Machine Performance Research Articles

Kinematic analysis of the movement of the active knife cutter of chicory roots

Chicory roots are a valuable technical and strategically important crop for the leading sectors of the Ukrainian economy. The processing of raw materials from chicory roots allows to obtain energy (biofuel), food (coffee) and pharmaceutical (inulin) products. The low level of mechanization of harvesting root crops and, especially, harvesting both chicory and chicory root crops (significant losses, damage) does not allow to provide the needs of raw materials for its processing, or the necessary provision of the food industry of the Ukrainian economy and the fodder base of animal husbandry due to an increase in the amount of use root crops of chicory. One of the reserves for improving the performance of machines for harvesting chicory root crops is the improvement of the technological process of harvesting ginseng through the use of improved main working organs – a rotary ginseng cutter and a cutter of ginseng residues from the heads of root crops. The purpose of the work is to increase the indicators of the technological process of harvesting chicory root crops by developing and substantiating the parameters of the cutter's working organs. On the basis of the conducted theoretical analysis of the process of movement of the active cutter knife along the head of the root crop, analytical dependencies were developed that functionally describe the process of movement of the active cutter knife along the root crop head, which made it possible to substantiate the main structural and kinematic parameters of the active cutter knife. It has been established that the working length of the active knife of the cutter of the remains of burdock from the heads of root crops is in the range from 0.25 to 0.3 m, provided that the maximum permissible deviation of the vertical axis of the root crop from the axis of the row at the speed of movement of the burdock harvesting module is from 1.6 to 2.2 m /s and the speed of movement of the cutting edge of the blade of the active knife in the range from 0.3 to 0.8 m/s.

Design and Analysis of a New Dual-Stator Hybrid Magnet Flux Modulation Machine

This paper proposes a new dual-stator hybrid-magnet flux modulation machine (DS-FMHMM) for direct-drive applications, which employs NdFeB magnet excitation and Ferrite magnet excitation on the rotor and outer stator sides, respectively. With this design, the proposed DS-FMHMM can not only fully use the bidirectional flux modulation effect, but also effectively alleviate the magnetic saturation issue. The machine configuration is described, together with the operating principle. Then, the design parameters of DS-FMHMM are globally optimized for obtaining high torque quality, and the influence of magnet dimensions on torque is analyzed. To evaluate the merits of the proposed DS-FMHMM, the electromagnetic performances of machines under different magnet excitation sources are analyzed, and a comprehensive electromagnetic performance comparison of DS-FMHMM and two existing dual-stator flux modulation machines (DSFMMs) is developed.

Justification of technological indicators of machines for the production of bulb onion in an annual crop

Onion is one of the main vegetable crops. Its consumption in Russia reaches 2.0 million tons. The gross harvest amounted to 1601.5 thousand tons in 2022 with a yield of 31.3 t/ha. The purpose of the research is to substantiate the technological performance of machines for the mechanized cultivation of onions in an annual crop, providing a yield of 70 - 80 t/ha, on alluvial meadow soils of the Non-Chernozem Zone of Russia. The research method is field experience. Issues considered: application of fertilizers, spring tillage, weed control in the previous field and during the growing season, pre-sowing treatment and sowing of seeds in the field, pest and disease control through foliar spraying, drip irrigation, harvesting work

Performance Test, Noise, and Economic Analysis of Coffee Roasting Machines Rotating Cylinder

The roasting process carried out in this study was at the medium roast level, using a rotating cylindrical coffee roasting machine that used an electric heat source. This research aims to determine the performance and economic analysis of a rotating cylinder coffee roasting machine. Descriptive analysis in this study includes coffee roasting machine performance data (roasting temperature, moisture content, electrical energy requirements and noise) and economic performance data (NPV, IRR and BCR). The results of observing the performance of the machine obtained a roasting temperature of 205°C and a moisture content of 4.42%, in accordance with the Indonesian national standard (SNI) and the need for electrical energy in the heater was 3.18 kWh and in the motor of electric was 1.17 kWh. In this study, the noise analysis obtained showed the number 90 dB, which means it is less effective for operators in that environment. Meanwhile, the results of the economic analysis were obtained NPV, IRR and BCR respectively are IDR 225,363,266; 21.6 %; 5.18.

