Quality Of Equipment Research Articles

Dynamic Screw Lead Accuracy Measurement: Research on the Compensation of the Workpiece Placed Away from the Ideal Position.

The screw, a critical element in a variety of transmission mechanisms, significantly influences the performance of the transmission process. Accurate measurement of screw lead is crucial for ensuring the quality of transmission equipment. However, the measurement process can be affected by the precision limits of the measuring instruments and the challenges of manual fine adjustments. This can lead to the screw being misplaced, introducing errors due to the off-center positioning of the workpiece. Such errors can hinder the achievement of high-precision measurements. This research aims to reduce the time needed to adjust for workpiece misalignment and to improve the accuracy of screw lead measurement through error compensation. This study starts by examining two specific scenarios that can cause workpiece misalignment in screw lead accuracy measurements: the tilting of the workpiece and the misalignment of the workpiece axis relative to the circular grating axis. Then, a mathematical model to quantify this misalignment and measure the associated parameters is developed. Based on the measured parameters, a computational model is established to compensate for the bias error under these conditions. This method allows for efficient and precise measurement of the screw lead even when the workpiece is not perfectly aligned. Calibrated screws and a digital micrometer are used to conduct experiments on workpiece misalignment. By comparing measurements with and without error compensation, the effectiveness of the compensation method in enhancing measurement accuracy is demonstrated.

Learning-based production, maintenance, and quality optimization in smart manufacturing systems: A literature review and trends

With the introduction of manufacturing paradigms, including Industry 4.0, production research has shifted its focus to enabling intelligent manufacturing systems within industrial environments. These systems can efficiently schedule and control processes and operations using artificial intelligence methods, including machine learning and deep learning. Since 1995, relevant literature has presented several examples of such implementations, addressing topics, for example equipment fault diagnosis and quality inspections. To this end, the present paper strives to present a state-of-the-art review of the learning-based scheduling and control frameworks, which are exploited in the production research. The review is limited to the relevant research between the years 1995 and 2024, surveying approaches in the domains of manufacturing, maintenance, and quality control. To this end, the paper follows a meta-analysis method for the selection and evaluation of relevant research articles. Moreover, research questions are formulated to analyze the obtained findings and seek out insights on aspects of the relevant research, including the inclusion of decision-making models and dissemination of literature. The provided answers, among others, reveal trends and limitations of the state-of-the art research in relation to learning-based scheduling and control.

Quality Assessment of Electrical Equipment

This paper is concerned with the methods of the measuring the quality and especially how the decision and game theory can be used in order to reach the goal of measuring quality in general and the quality of electrical equipment, in particular.

Quality Assessment of Electrical Equipment using ANOVA and Linear Regression Techniques

The article concerns utilization of linear regression and analysis of variance (ANOVA) for a set of data regarding the quality of electrical equipment. More precisely, this set of data concerns the nonconformant housings of electric motors for different diameters of housings. Both statistical methods, linear regression and ANOVA are employed to analyse this data with regard to their linear dependency and to check whether this data is likely to come from groups with the same mean.

Development of a model of the process of development of manufacturing defects in automation means

In automated process control systems, automation equipment (sensors, converters, amplifiers, etc.) with technical defects arising during their manufacture, which are one of the main causes of failures, is widely used. The paper establishes the possibility of using the laws of nonequilibrium thermodynamics as the basis for determining the relationship between the controlled parameters of automation equipment and the parameters of the displayed medium, which made it possible to build a deterministic model of the development of production defects and, ultimately, determine the directions for changing and adjusting the technological processes of production of automation equipment. A method has been developed for implementing a guaranteed forecast of changes in the parameters of automation equipment based on solving the evolution equation using optimal filtering algorithms, which is the subject of research. The purpose of the work is to improve the quality and reliability of automation equipment by improving the monitoring of defects arising in the production of instruments, functional units and sensors of automation equipment. The article solves the following problems: analysis of existing approaches to the problem of manufacturing defects and methods for their detection and setting a research task; modeling of the process of development of production defects causing changes in the technical condition of automation equipment; development of a decision-making method based on guaranteed prediction of the technical state of automation equipment. The methodology of work is based on the methods of thermodynamic description of the kinetics of processes (when developing a model of the process of development of production defects that cause a change in technical condition) and methods of assessment and forecasting based on optimal filtering algorithms (when developing a decision-making method based on guaranteed foresight of technical condition). The results of the work include a model of the process of development of manufacturing defects that cause a change in the technical condition of automation equipment, and a decision-making method based on a guaranteed forecast of the technical condition of automation equipment. Conclusions. The paper establishes the possibility of using the laws of nonequilibrium thermodynamics to determine the relationship between the controlled parameters of automation equipment and the displayed medium, and to build a deterministic thermodynamic model of the development of production defects. Disclosed is an equation of evolution of technical state of automation equipment based on a deterministic kinetic model of processes occurring in a multicomponent medium, and an observation model which takes into account errors caused by instability of external effects and measurement errors. Disclosed is a method of implementing a guaranteed forecast of change in parameters of automation equipment based on solving the evolution equation using optimal filtering algorithms, which are used to solve estimation and prediction problems.

