Cost Tool Research Articles

Investigating access and use of digital tools for agriculture among rural farmers: A case study of Nkomazi Municipality, South Africa

Abstract The study examined the access and utilization of digital tools for agriculture among rural farmers in Nkomazi, Mpumalanga, South Africa. Data were collected from 120 rural farmers who were purposively sampled in Nkomazi Municipality. Information was gathered from the respondents through enumerator-administered structured questionnaires. The data were analyzed descriptively using percentages, means, and ranks, and multiple linear regression was employed to analyze the influence of the farmers’ socio-economic characteristics on their utilization of digital tools. The findings reveal that the farmers had an average age of 45.81 years. Approximately half (50.9%) of the farmers had no formal education or only completed primary education, and the average years of farming experience was 8.62 years. Overall, the farmers had access to traditional digital tools and apps such as radio, television, and smartphones. However, their utilization of these tools and apps, especially modern digital tools such as WhatsApp (43.3%) and Facebook (37.5%) for agricultural purposes, was still relatively low. This can be attributed to various challenges highlighted by the farmers, including insufficient skills and training, high costs of tools and apps, and issues related to network coverage. The educational level and cosmopoliteness of the farmers were identified as key socio-economic factors influencing the utilization of digital tools among the respondents. It is recommended that the farmers receive education and training on the use of modern digital tools and apps to enhance their ability to leverage them effectively and efficiently for the benefit of their agricultural enterprise.

The Correlation Between Electrodiagnostic Severity and Patient-Reported Disability Among Carpal Tunnel Syndrome Patients.

The use, easy applicability, and costs of accurate diagnostic tools and their utility for early diagnosis, efficient treatment, and follow-up are important. In this study, we aimed to evaluate how electrophysiologic data were reflected in the clinical data of the patients with carpal tunnel syndrome (CTS). This study included 102 patients with definitive CTS based on electroneuromyography. The Boston Carpal Tunnel Syndrome Questionnaire (BCTQ), the 36-item Short Form (SF-36) questionnaire of the general quality of life, the Visual Analog Scale (VAS), and the painDETECT (PD-Q) neuropathic pain questionnaire were administered by a clinical practitioner. We found a moderate correlation between electrophysiologic measurements and VAS and a weak correlation between PD-Q scores. When we tested the mean scores of the SF-36 quality of life scale subscales for differences across the CTS groups, we found significant differences in the mean scores of the physical functioning, bodily pain, and social functioning subdomains by disease severity (P < 0.05 for each). While the BCTQ Symptom Severity Scale (BCTQ-SSS) was predictive of the early stages of CTS, we found that both BCTQ-SSS and BCTQ-Functional Status Scale scores increased in correlation with advanced stage CTS. In addition to the electrophysiological data, self-report measures may help to pursue a multidirectional approach in patient management by acting as a reference for the diagnosis, treatment, and monitoring of CTS. The correlation between objective data and time-saving, practical, subjective measurements can serve as markers to facilitate a diagnosis.

Enhancing Machining Efficiency: Real-Time Monitoring of Tool Wear with Acoustic Emission and STFT Techniques

Tool wear in machining is inevitable, and determining the precise moment to change the tool is challenging, as the tool transitions from the steady wear phase to the rapid wear phase, where wear accelerates significantly. If the tool is not replaced correctly, it can result in poor machining performance. On the other hand, changing the tool too early can lead to unnecessary downtime and increased tooling costs. This makes it critical to closely monitor tool wear and utilize predictive maintenance strategies, such as tool condition monitoring systems, to optimize tool life and maintain machining efficiency. Acoustic emission (AE) is a widely used technique for indirect monitoring. This study investigated the use of Short-Time Fourier Transform (STFT) for real-time monitoring of tool wear in machining AISI 4340 steel using carbide tools. The research aimed to identify specific wear mechanisms, such as abrasive and adhesive ones, through AE signals, providing deeper insights into the temporal evolution of these phenomena. Machining tests were conducted at various cutting speeds, feed rates, and depths of cut, utilizing uncoated and AlCrN-coated carbide tools. AE signals were acquired and analyzed using STFT to isolate wear-related signals from those associated with material deformation. The results showed that STFT effectively identified key frequencies related to wear, such as abrasive between 200 and 1000 kHz and crack propagation between 350 and 550 kHz, enabling a precise characterization of wear mechanisms. Comparative analysis of uncoated and coated tools revealed that AlCrN coatings reduced tool wear extending tool life, demonstrating superior performance in severe cutting conditions. The findings highlight the potential of STFT as a robust tool for monitoring tool wear in machining operations, offering valuable information to optimize tool maintenance and enhance machining efficiency.

