the validation test proved that the model is able to represent the behavior of the friction forces with relative errors mainly in the range of 10% or lower. [ABSTRACT FROM AUTHOR]

Haulage-truck fuel consumption is one of the costliest consumables in materials handling in mining. This systematic literature review aims to determine the techniques for predicting fuel consumption, the accuracy measures of the prediction techniques proposed by the selected studies, and parameters influencing haulage-truck fuel consumption. A systematic literature review of published studies on the prediction of haulage-truck fuel consumption in open-pit mining was conducted. Thirty-six (36) relevant studies were identified from 2010–2021. These reported different prediction techniques, e.g. ANN, CBR, MILP, and different performance metrics. The study further reported different parameters influencing haulage-truck fuel consumption using different prediction techniques and parameters. From the studies, it was evident that payload and speed are the highly used parameters in predicting fuel consumption. [ABSTRACT FROM AUTHOR]

The existing logistics practices frequently lack the ability to effectively handle disruptions. Recent research called for dynamic, digital-driven approaches that can help prioritise allocation of logistics resources to design more adaptive and sustainable logistics networks. The purpose of this study is to explore inter-dependencies between physical and digital assets to examine how cyber-physical systems could enable interoperability in logistics networks. The paper provides an overview of the existing literature on cyber-physical applications in logistics and proposes a conceptual model of a Cloud Material Handling System. The model allows leveraging the use of digital technologies to capture and process real-time information about a logistics network with the aim to dynamically allocate material handling resources and promote asset and infrastructure sharing. The model describes how cloud computing, machine learning and real-time information can be utilised to dynamically allocate material handling resources to product flows. The adoption of the proposed model can increase efficiency, resilience and sustainability of logistics practices. Finally, the paper offers several promising research avenues for extending this work. [ABSTRACT FROM AUTHOR]

Automated guided vehicle (AGV) scheduling has become a hot topic in recent years as manufacturing systems become flexible and intelligent. However, little research regards dynamic AGV scheduling considering energy consumption, particularly battery replacement. This paper proposes a novel method that employs deep reinforcement learning to address the dynamic scheduling of energy-efficient AGVs with battery replacement in production logistics systems. The bi-objective joint optimization problem of AGV scheduling and battery replacement management is modeled as a Markov Decision Process, which supports data-driven decision-making. Then, this paper constructs a deep reinforcement learning-based optimization architecture and develops a novel dueling deep double Q network algorithm to maximize the long-term rewards for optimizing material handling's tardiness and energy consumption. Numerical experiments and a case study demonstrate that the proposed algorithm is more efficient and cleaner than state-of-the-art methods. The proposed method can significantly improve customer satisfaction and reduce production costs within flexible manufacturing processes, particularly in Industry 4.0. [ABSTRACT FROM AUTHOR]

Heavy‐duty construction tasks implemented by hydraulic manipulators are highly challenging due to unstructured hazardous environments. Considering many tasks have quasirepetitive features (such as cyclic material handling or excavation), a multitarget adaptive virtual fixture (MAVF) method by teleoperation‐based learning from demonstration is proposed to improve task efficiency and safety, by generating an online variable assistance force on the master. First, the demonstration trajectory of picking scattered materials is learned to extract its distribution and the nominal trajectory is generated. Then, the MAVF is established and adjusted online by a defined nonlinear variable stiffness and position deviation from the nominal trajectory. An energy tank is introduced to regulate the stiffness so that passivity and stability can be ensured. Taking the operation mode without virtual fixture (VF) assistance and with traditional weighted adaptation VF as comparisons, two groups of tests with and without time delay were carried out to validate the proposed method. [ABSTRACT FROM AUTHOR]

In material handling, numerous solutions have been proposed to enhance the flexibility and adaptability of transport systems. Among these solutions, smart surfaces stand out as one of the most interesting responses, utilizing an array of actuators for common feeding tasks. The current paper focuses on a novel system within this category, notable for its distinguishing factor of being underactuated. With this characteristic, the concept leads to a simplified cost-effective design and a not actively driven functioning, leveraging gravity or object own velocity to manipulate the material flow maintaining top class performances, as the sorting rate reaches 4000 pcs/h. Specifically, the article begins with an introduction of the concept design and its digital model, followed by a description of the experimental setup built to test the surface's functionality and evaluate the predictions of the virtual counterpart. On top of that, a method to determine the essential parameters for the surface simulation is proposed and applied. As a result, the prototype successfully completed the three main intralogistic tasks experimented, i.e., sorting, slowing, and stopping of packages. Lastly, the digital model outcomes of the same operations were computed and compared with the measured results, demonstrating an accuracy of prediction with displacements and time errors below 7%. [ABSTRACT FROM AUTHOR]