Beam dynamics optimization for high gradient beam driven plasma wakefield acceleration at SPARC-LAB

The SPARC_LAB test facility at the LNF (Laboratori Nazionali di Frascati, Rome) holds a high brightness photo-injector used to investigate advanced beam manipulation techniques. High brightness electron bunch trains (so-called comb beams) can be generated striking on the photo-cathode of a Radio Frequency (RF) photo-injector with a ultra-short UV laser pulse train in tandem with the velocity bunching technique. Beam dynamics studies have been performed with the aim of optimizing the dynamics of the double beam (driver and witness) used to perform particle driven plasma wake field acceleration (PWFA). In this scenario different scans on beam parameters were carried on adopting the ASTRA simulation code, in order to optimize the witness beam quality and improve the plasma booster stage performances. A benchmark of the simulations has been then performed, reproducing the experimental data obtained from the optimization of machine performances, and a good agreement was found.

Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

Manufacturability analysis and optimisation of a reconfigurable machine to enhance optimal machine performance

Reconfigurable machines (RM’s) are machines that have been designed with a system architecture to quickly respond to the constantly changing needs of various industries, as well as to manage product variations within a certain part family. However, the reconfigurable systems structure and related modules bring new challenges for design, manufacturing and maintenance which ultimately affects the overall performance and productivity of these machines. To address this, the intelligent use of sensors to enable real-time data monitoring and analysis was explored. To further assist with the optimal management and decision-making of the best possible manufacturing process, a comprehensive manufacturing study of the machine was carried out. This leads to increased production capabilities, improved product quality, reduced maintenance requirements, and lower costs. This study describes the design optimisation and manufacturability analysis of a reconfigurable machine using intelligent sensing techniques based on a case study of a reconfigurable vibrating screen (RVS) machine. Using CompactRIO (NI cRIO-9074) with a total of 6 channels, analysis of the different sub-systems of the RVS machine was performed. The results of the study showed that the design and the manufactured prototype is able to withstand failure on the different subsystem under different loading conditions. This research contributes to the development of reconfigurable machines and also prediction of the structural integrity of such machines using smart sensoring techniques in order to prevent unforeseen failures and enhance optimal machine performance.

A Study on the effect of C3H8O3 and C8O7 electrolytes for electro chemical machine performance of titanium alloys

Electrochemical Machining is a non-traditional machining process that uses electro- chemical reactions to remove materials from the workpiece. In this work , micro hole are produced on the titanium alloys with combination of C3H8O3 and C8O7 electrolytes and the machining parameters such as voltage , Duty Cycle , Feed rate and Electrolyte Concentration with different levels for measuring Material removal rate and overcut.Taguchi-designed L16 orthogonal array was used to conduct the experiments. The results revelated that highest MRR is achieved at a voltage of 14V, electrolyte concentration of 65g/L, feed rate of 0.3mm/min and a duty cycle of 65- 75%. the Higher voltage provides more energy for the electrochemical process, which enhances the electrolytic dissolution of the workpiece material. This increased energy results in a more vigorous dissolution process and a faster material removal rate, leading to a higher MRR. additionally, the observations show that the highest electrolyte concentration of 65g/L resulted in less overcut. This is because higher electrolyte concentration improves conductivity, ensures uniform current distribution, and provides better control over the electrochemical reactions.

Development and Implementation of a Damage Model for Potato Tuber Blackspot in Discrete Element Method to Analyze Harvesting and Handling Processes