Perceptions of Yemeni EFL Students on the Use of AI Tools: Awareness, Frequency, and Preferred Applications

This study explores Yemeni EFL students' perceptions of using AI tools in their English language learning, focusing on awareness, frequency of use, and preferred applications. AI-powered tools like ChatGPT, Duolingo, and Grammarly offer personalized, interactive learning experiences that are especially valuable in regions with limited educational resources. The research utilized an online survey distributed via WhatsApp to gather data from Yemeni undergraduate students. Results indicate that while many students are familiar with AI tools and use them regularly for tasks such as vocabulary building and grammar checking, barriers like limited internet access and high AI tool costs remain significant. The study highlights the potential benefits of AI tools in accelerating learning, enhancing autonomy, and providing personalized feedback while addressing the need for improved infrastructure and support in under-resourced areas. The findings provide valuable insights for educators, policymakers, and AI developers to enhance the effectiveness and accessibility of AI tools in language learning, particularly in conflict-affected regions like Yemen.

Highly sensitive and specific electrochemical biosensor for direct detection of hepatitis C virus RNA in clinical samples using DNA strand displacement

Hepatitis C virus (HCV) is a common blood-borne infection that can lead to long-term illnesses such as hepatocellular cancer and liver cirrhosis. Early diagnosis is crucial for effective management, as no vaccine is available for preventing HCV infection. However, the high cost and complexity of current molecular diagnostic tools hinder efforts to achieve early diagnosis and prevent transmission, particularly in resource-limited settings. We developed a novel electrochemical biosensor for point-of-care testing (POCT) of HCV RNA. The sensor utilizes a strand displacement method, where the target RNA displaces a gold nanoparticle-labeled reporter probe (AuRP) from a pre-hybridized duplex with a magnetic nanoparticle (MNP)-labeled capture probe. The amount of displaced AuRP, detected using differential pulse anodic stripping voltammetry (DPASV), is directly proportional to the target RNA concentration. The biosensor exhibited excellent analytical performance, with a detection limit of 4 fM for synthetic targets and 43 ng/µL for RT-PCR products. Importantly, it successfully detected HCV RNA directly in clinical plasma samples without the need for RNA extraction or amplification. The sensor was used to analyze 30 RNA samples from HCV-positive patients, 20 cDNA samples from viral RNA, 30 HCV-positive plasma samples, and 22 HCV-negative plasma samples. The sensor results show good concordance with the RT-PCR results, demonstrating the sensor’s potential for detecting HCV in clinical samples.

Empirical Analysis of Widely Used Website Automated Testing Tools

In today's software development, achieving product quality while minimising cost and time is critical. Automated testing is crucial to attaining these goals by lowering inspection efforts and discovering faults more effectively. This paper compares widely used automated testing tools, such as Selenium, Appium, Java Unit (JUnit), Test Next Generation (TestNG), Jenkins, Cucumber, LoadRunner, Katalon Studio, Simple Object Access Protocol User Interface (SoapUI), and TestComplete, based on functionality, ease of use, platform compatibility, and integration capabilities. Our findings show that no single tool is inherently superior, with each excelling in certain areas such as online, mobile, Application Programming Interface (API), or performance testing. While Selenium and Appium are the dominant online and mobile testing frameworks, TestComplete and Katalon Studio offer complete, user-friendly cross-platform testing solutions. Despite the benefits of automation, obstacles such as tool maintenance, scalability, and cost issues remain. The report finishes with advice for picking the best tool for the project and offers potential approaches for enhancing testing frameworks, such as AI-driven optimisation, cloud-based testing, and greater Continuous Integration/ Continuous Deployment (CI/CD) integration. This study offers useful information for developers and testers looking to optimise their testing methods and increase software quality.