Ultra‐fast magic‐angle spinning (100+kHz) has revolutionized solid‐state NMR of biomolecular systems but has so far failed to gain ground for the analysis of paramagnetic organic and inorganic powders, despite the potential rewards from substantially improved spectral resolution. The principal blockages are that the smaller fast‐spinning rotors present significant barriers for sample preparation, particularly for air/moisture‐sensitive systems, and are associated with low sensitivity from the reduced sample volumes. Here, we demonstrate that the sensitivity penalty is less severe than expected for highly paramagnetic solids and is more than offset by the associated improved resolution. While previous approaches employing slower MAS are often unsuccessful in providing sufficient resolution, we show that ultra‐fast 100+kHz MAS allows site‐specific assignments of all resonances from complex paramagnetic solids. Combined with more reliable rotor materials and handling methods, this opens the way to the routine characterization of geometry and electronic structures of functional paramagnetic systems in chemistry, including catalysts and battery materials. We benchmark this approach on a hygroscopic luminescent Tb3+ complex, an air‐sensitive homogeneous high‐spin Fe2+ catalyst, and a series of mixed Fe2+/Mn2+/Mg2+ olivine‐type cathode materials. [ABSTRACT FROM AUTHOR]

Due to the handling of flammable materials, offshore oil facilities are at risk of fire, endangering crew and structure. This study aims to predict fire load and structural response, focusing on a hydrocarbon fire on an offshore platform in the Gulf of Mexico. Simulations were conducted in sections due to the platform's size, with fire load estimated for the considered fire scenario. The fire dynamic simulator (FDS) using PyroSim, a CFD tool, was used to estimate time-temperature curves, with mesh size determined by a convergence study and wind effects considered. The FDS simulation data was input into Abaqus for a detailed structural response analysis. A heat transfer analysis simulated node temperatures during fire exposure, followed by a structural analysis considering high-temperature material properties. The structural response at critical points was observed and discussed. The discussion revolves around the fire rating derived from the study's results. [ABSTRACT FROM AUTHOR]

At present, China's coal mine permanent tunneling support commonly uses mechanized drilling and anchoring equipment; there are low support efficiency, labor intensity, and other issues. In order to further improve the support efficiency and liberate productivity, this paper further researches the trajectory planning of the drilling and anchoring materials of the robotic arm for the drilling machine "grasping–carrying–loading–unloading" on the basis of the drilling and anchoring robotic system designed by the team in the previous stage. Firstly, the kinematic model of the robotic arm with material was established by improving the D-H parameter method. Then, the working space of the robotic arm with the material was analyzed using the Monte Carlo method. The singular bit-shaped region of the robotic arm was restricted, and obstacles were removed from the working space. The inverse kinematics was utilized to solve the feasible domain of the robotic arm with material. Secondly, in order to avoid blind searching, the guidance of the Bi-RRT algorithm was improved by adding the target guidance factor, and the two-way tree connection strategy for determining the feasible domain was combined with the Bi-RRT algorithm's feasible domain judgment bi-directional tree connection strategy to improve the convergence speed of the Bi-RRT algorithm. Then, in order to adapt to the dynamic environment and avoid the global planning algorithm from falling into the local minima, on the basis of the above planning methods, an improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field was proposed, which takes the planned paths as the guiding potential field of the artificial potential field to make full use of the global information and avoid falling into the local minimization. Finally, a simulation environment was built in a ROS environment to compare and analyze the planning effect of different algorithms. The simulation results showed that the improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field improved the optimization speed by 69.8% and shortened the trajectory length by 46.6% compared with the traditional RRT algorithm. [ABSTRACT FROM AUTHOR]