Highlights Method for determining the discoloration of potato tissue samples induced by mechanical stress. Model of the discoloration susceptibility of specific potato tissue. Particle segmentation algorithm in the Discrete Element Method for contact localization in post-processing. Development of the "Discrete Element Method Blackspot Potato Tuber Model" capable of predicting internal blackspot damage in potato tubers. Abstract. Blackspot damage caused by mechanical load during the harvesting and processing stages of potato tubers remains difficult to mitigate. Field tests are inadequate as it takes around two days to develop blackspot discoloration, making it unclear when and where the initial damage occurs. Particle simulation, particularly with the Discrete Element Method (DEM), offers opportunities to improve machine performance and reduce crop losses. However, the DEM cannot predict local blackspot damage, making it unsuitable for reducing potato tuber damage. To address this, the “DEM blackspot potato tuber model” presented in this contribution integrates a discoloration function and a segmentation algorithm of DEM particles to predict and analyze blackspot damage during harvesting and processing. Based on mechanical experiments on tuber tissues with different loading conditions, a discoloration function was proposed dependent on strain and strain rate. The segmentation algorithm adapts to the varying potato tuber particle size by varying the number of segments to generate segments of average blackspot size. Two different validation tests are used to identify the single and multiple impact capabilities of the model. The preliminary results show that the discoloration induced by single impact events is well predicted in terms of the number of damaged tubers as well as the average damage per tuber. Damage of multiple impacts is less accurately predicted since the model does not take into account the accumulation of damage. Keywords: Blackspot, Damage model, Discrete Element Method, Potato handling, Simulation.

On the Human–Machine Gap in Car Racing: A Comparative Analysis of Machine Performance Against Human Drivers

On the Human–Machine Gap in Car Racing: A Comparative Analysis of Machine Performance Against Human Drivers

Engineering workshop education and supervision: AR for machine operation guidance and safety instructions

This research explores the implementation of Augmented Reality (AR) in the mechanical workshop of an engineering education program. The objective is to provide engineering students with an immersive and interactive learning experience, improving their understanding of machine operation while emphasizing safety protocols. This research introduces an AR approach designed to overcome challenges when comprehending the intricate workings of machines and adhering to safety guidelines. By overlaying digital information onto the physical workspace, AR assists students in visualizing machine components, operational procedures, and safety measures, promoting a more effective learning process. In the AR experience, we incorporate sensor data from the workshop environment. This integration enables real-time monitoring of machine performance, environmental conditions, and student activities. Furthermore, the study investigates the potential of AR for workshop supervision. Workshop operators can monitor students’ activities in real-time, ensuring compliance with safety protocols and providing personalised assistance when needed.

Features of static distributions of the mass of parts of rose hips

The article presents the need to use a systematic approach to assessing machine performance which is possible only on the basis of the widespread use of mathematical methods and electronic computing. Machines and experimental results on the distribution of masses of rose hips of the Rosa Conina variety and their parts (shell, seeds), as well as theoretical models in the form of analytical expressions that adequately describe the experimental data are described in the article.

Design and Control of a Permanent Magnet Assisted Synchronous Reluctance Motor

In recent years, studies aiming to use different motor types for traction purpose, such as in electric vehicles, have become increasingly widespread. Among these motor types, permanent magnet assisted synchronous reluctance motor (PMa-SynRM) has become in-creasingly preferred in commercially electric vehicles nowadays. This study addresses the design and control of a PMa-SynRM, also the comparison with the synchronous reluc-tance motor (SynRM). The motor design process is carried out using the finite element method in Ansys-Maxwell environment. A series of a simulation studies is conducted in the MATLAB/Simulink environment for controlling the obtained motor designed in An-sys-Maxwell. The field-oriented control (FOC) approach is chosen for precise speed con-trol. As a result of the simulation studies, it is observed that the designed motor tracks the reference with minimal error under various load conditions within a closed-loop system. Also, this paper investigates how the PM implementation affects the machine perfor-mance comparing to SynRMs. In addition, such a study takes into account that the de-sign of machines involves always several constraints, including geometry, materials, sup-ply limits, and performance constraints.

Robustness of the Fuzzy Adaptive Speed Control of a Multi-Phase Asynchronous Machine

Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Local-scale flash flood susceptibility assessment in northeastern Bangladesh using machine learning algorithms

The recurring flash floods in northeastern Bangladesh have been causing significant damage to the lives and livelihoods of local people every year, underscoring the necessity of effective flood management and mitigation efforts. Identifying flood hazard areas is the very first step in achieving such ends. While machine learning algorithms have been widely used in flood susceptibility studies, there is a significant dearth of research addressing their application for local-scale assessment of flood susceptibility in Bangladesh. Besides, in most of the flood susceptibility studies, only statistical metrics are used to evaluate the prediction capability of machine learning algorithms, overlooking their ability to account for spatial consistency. Therefore, this study attempts to evaluate the performance of Random Forest (RF) and Support Vector Machine (SVM) algorithms in flash flood susceptibility assessment at local scale using statistical and spatial metrics. RF model performed better than SVM with area under the curve (0.964), accuracy (92.1 %) and kappa (0.894). Five susceptibility zones were identified using a natural breaks method: very high, high, moderate, low and very low. The overall spatial agreement between the susceptibility maps of RF and SVM was 73.3 %. For very low susceptible classes, the spatial agreement was highest for RF-SVM (97.15 %) and SVM-RF (81.54 %). The findings of this study can be useful for a more accurate assessment of flash flood susceptibility in similar local settings. Moreover, the prepared susceptibility map can be helpful for taking sustainable measures to mitigate the devastating effects of flood hazard in northeastern Bangladesh.