ECONOMIC EFFICIENCY OF APPLICATION OF OPTIMIZED MILL BED

This paper presents the selection of optimization parameters for the bed geometry of a long metal cutting machine (MCM), the design problem and boundary conditions were given. Five different geometries were designed for further mathematical analysis to meet the requirements of the problem. Static analysis of the mathematical model of the bed shells was performed by finite element method (FEM) using BETA CAE System tool, ABAQUS, which showed that by using stiffeners in the form of two variable pitch spirals and three hollow tubes, as well as changing the design at the connection point of the beam support to the bollards of the long bed of the metal cutting machine, the stresses that occurred in these places at an angle of 90° were reduced. The geometries were chosen in such a way that it was possible to reduce the stresses occurring at the point of cutting, to reduce the deflection, to increase the rigidity of the structure. The economic calculation aimed at determining the cost of a long metal-cutting machine tool with the proposed geometry has been carried out. The analysis of the unit cost of the product (long bed of the metal-cutting machine tool made of polymer concrete with optimized geometry) has been carried out, the calculation of the annual economic effect from the use of the proposed method of manufacturing has been carried out. Keywords: MCM, FEM, statistical analysis, product cost, economic calculation.

Electronic monitoring versus manual paper-based monitoring for hand hygiene compliance: a comprehensive health economic assessment analysis

BackgroundMonitoring hand hygiene compliance (HHC) of healthcare providers (HCPs) in healthcare facilities is critical for hand hygiene (HH) promotion. However, less is known about the cost and effectiveness of different HHC monitoring tools. In this study, we aimed to compare various health economic indicators corresponding to electronic system-based monitoring (ESM) and manual paper-based monitoring (MPM) for HHC to provide evidence-based advice for HHC monitoring measures targeted selecting.MethodsA before and after study in 40 clinical departments with 4,524 healthcare providers was conducted from December 2022 to January 2023 (MPM implementation phase) and March 2023 to May 2023 (ESM implementation phase). The cost-effectiveness, cost-efficiency, the extent of the Hawthorne effect, and indirect cost-benefit of the two monitoring methods were compared.ResultsThe total cost spent on ESM for the 40 departments (17,702.92 CNY) was 4,123.76 CNY lower than that of MPM (21,826.68 CNY). The HHC of MPM (80.16%) was higher than that of ESM (69.82%) (p < 0.01). In high- and medium-risk departments, the cost-effectiveness ratio of ESM (7,977.90 CNY and 13,794.60 CNY, respectively) was lower than that of MPM (9,039.61 CNY and 14,549.05 CNY, respectively). In low-risk departments, the cost-effectiveness ratio of ESM (3,910.77 CNY) was higher than that of MPM (3,899.06 CNY). Compared with ESM, the incremental cost of MPM in all departments was 4,123.76 CNY, the incremental effectiveness was 10.34%, and the incremental cost-effectiveness ratio was 39,881.62 CNY. Between the two monitoring methods, the efficiency of ESM (48.11%) in all departments was higher than that of MPM (14.20%) (p < 0.01). The cost-efficiency ratio of MPM in all departments (155,775.56 CNY) was higher than that of ESM (36,796.76 CNY). The extent of Hawthorne effect of MPM of HHC in all departments (43.99%) was higher than that of ESM (35.69%) (p < 0.01). When ESM was used as the HHC monitoring approach, the HAI rates (1.39%) in all departments were higher than that when MPM was used (1.34%) (p = 0.562). When the payment willingness was less than 40,000 CNY, the ESM method was the better option for cost-effectiveness; When the input exceeded this threshold, the MPM method was the better option for cost-effectiveness.ConclusionsESM exhibited notable advantages over MPM in terms of cost-effectiveness, cost-efficiency, cost-benefit, and the Hawthorne effect.