Dryers are designed once but then operate for many years, and it is important to have systematic methods to solve problems when they arise. Kemp and Gardiner proposed a systematic methodology in 2001, based on categorization of problems into five main types and a divergent-convergent algorithm to identify both root causes and potential solutions. This approach to troubleshooting has proved successful for dryers in a range of industries. This article reviews the experience gained, some resulting improvements, and overlap and synergy with other investigation methods such as Lean Six Sigma techniques. An extensive range of case studies is given, illustrating the successful application of the methodology to many different situations and dryer types. The broad approach has remained the same but various points of detail have been added. Appropriate theoretical models can give useful insights, often using quite simple methods such as heat and mass balances and drying times estimated with first-order kinetics. The insights can solve other drying-related problems such as caking in storage. The methods can also be used for process improvement, debottlenecking, and enhanced product quality. [ABSTRACT FROM AUTHOR]

• A novel redundantly actuated series-parallel manipulator is proposed. • Unified recursive kinematics and statics models of the manipulator are established. • The theoretical model is validated by comprehensive numerical results. • Load/mass ratio of the tested manipulator in non-redundant actuation mode is 1.34. • The manipulator has higher load-carrying capacity in redundant actuation mode. Construction robots with mobile systems are an integral part of automatic building processes. However, with the vigorous development of prefabricated buildings, traditional manipulators have progressively failed to satisfy the requirements of handling heavy materials on construction sites. Thus, this paper proposes a redundantly actuated series-parallel manipulator (RAS-PM). To explore the feasibility of applying the manipulator in construction tasks, this paper establishes the unified recursive kinematics and statics of the manipulator and verifies the validity and reliability of the theoretical modeling method through comprehensive numerical results. The prototype of the manipulator is developed and installed on a bionic hexapod construction robot. The test results demonstrate that the manipulator exhibits an excellent load/mass ratio in non-redundant actuation mode, and its load-carrying capacity can be further enhanced with the optimized force/position hybrid actuation. In the on-site test, the robot can freely switch between modes to handle horizontal and vertical states of materials, such as curtain walls and large panels, thereby contributing to modern prefabricated construction. [ABSTRACT FROM AUTHOR]

To address the parameter instability issues in hazardous materials handling during multi-machine loading and unloading operations, we propose a Full-Scale Smart Parameter Optimization Control (FSPOC) system specifically designed for multi-machine coordination. This system leverages a novel fish scale prediction algorithm tailored for cooperative multi-machine environments. Initially, the fish scale prediction algorithm, inspired by bionic fish scales, is developed to predict future system behavior by analyzing historical data. Building on this algorithm, we introduce a disturbance cancellation control theorem and design a parameter optimization controller to enhance stability in high-dimensional nonlinear spaces. The FSPOC method is then applied to a multi-machine cooperative system, enabling online distributed parameter optimization for complex systems with multiple degrees of freedom. The effectiveness of the proposed method was validated through simulations, where it was compared with two other optimization techniques: Genetic Algorithm-based PID (GAPID) and Chaotic Atomic Search Algorithm-based PID (CHASO). The simulation results confirm the superiority of the FSPOC method. [ABSTRACT FROM AUTHOR]

AbstractThe aim of this study was to append a passive soft back exoskeleton to a validated musculoskeletal model and assess its effectiveness in reducing lumbar loads. Fifteen participants lifted a box, with and without wearing a CORFOR® exoskeleton. A full body OpenSim model was used to estimate lumbar joint moments and reaction forces, as well as low back muscles forces. Wearing the exoskeleton reduced the peak flexion moment, muscles forces, as well as peak compressive and shear forces. This musculoskeletal modelling study shows that wearing the exoskeleton may reduce lumbar spine loads and may contribute to prevent low back disorders. [ABSTRACT FROM AUTHOR]

Material handling tasks often lead to skeletal injury of workers. The whole-body static biomechanical modeling method based on virtual humans is the theoretical basis for analyzing the human factor index in the lifting process. This paper focuses on the study of humans' body static biomechanical model for virtual human ergonomics analysis: First, the whole-body static biomechanical model is constructed, which calculates the biomechanical data such as force and moment, average strength, and maximum hand load at human joints. Secondly, the prototype model test system is developed, and the real experiment environment is set up with the inertial motion capture system. Finally, the model reliability verification experiment and application simulation experiment are designed. The comparison results with the industrial ergonomic software show that the model is consistent with the output of the industrial ergonomic software, which proves the reliability of the model. The simulation results show that under the same load, the maximum joint load and the maximum hand load are strongly related to the working posture, and the working posture should be adjusted to adapt to the load. Upright or bent legs have less influence on the maximum load capacity of the hand. Lower hand load capacity is due to forearm extension, and the upper arm extension greatly reduces the load capacity of the hand. Compared with a one-handed load, the two-handed load has a greater load capacity. [ABSTRACT FROM AUTHOR]