Investigation of machinability characteristics of Inconel 713C using new novel honeycomb and broken-parallel texture cutting inserts with graphene-based solid lubricants

The present investigation aims to investigate the machinability performances of graphene solid lubricant (S) deposited on dimple texture (T1-S), novel honeycomb texture (T2-S), and novel broken-parallel textures (T3-S) during dry turning of Inconel 713C has been carried out and compared with dry (D) textured tools (T1-D, T2-D, and T2-D). L24 orthogonal design was used to design the experiments by considering conditions (dry and solid lubricant), textured type, cutting speed, and feed rate. The experimental results reveal that the honeycomb without and with graphene (T2-D and T2-S) effectively reduced the generated cutting temperature by 14.5 % and 22.4 %, cutting force by 34.6 % and 39.4 %, surface roughness by 14.3 % and 22.4 % and tool flank wear by 11.9 % and 2.3 % compared dimple and broken parallel textured inserts. The honeycomb tool (T2-D and T2-S) exhibited shear angle increased by 7.45 % and 6.5 % and 29.3 %, and 33.33 % than dimple under dry and graphene textured cutting tool. The chip reduction coefficient was <1.5, resulting in an increased shear angle and decreased friction coefficient in graphene-deposited honeycomb texture conditions. The major mechanism credited to the improved performance of honeycomb with graphene tool was reduced chip curl diameter and chip width by 3.3 % and 5.7 % compared to other tools. SEM images showed that all textured inserts' primary tool wear mechanisms on the tool surface were built-up edges, micro-chipping, adhesions, and abrasions. EDS analysis and following elemental plotting showed the strong presence of workpiece constituents on the flank surface. But, the influence of adhesion and abrasion was more noticeable for all dry-textured tools. The findings of this study indicate that honeycomb textured tools are a superior alternative to dry machining of Inconel 713C. Additionally, broken-parallel textured tools were more effective than textured dimple tools.

ANALISA PERFORMANCE THRESER DI PABRIK KELAPA SAWIT (PKS) PTPN V SEI GARO DENGAN METODE OVERALL EQUIPMENT EFFECTIVINESS (OEE) DAN 5S

This study aims to analyze things that support the performance of thresher in palm oil mills, determine thresher performance with Overall Equipment Effectiveness (OEE) and 5S methods in palm oil mills and analyze and provide solutions to improve thresher performance with a Total Productive Maintenance approach using the Overall Equipment Effectiveness (OEE) method and 5S on thresher in palm oil mills.. This research was conducted with descriptive and qualitative methods in improving the production performance of threser machines to determine the problems of threser machines that cause a decrease in machine productivity by analysis and discussion. Based on the results of the analysis and description of OEE measurement results in the PTPN V Sei Garo Threser machine, Measurement of the level of machine effectiveness using the Overall Equipment Effectiveness (OEE) method at PTPN V Sei Garo obtained the largest percentage of OEE on the Thresher machine at 91.66% and the lowest at 878.79%. The factors that have the largest percentage of six big losses on thresher machines are Idling and Minor Stoppage Losses of 1% and Equipment Faillure Losses of 0.37%.