The cost-of-illness of multiple sclerosis in Jordan

ABSTRACT Background Multiple Sclerosis (MS) imposes a significant financial burden on health-care systems. This study aims to determine the cost-of-illness (COI) for MS in Jordan, a country where data on the economic impact of MS are scarce. Methods Data were collected for one year, annual COI was estimated using a cross-sectional snowball sampling design. Eligible patients completed a self-reported questionnaire to provide sociodemographic, physician visit, and diagnostic and laboratory test data. Indirect costs were estimated using an adjusted Human Capital Approach. Results This study included 383 patients, (73% females, 61% between 26-45). Eighty % took disease-modifying therapies (DMTs), and 40% had relapses in that year. One-third use non-DMTs and equipment for assistance. The average annual cost per patient was $11,719 (direct costs=$11,252, indirect costs=$467). The total annual cost for all participants was $748,299. The estimated cost of non-DMT, medical tools, diagnostic tests, and hospitalization per patient was $53, 51, 99, and 235 respectively. Conclusion High costs of DMTs state the necessity of resource optimization in Jordan public healthcare facilities. Such findings yield policy-informing actionable insights, suggesting strategic investments in more cost-effective DMTs with potential improvement in accessibility and reduction in the overall economic burden faced by both patients and governments.

Validation of a novel medical device (Chloe SED®) for the administration of analgesia during manual vacuum aspiration: a randomized controlled non-inferiority pilot study.

Millions of women worldwide annually undergo manual vacuum aspiration (MVA) with no pain medication, which is a violation of their basic human dignity. We designed a novel device (Chloe SED®) to administer paracervical block (PCB) during MVA in countries where pain medication is not typically given due to the high cost of the necessary tools. We conducted a single-blinded, randomized controlled non-inferiority trial including 61 patients at two hospitals in Kisumu, Kenya, to validate Chloe SED® for administration of PCB during MVA. PCB administered with Chloe SED® was compared to PCB administered with a standard spinal needle. Patients requiring MVA were block randomized in blocks of six, each provider completing six PCBs-three with the Chloe SED® and three with the standard spinal needle. The trial was registered with the Kenya Pharmacy and Poisons Board, ECCT/19/03/01 (https://ctr.pharmacyboardkenya.org/applications/index/protocol_no:RUNDVC8xOS8wMy8wMQ__/filter:/investigator:/sites:/pages:5/start_date:/end_date:/disease_condition:/users:/ercs:/stages). An intention-to-treat analysis was completed. The primary outcome was the non-inferiority of the pain score during uterine evacuation with a non-inferiority margin of 2 points on an 11-point numerical rating scale. Secondary outcomes included the non-inferiority of the pain score at four other time points and patient satisfaction. Chloe SED® showed non-inferiority of the primary outcome with a mean pain score during evacuation of 3.8 [90% confidence interval (CI): 3.1-4.6] compared with the spinal needle at 4.1 (90% CI: 3.5-4.7). Non-inferiority of the pain score was shown at all time points. Most patients expressed a desire for the continued use of the device to administer PCB for MVA. No adverse events were noted. In summary, the Chloe SED® appears non-inferior to the spinal needle and desirable for the administration of PCB during MVA.