AbstractThe reconfigurable manufacturing system (RMS) is an advanced manufacturing strategy that enables precise adjustment of functionality and capacity to meet fluctuating demands economically. RMS focuses on part families, allowing configurations to be adapted for new part requirements. Optimizing flow line design to produce various parts involves minimizing reconfigurations and associated costs by enhancing operation sequence similarity. This article proposes a novel sequence optimization using the Longest Common Subsequence (LCS) method to reduce bypassing moves and machine idle times. The study introduces a similarity coefficient derived from LCS and employs average linkage hierarchical clustering to categorize parts in a case study. Unlike traditional methods, this approach considers material movements both before the initial machine and after the final processing station, addressing gaps in bypassing move calculations. The impact of different weighting scenarios for Type-II moves (ω) and machine idleness (β) on clustering was examined. For example, with Type-II move weights (ω) of {1.0, 0.6, 0.3, 0.0} and equal weightings for bypassing moves (α) and machine idleness (β) set at 0.5, a threshold value of 0.3 results in eight clusters, such as Cluster 1 {1, 11, 10, 12} and Cluster 3 {3, 5, 6, 4, 15, 9, 13, 14, 7, 8}. Lower threshold values lead to fewer clusters with larger sizes, indicating a more consolidated part family grouping. Various Type-II move weights and material handling scenarios demonstrate how different weighting configurations affect clustering and part family sizes. This approach enhances RMS efficiency by integrating comprehensive material handling considerations and optimizing clustering based on operational similarities. [ABSTRACT FROM AUTHOR]

Mesocrystals are ordered nanoparticle superstructures, often with internal porosity, which receive much recent research interest in catalysis, energy storage, sensors, and biomedicine area. Understanding the mechanism of synthetic routes is essential for precise control of size and structure that affect the function of mesocrystals. The classical synthetic strategy of mesocrystal was formed via self-assembly of nanoparticles with a faceted inorganic core but a denser (or thicker) shell of organic molecules. However, the potential materials and synthetic handles still need to be explored to meet new applications. In this work, we develop a non-classical synthetic strategy for organic molecules, such as tetrakis (4-hydroxyphenyl) ethylene (TPE-4OH), tetrakis (4-bromophenyl) ethylene (TPE-4Br), and benzopinacole, to produce mesocrystals with composed of microrod arrays via co-solvent-induced crystal transformation. The aligned nanorods are grown epitaxially onto organic microplates, directed by small lattice mismatch between plates and rods. Thus, the present work offers general synthetic handle for establishing well-organized organic mesocrystals. [ABSTRACT FROM AUTHOR]

In recent years, manufacturers have increasingly applied automation techniques to enhance efficiency and remain competitive. Material handling is an essential activity in any production process. Its effectiveness has a significant impact on production costs. Automated guided vehicle (AGV) systems have become a strategic tool for factories and automated warehouses. They can reduce production costs and improve delivery times in a competitive business scenario. One of the main problems encountered in managing AGVs is the dispatching decision. The present paper proposes a vehicle dispatching system based on a multi-attribute cascaded fuzzy system with a state-space-based Petri net model to predict the future states of the factory. This work aims to reduce the production system's makespan and/or tardiness values. Additionally, the paper presents one simulated factory scenario to evaluate the proposed fuzzy system against five other dispatching methods. The statistical validation results of the simulations show a 97% confidence level in the hypotheses of this work. [ABSTRACT FROM AUTHOR]