Analisis Ergonomika Bagian Penghancur pada Mesin Pencacah Pakan Ternak Multiguna

The agricultural machinery use can increase time and labor efficiency compared to traditional agricultural systems. One of the agricultural machines that is widely used in the livestock sector is the multi-purpose animal feed chopper machine. This machine has two parts with different functions. The chopper section is used to chop long-shaped animal feed, the crusher section is used to crush short-shaped animal feed, for example corn cobs. Machines can work optimally if the design considers ergonomic principles so that they can be operated safely and comfortably. Operating the machine safely and comfortably for the operator can increase the productivity of machine performance. This research goal was to analyze the ergonomics of multi-purpose animal feed chopping machines in the crushing section. The research used quantitative methods supported by literature studies. The research parameters consisted of Standing Finger Tip Height (TJUB), Standing Vertical Reach (JVB), Standing Horizontal Reach (JHB), recommended load limit data (RWL), work fatigue level, equipment noise, environmental temperature, and body posture measurements using REBA method. The research results stated that the crushing input on the multipurpose animal feed chopper machine was classified as ergonomic with an input height of 140 cm, between P95 TUJB (68.8 cm) and P5 JVB (183.5 cm). Machine operation did not cause fatigue with a CVL value ≤ 30%, RWL value 5.55 kg, Noise level 98.91 dBA. The environmental temperature suitable for operating the machine in the morning was (29.1oC) and in the afternoon was (28.6 oC). The operator's body posture measurement using REBA was at a moderate level (score 5). It is recommended modifying the machine design to improve the safety and comfortness of the operator when operating the crushing part. Keywords: Anthropometry, CVL, Physical Environment, REBA, RWL

Fear of falling in community-dwelling older adults: What their gait acceleration pattern reveals

BackgroundFear of Falling (FOF) is common among community-dwelling older adults and is associated with increased fall-risk, reduced activity, and gait modifications. ObjectiveIn this cross-sectional study, we examined the relationships between FOF and gait quality. MethodsOlder adults (N=232; age 77±6; 65 % females) reported FOF by a single yes/no question. Gait quality was quantified as (1) harmonic ratio (smoothness) and other time-frequency spatiotemporal variables from triaxial accelerometry (Vertical-V, Mediolateral-ML, Anterior-Posterior -AP) during six-minute walk; (2) gait speed, step-time CoV (variability), and walk-ratio (step-length/cadence) on a 4-m instrumented walkway. Mann Whitney U-tests and Random forest classifier compared gait between those with and without FOF. Selected gait variables were used to build Support Vector Machine (SVM) classifier and performance was evaluated using AUC-ROC. ResultsIndividuals with FOF had slower gait speed (103.66 ± 17.09 vs. 110.07 ± 14.83 cm/s), greater step time CoV (4.17 ± 1.66 vs. 3.72 ± 1.24 %), smaller walk-ratio (0.53 ± 0.08 vs. 0.56 ± 0.07 cm/steps/minute), smaller standard deviation V (0.15 ± 0.06 vs. 0.18 ± 0.09 m/s2), and smaller harmonic-ratio V (2.14 ± 0.73 vs. 2.38 ± 0.58), all p<.01. Linear SVM yielded an AUC-ROC of 67 % on test dataset, coefficient values being gait speed (-0.19), standard deviation V (-0.23), walk-ratio (-0.36), and smoothness V (-0.38) describing associations with presence of FOF. ConclusionOlder adults with FOF have reduced gait speed, acceleration adaptability, walk-ratio, and smoothness. Disrupted gait patterns during fear of falling could provide insights into psychosocial distress in older adults. Longitudinal studies are warranted.

Consistency Analysis of Rendement and Quality of CPO (Crude Palm Oil) Palm Oil Processing at PT. Agricinal North Bengkulu

The yield and quality of CPO is influenced by the condition of unripe and overripe FFB (fresh fruit bunches), which can cause an increase in ALB, water content and dirt content. The quality of CPO is also influenced by FFB from the community. Analysis of the consistency of the yield and quality of CPO was carried out due to the age of the plants that were too old and the performance of the factory machines decreased due to the age of the machines. Analysis of yield consistency and quality was carried out using statistical quality control methods, namely quality control using a statistical approach using control charts and causal diagrams. This study uses secondary data on the yield and quality of CPO for the past year (July 2021-June 2022). The research results show, there are data that are outside the upper control limit, yield in July 2021, free fatty acid content in May 2022 and dirt content in October 2021. While the water content is statistically controlled (in statistical control). The yield and quality of ALB are influenced by type of raw material, production capacity and oil losses. Moisture content and dirt content are affected by treatment of production process and machine conditions.