Digital game–based learning in music education: A systematic review between 2011 and 2023

Digital game–based learning is increasingly integrated into classrooms, offering a novel approach to combining informal and formal music education. This article reports the findings of a systematic review investigating digital game–based learning in music education, analysing 15 empirical, peer-reviewed articles written from 2011 to 2023. In this analysis, we first analyzed the platforms of digital game–based learning tools and their corresponding musical objectives. Second, we examined the methodologies, participant demographics, and the effectiveness of digital game–based learning in music education. Finally, we considered potential issues associated with the reviewed studies. Our findings reveal that while potential benefits of digital game–based learning in music education are evident, several challenges also arise. Many of the studies we reviewed failed to consider and discuss potential issues associated with digital game–based learning; with our prominent concerns pertaining to tool availability, cost, and accessibility. In addition, our systematic review highlights the need for further research focusing on open-access resources and free tools that help mitigate such accessibility barriers. Recommendations for future research include further work on experimental designs between traditional music learning and digital game–based learning and examining additional dependent variables beyond motivation and achievement.

Cutting performance and wear mechanism of submicron and ultrafine Ti(C, N)-based cermets

The complex thermal-mechanical coupling among Ti(C, N)-based cermet tool, workpiece and chip affects immensely the tool life, machining quality and costs during high-speed cutting, which makes the investigation on wear mechanisms of tools quite important. In this work, submicron and ultrafine Ti(C, N)-based cermet tools were prepared by vacuum sintering technology, and the cutting performance of the tools was evaluated by continuous dry cutting. The aim of this work is to unravel the wear mechanisms of submicron and ultrafine Ti(C, N)-based cermet tools based on the cutting performance and wear characteristics of both the cutting tools and chips generated during high-speed cutting. The Vickers hardness, flexural strength and tool lifespan of ultrafine Ti(C, N)-based cermets are significantly superior to those of submicron Ti(C, N)-based cermets because of grain refinement strengthening and the improved distribution of metal phases. Tool wear depends to a large extent upon the contact states and heat transfer ability at different locations of the tool edge, which are characterized by simultaneous action and mutual transition from abrasive, adhesion, surface fatigue and oxidative wear. Overall, ultrafine Ti(C, N)-based cermet tools with excellent comprehensive properties exhibit a distinctly reduced tool wear at different wear regions.

Influence of Remote Laser Cutting on Magnetic Loss and Mechanical Properties in 0.2 mm Silicon Steel

Energy loss due to eddy current generation is a significant factor in reduced efficiency of electrical machines, therefore motor cores with thinner sheets are required due to their effect in reducing eddy currents. However, reducing the thickness of laminations is challenging due to the high tooling costs in blanking due to the small tolerances required, whilst other methods such as conventional laser cutting are too slow to be commercially viable. In this paper the influence of remote laser cutting on thin electrical steel sheets (Cogent/Tata Steel NO20 3.2% Si) has been investigated on the tensile strain to fracture, fatigue life, edge hardness, and energy loss in an AC magnetisation cycle for two laser power levels. The laser power has found to have no statistically significant influence on the bulk mechanical properties of the material, but significantly affects the measured specific loss. The latter was associated with the increased edge hardness at higher laser powers. Based on the parameters selected it is highly questionable whether RLC offers a viable method for lamination cutting, significant refinement of the laser parameters and/or the use an alternative laser such as an ultra-fast pulsed laser is required to be competitive with existing methods. Additionally, it is shown that energy loss increases linearly with respect to length of the cut edge - to the minimum cut spacing tested of 6 mm. These results can be used to optimise laser parameters to reduce the degradation of magnetic properties by decreasing laser power where possible.

Charlotte: A modern tool for cave surveying

The future of cave surveying is a full 3D scan, as automatic as possible, capturing all morphologically relevant details. However, the vast majority of cavers are still using tools designed more than 15 years ago. The advancements in tools for architects, CAD designers, programmers of VR and robotics could be helpful also for the caving community. That’s why Charlotte, a cheap DIY 2.5D scanner designed for cave surveying, was developed and built. To demonstrate its capabilities, a new survey of Grotta Regina del Carso cave (cad. nr. 2328/4760VG), the biggest cave in the Gorizia Karst, has been realized and published. The new scanner is based on the same traditional cave surveying techniques, familiar to all cavers, and features a LiDAR to capture the exact cave morphology. The results are so realistic they can be used for 3D animations, physics simulations, or even 3D printing. The prototype of the new tool costs less than 400€ (EURO; as of December 2022). All the source code and schematics are released as Free and Open Source. Cavers are encouraged to fork the project on Github and provide new functionalities, to keep up with new technology available and the needs of caving scientific research all around the world.