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Assessing musculoskeletal disorders (MSDs) in the workplace is vital for improving worker health and safety, reducing costs, and increasing productivity. Traditional hazard identification methods are often inefficient, particularly in detecting complex risks, which may compromise risk management. This study introduces a semi-automatic platform using two motion capture systems—an optical system (OptiTrack®) and a Bluetooth Low Energy (BLE)-based system with inertial measurement units (IMUs), developed at the Biomedical Engineering Laboratory, Universidad de Concepción, Chile. These systems, tested on 20 participants (10 women and 10 men, aged 30 ± 9 years without MSDs), facilitate risk assessments via the digitized NIOSH Index method. Analysis of ergonomically significant variables (H, V, A, D) and calculation of the RWL and LI showed both systems aligned with expected ergonomic standards, although significant differences were observed in vertical displacement (V), horizontal displacement (H), and trunk rotation (A), indicating areas for improvement, especially for the BLE system. The BLE Inertial MoCap system recorded mean heights of 33.87 cm (SD = 4.46) and vertical displacements of 13.17 cm (SD = 4.75), while OptiTrack® recorded mean heights of 30.12 cm (SD = 2.91) and vertical displacements of 15.67 cm (SD = 2.63). Despite the greater variability observed in BLE system measurements, both systems accurately captured vertical vertical absolute displacement (D), with means of 32.05 cm (SD = 7.36) for BLE and 31.80 cm (SD = 3.25) for OptiTrack®. Performance analysis showed high precision for both systems, with BLE and OptiTrack® achieving precision rates of 98.5%. Sensitivity, however, was lower for BLE (97.5%) compared to OptiTrack® (98.7%). The BLE system's F1 score was 97.9%, while OptiTrack® scored 98.6%, indicating both systems can reliably assess ergonomic risk. These findings demonstrate the potential of using BLE-based IMUs for workplace ergonomics, though further improvements in measurement accuracy are needed. The user-friendly BLE-based system and semi-automatic platform significantly enhance risk assessment efficiency across various workplace environments. [ABSTRACT FROM AUTHOR]

This paper is devoted to presenting the results of the computer-aided design, the multibody dynamic analysis, and the proportional-derivative control synthesis of an adaptive mechanism serving as a lifting table. More specifically, the first part of the manuscript deals with the methodological approach and the mathematical background employed in the entire research work, whereas the second part of the present paper is focused on the model development and the numerical experiments carried out in this investigation. The analytical derivations presented herein demonstrate that the desired adaptive behavior can be successfully obtained for the virtual prototype of the lift mechanism devised in this investigation. Furthermore, a detailed CAD model of the proposed design was constructed in this investigation using SOLIDWORKS. To this end, particular attention was paid to the actual assembly and disassembly of each mechanical component, in conjunction with the choice of the actuators and sensors that are necessary for the proper functioning of the lifting mechanism. Then, a three-dimensional multibody model was developed starting from the CAD model of the virtual prototype devised in this investigation. The resulting multibody model, following appropriate simplifications, was subsequently imported into the MATLAB virtual environment, thereby allowing for readily performing kinematic and dynamic simulations of the nonlinear behavior of the mechanical system under study by using the SIMSCAPE MULTIBODY computational software. By doing so, the development of an appropriate control strategy, as well as the analysis of its behavior under loading and unloading goods conditions, was carried out and tested in the case of four different scenarios considered as the case study. For this purpose, the applicative scenarios considered are: 1) an impulsive loading scenario; 2) a progressive loading scenario; 3) an impulsive unloading scenario; 4) and a progressive unloading scenario. The performance of the feedforward plus feedback control strategy devised in this study was discussed based on several computer simulations. Numerical simulations demonstrate that the desired adaptive behavior is successfully obtained for the virtual prototype of the lift table designed in this study. [ABSTRACT FROM AUTHOR]

The tools used during mobilities are very diverse, but their operation and structure can be traced back to the same basic principles that created the material handling machines during the previous centuries. Today, knowledge of material handling machines has become a basic necessity not only for industrial and service processes, but also for people's everyday lives, since our lives are almost unimaginably filled with different means of transportation, or without using the vehicles that transport and load our daily consumer goods. As in all areas, material handling is becoming more and more modern, and equipment that serves social and economic needs at a high level is used. One of the most defining characteristics of today's consumer society is extremely rapid change, which also affects our devices, so the design of material handling machines is also constantly changing. An important question of competitive service is how to meet rapidly changing needs. In my article, I review the development of material handling equipment, or the most important handling machines used in modern systems. Based on the outlined processes and technical changes, I will try to show where material handling is headed, what trends prevail today or are expected in server systems of the near future. [ABSTRACT FROM AUTHOR]