The Importance of Brand in Medical Tourism

Medical tourism, which is becoming more popular every year, represents a significant segment of global tourism. This trend is driven not only by the growing number of patients seeking better, faster, or more affordable healthcare but also by increasing globalisation and the greater availability of information. In the context of the Czech Republic, where the number of international patients has significantly increased over the last decade, it is essential to understand the role that the brand image of healthcare facilities plays in the decision-making process of these patients. Based on the research conducted, it can be concluded that the key factors influencing the choice of a healthcare facility are the quality of services, safety, and modern equipment. Price and speed of service also play an important role, with patients particularly appreciating a good value-for-money ratio. The importance of communication and customer service is also evident, as effective and high-quality communication can significantly strengthen the brand image and patient trust. The research results suggest that although word-of-mouth and personal recommendations are important, their effect is not statistically significantly greater than that of the marketing communication of a given healthcare facility. This indicates that it is important for healthcare providers to address both forms of communication equally. In conclusion, it can be said that a strong brand image of a healthcare facility, built on quality, safety, and effective communication, plays a key role in attracting foreign patients as part of medical tourism. Healthcare providers should actively develop these factors to be able to compete in the ever-growing medical tourism market.

WAYS TO IMPROVE THE EFFICIENCY OF TECHNOLOGICAL EQUIPMENT

Increasing the productivity of production systems and equipment in the meat industry is inextricably linked with maintenance activities. The article analyzes the influence of manufacturability, hygiene, reliability, simplicity of equipment design on the main indicators of the quality of meat products. It is shown that the Total Productive Maintenance (TRM) and Lean production strategy is an important tool for evaluating the Overall Equipment Effectiveness (OEE) indicator, which is used to evaluate the main types of losses that reduce the efficiency of equipment. The relationship of structural and mechanical characteristics of food masses, humidity of raw materials, temperature and viscosity, processing pressure, density on the optimal operating modes of the equipment is analyzed. Using the OEE concept, the time losses associated with the functioning of the equipment are determined. The types of losses are classified: downtime and changeover (availability or readiness) of equipment, short-term shutdown of equipment and reduction of processing speed (equipment performance), defective products and product losses at startup (quality) of equipment. The application of this method of studying the overall efficiency of the equipment can be applied to any technological equipment used in the meat industry and will eliminate many problems that arise during the operation of technological equipment, improve its technical and economic indicators, develop a system of measures to improve its maintenance and repair. Using this concept, it is possible to systematize the factors that reduce the efficiency of the equipment. At the same time, it is proved that information about the factors affecting the loss of equipment operation time allows you to create a system for maintenance and repair of equipment.

Import substitution of elevator equipment in public procurements: problems and directions of stimulation

The problem of import substitution is relevant for any country, taken into account the requirements of its economic self-sufficiency, independence on the situation at the international markets and on geopolitical changes. For Ukraine in the state of full-scale war, this task is important from the viewpoints of economic resilience and security. For this reason, the Government determined the substitution of import components in public procurements as one of the priorities of its activity. Solving this problem will be important for the projects associated with the procurement for the recovery of infrastructure in post-war period. The sector of elevator equipment production has a significant industrial potential for the post-war recovery of infrastructure in Ukraine. Extension of industrial capacity of this segment of machine building in order to cover the domestic market requirements in post-war recovery period will enable new job creation and will provide a multiplicative effect based on the development of complementary suppliers of production components. However, a number of problems prevents Ukrainian elevator equipment producers from winning in public procurements. The goal of the article is to substantiate the reasonability and to determine the directions and stimulating measures for elevator equipment import substitution in public procurements in Ukraine. The market of elevator equipment of Ukraine has been analyzed. The capacity of Ukrainian elevator equipment producers to compete at the domestic market has been assessed based on price, warranty terms, cost of warranty service, and quality of equipment. Public procurement of elevator equipment and maintenance services in “Prozorro” system has been studied. It was found that about 70 % of public procurements of elevator equipment account for the purchases of imported equipment from Turkey and China. The problems of domestic producers of elevator equipment preventing them from winning the public procurement have been explained. The multiplicative effect from the increase of public procurements of elevator equipment from national producers has been assessed. This proves the reasonability to stimulate import substitution of elevator equipment in public procurements. The directions and measures of elevator equipment import substitution stimulation in public procurements in Ukraine have been suggested.