Microstructure, mechanical, and cutting performance properties of B4C and SiC reinforced sandwich composite segments

This study aims to extend the work-life of diamond-cutting segments and to economize the operating cost of diamond-cutting tools. In order to achieve this object, bronze matrix sandwich segments reinforced with SiC and B4C were produced utilizing the hot pressing technique. In the term of the cutting segments, it is favorable that the outer layers are wear-resistant and the middle layer is tough. SEM and XRD analysis were used to determine the microstructural properties. Mechanical properties were evaluated by conducting hardness, wear, cutting performance, and three-point bending tests. The cutting performance of the segments was determined by turning andesite marble. SEM examinations showed that SiC and B4C grains were homogeneously distributed in the bronze matrix. The highest hardness value was 113.9 HB in the B4C reinforced sandwich segment. The reciprocating wear test findings indicated that the matrix exhibited the lowest wear rate in the B4C reinforced sandwich composite segment, followed by the hybrid sandwich composite segment. The lowest amount of cutting loss after turning andesite stone was achieved in the SiC, and B4C reinforced hybrid sandwich composite segment. The cutting performance of the hybrid sandwich composite segment increased by 46.15 % compared to the conventional segment without additives. The highest value of the transverse rupture strength of the specimens was 380 MPa for the B4C reinforced sandwich composite segment and 352 MPa for the hybrid sandwich composite segment. Considering all the tests and analyses, the hybrid sandwich composite segment sample may be the most suitable for diamond-cutting tools.

Management Of Pest And Disease Control In Sallots (Allium Ascalonicum L) Farm Activities Sub-District Sungai Ulin Banjarbaru City

This research aims to identify management pest and disease control and cost incurred of shallot (Allium ascalonicum L) farmer in Banjarbaru City, This research activity was carried out began on December-January 2024 with research sampling method is case study, data analysis with management implementation and financial analysis. Result of this research Pest control is very important for farmers to reduce the risk of crop failure due to pests, the purpose of pest and disease control management is not to eliminate pests altogether but to reduce the risk of attacks due to pests and diseases in shallot plants. Farmers need to apply management functions in controlling pests and diseases, namely the functions of planning, organizing, implementing and supervising. The application of management function in Bawang Mas Horti Langgeng Farmer Group has not been fully carried out properly and Average total cost incurred by each farmer is Rp.640,720. The average cost of medicines per one harvest period is 4 months amounting to Rp.277,800. The average depreciation cost of tools amounted to Rp.41,670.

Effect of contact blast loading on the plastic deformation forming ability of large steel pipes

Plastic deformation forming with metal pipe blanks by contact blast loading inside pipes is an interesting moldless forming technique, also a complex and error-prone process. Some advantages are very characteristic of this forming technique such as no cost of mold, tooling and low energy consumption, no complicated control equipment compared to other forming techniques such as casting, rolling, tube hydrostatic forming, bending – welding. Up to now, the calculation and design of this forming technique mainly use some existing reference empirical formulas, so the experimental results are only suitable in the range of small pipe diameters, and still there are significant deviations for larger pipe diameters. In order to increase the predictability and accuracy of forming process by contact blast loading inside large pipes, this paper presents a study on the influence of the mass of highly explosive material – TNT to the forming ability of large steel pipes from API-5LX-42 mild steel materials by modern 3D numerical simulation – using Abaqus/Cae software. Four output criteria with maximum values are used to evaluate the efficiency of this forming process, including maximum diameter of the blast zone (Dmax£2D0), Von Mises stress (Smax£UTS), Hoop plastic strain component (PE22max£1), and Pipe wall thinning rate (eT-max£60 %). The results of this research on the plastic deformation forming process using numerical simulation can be used for the next experimental step to evaluate the difference between simulation and experiment, as well as use this data in the calculation and design of pipe products with circular or square cross-sections to save both time and money of trial and error before application in actual manufacturing

The cost of inaction: a global tool to inform nutrition policy and investment decisions on global nutrition targets.