This paper reports on the evaluation and stabilization/solidification (S/S) of a thixotropic, silica-rich slurry sediment (SS) media from a 14.2-ha (35-acre) unlined lagoon that exhibited flash setting behavior when contacted with low doses (≤5 wt%) of portland cement (PC), transforming it into sticky, tacky peanut butter-like solid in less than 20 s. This presented a significant challenge for material handling. Meanwhile, the high initial unconfined compressive strength (UCS) at 3 and 7 days decreased by 50% by 28 days, indicating metastability. Numerous mix designs that increased calcium content were explored to mitigate the flash setting behavior and strength loss. Higher PC-only doses could not be effectively homogenized in the lab. Mix designs with hydraulic lime, agricultural lime, or calcium chloride (road salt) brine solutions were mixable, and the latter two maintained high UCS. EPA Leaching Environmental Assessment Framework (LEAF) tests (Methods 1313, 1315, and 1316) were used to characterize leaching from the SS media, which contained 400–800 µg/L arsenic (As) in its natural liquefied state. Despite the high concentrations in the SS, dissolved As levels in two groundwater wells immediately downgradient of the lagoon were below the regional groundwater criterion for As of 10 µg/L. EPA 1313 testing on the untreated SS media revealed that As leaching was independent of pH, and EPA 1316 testing indicated that As was available-content controlled, making dilution effects fairly predictable. EPA 1315 (extended to 120 days) and 1316 testing on select intact and crushed S/S mix designs, respectively, showed that the long-term EPA 1315-As water bath concentrations and those of crushed (simulated reworked surface) ISS samples were ≤10 µg/L. It was thought that the leaching of calcium and silica would be lower from high-strength mix designs since calcium silica hydrate compounds are responsible for high strength. On the contrary, silica leaching (100–200 mg/L as SiO2) was regulated by amorphous silica and independent of UCS. Calcium concentrations ranged from 20 to 30 mg/L and were likewise similar for all mix designs. [ABSTRACT FROM AUTHOR]

Digital servitization (DS) enabled by the Industrial Internet of Things (IIoT) is essential for securing long-term competitiveness in manufacturing. The literature identifies the need for developing data models for multichannel communications across IIoT devices that fulfil the DS vision. This is crucial for avoiding isolated systems based on proprietary solutions and for promoting data sharing and interoperability across existing and future DS applications. Accordingly, this study proposes a data model for multichannel communication that facilitates IIoT-enabled DS for smart production logistics (SPL). We present three findings from a case study focussing on material handling in a manufacturing company. First, this study provides a model with four modelling profiles, including IIoT devices, databases, and services for multichannel communication. Second, it shows how the proposed modelling profiles transfer information across monitoring, control, optimisation, and autonomous decision services. Third, it presents the operational benefits of applying the proposed data models, including improvements in the delivery, makespan, and energy of material handling. These findings are essential for capturing, processing, and transferring information across products, services, and software databases in IIoT-enabled DS for SPL. They are relevant for manufacturing managers and academics and improve our understanding of IIoT-enabled DS's deployment for SPL in manufacturing. [ABSTRACT FROM AUTHOR]

A novel dielectric scheme is proposed for strongly coupled electron liquids, which handles quantum mechanical effects beyond the random phase approximation level and treats electronic correlations within the integral equation theory of classical liquids. The self-consistent scheme features a complicated dynamic local field correction functional and its formulation is guided by ab initio path integral Monte Carlo simulations. Remarkably, our scheme is capable of providing unprecedently accurate results for the static structure factor with the exception of the Wigner crystallization vicinity, despite the absence of adjustable or empirical parameters. [ABSTRACT FROM AUTHOR]