The Essential Computer Drawing Labs Facilities and Infrastructure to Achieve Training Quality According to International Standards

Educational facilities and infrastructure at any training institute must meet the minimum international standards. This study aims to evaluate the feasibility of the current facilities and infrastructure in the Computer Drawing Labs. The study used quantitative research methods, including observation and documentation. Study results indicate that all aspects of facilities and infrastructure assessed are in the good feasible category, with achievement levels ranging from 70 to 100 percent. The aspect with the lowest feasibility achievement is the space area at 70%, while the aspect of room furniture, educational media, equipment, and environment quality, achieved feasibility levels of 85%

Development of fetal magnetic resonance imaging (MRI) phantom.

Anthropomorphic phantoms play an important role in routine clinical practice. They can be used to calibrate magnetic resonance imaging (MRI) scanners, control the diagnostic equipment quality, and reduce the acquisition time. The latter is especially critical for diagnosing fetal anomalies, which requires optimal image quality within the shortest possible time. This paper aims to develop an MRI fetal phantom and determine the materials that best mimic the magnetic resonance (MR) characteristics of its internal organs. Future phantom features will include simulations of fetal limb movements. A single MRI study of a pregnant woman at 20 weeks 3 days of gestation was used as a reference and for image segmentation. Anonymized Digital Imaging and Communication in Medicine (DICOM) files were imported into 3D Slicer v. 5.2.1 for segmentation of the uterus, fetus, and internal organs. Based on the performed segmentation, a three-dimensional model was obtained for printing on a 3D printer. The mold was 3D printed on an Anycubic Photon M3 Max printer. The paper showcases the selection and manufacturing of compositions to simulate the relaxation times of the fetal organs. Formulations for emulsions and carrageenan- and agar-based hydrogels are presented. The selected compositions were used to fill the 3D printed model. Statistical analysis showed no significant differences in absolute and relative signal values obtained from scans of a pregnant woman at 20 weeks and 3 days and a fetal phantom. During the study, an anthropomorphic fetal phantom was constructed, filled with compositions with relaxation times T1 and T2 similar to the control values of the corresponding tissues. The phantom can be used to set up and optimize fetal MRI protocols, train and educate medical students, residents, graduate students, and X-ray technicians, as well as to timely control image quality and equipment serviceability.

An Efficient Prediction Model on the Operation Quality of Medical Equipment Based on Improved Sparrow Search Algorithm-Temporal Convolutional Network-BiLSTM.

Combining medical IoT and artificial intelligence technology is an effective approach to achieve the intelligence of medical equipment. This integration can address issues such as low image quality caused by fluctuations in power quality and potential equipment damage, and this study proposes a predictive model, ISSA-TCN-BiLSTM, based on a bi-directional long short-term memory network (BiLSTM). Firstly, power quality data and other data from MRI and CT equipment within a 6-month period are collected using current fingerprint technology. The key factors affecting the active power of medical equipment are explored using the Pearson coefficient method. Subsequently, a Temporal Convolutional Network (TCN) is employed to conduct multi-layer convolution operations on the input temporal feature sequences, enabling the learning of global temporal feature information while minimizing the interference of redundant data. Additionally, bidirectional long short-term memory (BiLSTM) is integrated to model the intermediate active power features, facilitating accurate prediction of medical equipment power quality. Additionally, an improved Sparrow Search Algorithm (ISSA) is utilized for hyperparameter optimization of the TCN-BiLSTM model, enabling optimization of the active power of different medical equipment. Experimental results demonstrate that the ISSA-TCN-BiLSTM model outperforms other comparative models in terms of RMSE, MSE, and R2, with values of 0.1143, 0.1157, 0.0873, 0.0817, 0.95, and 0.96, respectively, for MRI and CT equipment. This model exhibits both prediction speed and accuracy in power prediction for medical equipment, providing valuable guidance for equipment maintenance and diagnostic efficiency enhancement.