At present, the world is off-track to meet the World Health Assembly global nutrition targets for 2025. Reducing the prevalence of stunting and low birthweight (LBW) in children, and anaemia in women, and increasing breastfeeding rates are among the prioritized global nutrition targets for all countries. Governments and development partners need evidence-based data to understand the true costs and consequences of policy decisions and investments. Yet there is an evidence gap on the health, human capital, and economic costs of inaction on preventing undernutrition for most countries. The Cost of Inaction tool and expanded Cost of Not Breastfeeding tool provide country-specific data to help address the gaps. Every year undernutrition leads to 1.3 million cases of preventable child and maternal deaths globally. In children, stunting results in the largest economic burden yearly at US$548 billion (0.7% of global gross national income [GNI]), followed by US$507 billion for suboptimal breastfeeding (0.6% of GNI), US$344 billion (0.3% of GNI) for LBW and US$161 billion (0.2% of GNI) for anaemia in children. Anaemia in women of reproductive age (WRA) costs US$113 billion (0.1% of GNI) globally in current income losses. Accounting for overlap in stunting, suboptimal breastfeeding and LBW, the analysis estimates that preventable undernutrition cumulatively costs the world at least US$761 billion per year, or US$2.1 billion per day. The variation in the regional and country-level estimates reflects the contextual drivers of undernutrition. In the lead-up to the renewed World Health Assembly targets and Sustainable Development Goals for 2030, the data generated from these tools are powerful information for advocates, governments and development partners to inform policy decisions and investments into high-impact low-cost nutrition interventions. The costs of inaction on undernutrition continue to be substantial, and serious coordinated action on the global nutrition targets is needed to yield the significant positive human capital and economic benefits from investing in nutrition.

Research on tool remaining useful life prediction algorithm based on machine learning

Tool wear during machining significantly impacts workpiece quality and productivity, making continuous monitoring and accurate prediction essential. In this context, the present study develops an efficient tool wear prediction system to enhance production reliability and reduce tool costs. It is worth noting that conventional methods, including support vector regression, autoencoders, attention mechanisms, CNNs, and RNNs, have limitations in feature extraction and efficiency. Aiming at resolving these limitations, a multiscale convolutional neural network (MDCNN)-based algorithm is proposed for predicting the remaining life of milling cutters. The algorithm uses preprocessing techniques like wavelet transform and principal component analysis for noise reduction and feature extraction. It then extracts temporal data features using convolutional layers of different scales and employs a self-attention mechanism for feature encoding. Validation on the PHM2010 milling cutter wear dataset with 10-fold cross-validation demonstrates that the MDCNN model achieves a wear prediction accuracy of 97%, a recall rate of 98%, and an F1 score of 97%. The MDCNN model effectively processes multi-band data and captures complex temporal features, confirming its efficiency and accuracy in predicting milling cutter wear and remaining service life.

Optimizing product design and development of engine carbon cleaning maintenance tools using reverse engineering and VDI 2222 methods

This research article explains the product design and development optimization of multi feature engine carbon cleaning maintenance tools. The implementation of the Reverse Engineering method was integrated with VDI 2222 in the research process. The results of the optimal design and development of this tool obtained a component structure that was able to meet 14 types of consumer needs with a total tool cost of IDR 1.137.900 with a total tool weight of 6.9 kg. The results of the load test simulation concluded that the housing case was able to withstand the overall weight of the components that make up the tool. Depending on the liquid chemical used, the results of tool tests on a limited scale have proven to be able in save fuel consumption by ±12.5% per hour with engine workload which can also be reduced by 3,14%.