Maritime transportation is crucial for global trade but faces significant risks and operational challenges. Ensuring safety is essential for protecting lives, the environment, and economic stability. This review explores the role of artificial intelligence (AI) in enhancing maritime safety and risk management. Key AI applications include risk analysis, crew resource management, hazardous material handling, predictive maintenance, and navigation systems. AI systems identify potential hazards, provide real-time decision support, monitor hazardous materials, predict equipment failures, and optimize shipping routes. Case studies, such as Wärtsilä's Fleet Operations Solution and ABB Ability™ Marine Pilot Vision, illustrate the benefits of AI in improving safety and efficiency. Despite these advancements, integrating AI poses challenges related to infrastructure compatibility, data quality, and regulatory issues. Addressing these is essential for successful AI implementation. This review highlights AI's potential to transform maritime safety, emphasizing the need for innovation, standardized practices, and robust regulatory frameworks to achieve safer and more efficient maritime operations. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposes a protocol for researchers, ergonomists, and industrial practitioners to design and carry out well-structured experiments that allow for reliable and valid comparisons between different exoskeleton designs or configurations, considering factors such as user characteristics, task demands, environmental conditions, and subjective user perceptions. This paper proposes a modular protocol for the designing of experimental studies to analyze exoskeletons used in industrial settings to support manual material handling (MMH). Despite exoskeleton technologies starting to be highly commercialized and present in workplaces, research still lacks a standardized procedure for analyzing the impact of these devices on workers. The protocol presented in this paper outlines a step-by-step procedure, including the parameters to be collected and analyzed in a research study. Moreover, the approach could be easily adapted to meet the specificity of a wide range of exoskeletons. The main novelty of the protocol is thus to support the experimental design and analysis of studies assessing the overall impact of exoskeletons on workers. To implement the protocol, the selected case study concerned a palletizing task involving the MMH of 12 cardboard boxes, weighing 10 kg. The results from physiological signals and pressure insoles show that the protocol is comprehensive and can be utilized by researchers evaluating different occupational exoskeletons for assistance during MMH (both active and passive), with modifications to specific parts based on the type of exoskeleton being assessed or the variables of interest. [ABSTRACT FROM AUTHOR]

A prerequisite for the recycling of mineral wool is information about the type of material, that is, whether it is glass wool or rock wool. As mineral wool produced before the year 2000 can be potentially carcinogenic, it is furthermore important to distinguish between “old” and “new” wool when handling the material. Based on VDI 3492, it is possible to determine the material and, in the case of rock wool, the age by analyzing the mass fractions of eight oxides, which are the main components of mineral wool. This study presents the X‐ray fluorescence (XRF) analyses of 141 man‐made mineral fibers collected in Germany. Only in a few cases it was not possible to clearly assign the material type. In contrast, the identification of “old” and “new” rock wool posed a challenge as there were many borderline samples. Based on the available data, a chemometric model was developed that can classify “old” and “new” RW with a sensitivity of 93% and 89% and with a specificity of 100% in both cases. However, care must be taken when oxide contents are close to the specification limits. The reason for this mainly lies in the overlapping intervals of key oxides as suggested by VDI 3492, and, to a lesser extent, in the uncertainties typically occurring in the XRF‐based analysis of oxides. With this study, a comprehensive collection and evaluation of XRF data on mineral wool is made available, which can serve as a reference database for future users. [ABSTRACT FROM AUTHOR]

Objective: During the Coronavirus disease-2019 (COVID-19) pandemic, many screening and elective procedures were deferred, leading to a notable reduction in the volume of materials handled by the cytopathology laboratory. This study seeks to explore both the immediate and prolonged impacts of the pandemic on non-gynecologic cytology practices in a hospital, focusing on the timeframe beginning in March 2020, when the first case was identified in our country. Methods: Starting from March 2020, when our country reported its first COVID-19 case, we compared the percentages of cytological samples processed at the cytopathology laboratory of University of Health Sciences Turkey, Prof. Dr. Cemil Taşcıoğlu City Hospital, for the three-month period of March to May in 2020 with those from the same months in 2019, 2021, and 2022. We also assessed the differences in malignancy rates. Results: In the three-month study period of 2020, there was an 81.5% reduction in the total number of non-gynecologic cytological specimens compared to 2019. Conversely, the overall malignancy rate saw a significant increase (6.1% in 2019 and 10.8% in 2020). During the 3-month study period in 2021, cytologic specimens increased compared with 2020 (127.8%) but continued to decrease compared with 2019 (-57.8%). In 2021, the overall malignancy rate was higher than that in other years (12.5%). Similarly, in the 3-month period in 2022, cytologic samples increased compared with 2020 (221.6%), but despite this increase, the number of cases was still lower than in the pre-pandemic period (-40.5%). The overall malignancy rate continued to be higher than before the pandemic (2019: 6.1%, 2022: 10.1%). Conclusion: The delay of elective procedures due to the COVID-19 pandemic has had a major impact on cytopathology practices. In both 2021 and 2022, the volume of non-gynecologic cytologic materials remained significantly lower than in 2019, highlighting the ongoing effects of the pandemic on cytopathology. Meanwhile, the rise in the overall malignancy rate underscores the need to prioritize diagnostic procedures for patients at high risk for cancer. [ABSTRACT FROM AUTHOR]