State Evaluation of Electrical Equipment in Substations Based on Data Mining

This paper explores the combination of a data mining-based state evaluation method for electrical equipment in substations, analyzing the effectiveness and accuracy. First, a Gaussian mixture model is applied to fit all raw data of electrical equipment. The Expectation Maximization algorithm summarizes the data distribution characteristics and identifies outliers. The a priori algorithm is then employed for data mining to derive frequent itemsets and association rules between equipment quality and measurement data. For new equipment samples, conditional probabilities of each feature are independently calculated and combined to classify and evaluate equipment quality. The results suggest that equipment reliability in smart substations can be inferred from historical and real-time operational data using improved association rule algorithms and Naive Bayes classifiers. Finally, the proposed method was applied to analyze statistical data from a 110 kV substation of a power supply company. The states prediction accuracy exceeded 95% when compared with actual equipment quality. The effectiveness evaluation metrics demonstrated that this method outperforms single-category algorithms in terms of accuracy and discrimination ability.

Financial Optimization Management and Equipment Procurement Risk Analysis of New Energy Photovoltaic Power Generation Project

As renewable energy gains momentum and energy structures evolve, photovoltaic power generation projects assume greater significance in the energy sector. This paper aims to explore financial optimization strategies and procurement risks in new energy PV projects, offering countermeasures. Firstly, an in-depth study of PV project finance reveals potential issues during operation. Cost control, income optimization, and capital management strategies are proposed to ensure economic viability and long-term profitability. Secondly, a systematic analysis of equipment procurement risks in PV projects considers factors like market volatility, technological advancements, and supply chain challenges. Comprehensive risk management measures are put forward to mitigate these risks. These measures cover supplier selection, contract management, technical monitoring and other aspects, aiming at minimizing the uncertainty in the procurement process and ensuring the equipment quality and reliability of the project. Finally, based on actual cases, this paper verifies the practicability and effectiveness of the proposed optimal management and risk analysis methods by comparing the effects of different financial management and equipment procurement strategies. Through these studies, this paper aims to provide useful reference for investors, managers and decision makers of new energy photovoltaic power generation projects, and promote them to make more scientific and reasonable financial management and equipment procurement decisions in the process of project implementation.

Employing user-centered design to develop a remote technology kit for studying young children's social communication skills.

The COVID-19 pandemic required behavioral researchers to rapidly pivot to the implementation of remote study protocols to facilitate data collection. Remote implementation required robust and flexible research protocols including reliable audio/visual technology that met all the quality, security, and privacy hallmarks of lab-based equipment, while also being portable and usable by nontechnical staff and participants. The project's primary purpose was to develop a technology kit that could be deployed for data collection in homes with young children. The secondary objective was to determine the feasibility of the kit for use longitudinally across four disparate sites. User-centered design principles were employed in the development and implementation of a technology kit deployed across urban, suburban, and rural participant locations in four states. Preliminary feasibility and usability data were gathered to determine the reliability of the kit across three timepoints. In study 1, a technology kit was constructed addressing all project needs including the provision of the internet to connect remotely with participants. Staff training protocols and participant-facing materials were developed to accompany deployment procedures. In study 2, data gathered in technology logs demonstrated successful capturing of video footage in 96% of opportunities with most technology challenges mitigated. Subsequent behavioral coding indicated 100% of captured assessment footage has been successfully coded to date. Moreover, participants needed less support for technology setup at their later timepoints, and staff rated the kit as highly usable. This study offers a model for future development of technology use in remote community- and home-based pediatric research.

Implementation of Total Productive Maintenance in Centrifugal Pump Maintenance At Pt. Fajar Surya Wisesa

PT. Fajar Surya Wisesa specializes in manufacturing packaging paper, with its factory located in the WWTP Department. The company is dedicated to enhancing the productivity and operational efficiency of its Centrifugal Pump machines through effective maintenance strategies. This study employs a quantitative approach to assess the Overall Equipment Effectiveness (OEE), encompassing availability, performance efficiency, and quality rate, alongside a Six Big Losses analysis. The findings revealed that the average machine availability reached 98%, with a notable decrease observed in August due to downtime incidents. Performance efficiency consistently exceeded 90%, although higher production outputs occasionally led to efficiency declines. Quality rates remained stable and high, signaling advancements in production processes and quality control measures. Overall, the average OEE value attained 88%, surpassing the global standard of 85%. To further optimize Centrifugal Pump machine effectiveness, proposed enhancements include operator training, regular performance assessments, improved operator welfare considerations, selection of premium raw materials, updates to standard operating procedures (SOPs), scheduled preventive maintenance, enhanced workplace safety measures, and investments in energy backup systems. In conclusion, these initiatives have effectively elevated the performance and operational quality of the Centrifugal Pump machines at PT. Fajar Surya Wisesa.

The Lived Experiences of Discharged Patients on Quality Care in a Crowded Emergency Department

Background and Aim: In the Philippines, the problem of overcrowding in emergency rooms causes serious negative effects to delivering quality care to patients. The study aims to investigate the lived experiences of discharged patients from a crowding emergency rooms revealing the difficulties that patients encounter and offer critical insights to improve the standard of care and emergency department flow.  Method: This qualitative study employed a phenomenological approach, using semi-structured interviews to gather data from 16 participants who had recently been discharged from an overcrowded emergency department in Iligan City, Lanao del Norte. The interviews were conducted in the local dialect, Bisaya, and were analyzed using Colaizzi's method for qualitative data analysis.  Results: The findings reveal key themes that emerged from the participants' responses; the stress and anxiety, the environmental stressors such as noise, overcrowding, lack of privacy, the Specific spaces like triage, examination rooms, and waiting areas, the technological environment, particularly equipment quality, the Extended waiting periods, rapid treatment progression, sudden discharge and contrasting temporal experiences. Lastly, human connection amidst chaos and feeling understood and cared for with kindness.  Conclusion: The findings emphasize the need for improved patient flow management, enhanced environmental design, and a patient-centered approach to care delivery to prioritize patient comfort, reduce distress, and promote better outcomes especially for patients. It also shows how nurses care compassionately with patients amidst piling responsibilities in crowding emergency department.

Evaluating the effect of using augmented reality (Metaverse) on improving the teaching and academic performance

This study aimed at evaluating the effect of employing the augmented reality (metaverse) on improving the process of teaching and academic performance. An electronic questionnaire containing five questions was distributed to the academic groups that received the lesson using augmented virtual reality (Metaverse). The aim of the questions was to evaluate their experience, and after they answered the questions, the answers were analyzed in the form of percentages and frequencies. The study sample consisted of (97) students from Al-Ain University enrolled in the programs of (special education, nutrition, and applied sociology), to whom the experiment was applied using augmented virtual reality in teaching during their academic course. The results revealed that (83%) of the respondents reported that the augmented virtual reality contributed to understanding the concepts of the lesson well, (79%) felt enjoyment in using this technique, (75%) suggested that the technique enhanced their involvement in the content well, (68%) suggested that augmented virtual reality could be a useful educational instrument in the future, and (77%) confirmed that the lesson's objectives were achieved by using metaverse technique in teaching. However, several challenges were faced by students, including the used language (only English) and the negative effects of bad quality of used glasses. Based on the findings, the study recommended addressing several key areas for optimizing the use of augmented virtual reality (AVR) in teaching. For example, diversifying language options for AVR content is crucial to accommodating the linguistic diversity among students, thereby enhancing accessibility and comprehension. Additionally, we should invest in high-quality equipment and implement regular maintenance protocols to enhance the quality of equipment, specifically addressing issues related to the negative effects of subpar AVR hardware.

Mathematical Assessment of Pollution Factors from Eddy Currents in the Durrës Seaport

Eddy currents, a significant phenomenon in electromagnetic fields, were first distinguished from general electric currents by Foucault. These currents, influenced by the magnetic field vector (H), magnetic flux density (B), and electric field (E), are present in various environments, including homogeneous and non-homogeneous areas, linear and non-linear environments, and open boundary problems. In marine environments, these currents, referred to as planetary currents, contribute to electrical pollution, impacting maritime infrastructure, machinery, and ecosystems. This study aims to assess the impact of eddy currents in the Durrës Seaport, Albania, focusing on how meteorological factors such as temperature, atmospheric pressure, and humidity influence pollution levels. Using the TES-92 Electro-smog meter and the PCE-THB 40 Thermo-hygrometer and barometer, we measured electromagnetic field characteristics and meteorological parameters. Our results highlight the significant impact of stray currents on marine environments, emphasizing the need for effective measures to minimize their effects and improve the quality and selection of materials and equipment in port facilities. This study provides valuable insights into the environmental and infrastructural challenges posed by electromagnetic pollution and proposes recommendations for mitigating these impacts.

The Factors Influencing the Depression, Anxiety, and Stress of Grassroots Healthcare Workers in the Context of the Covid-19 Pandemic in the Vietnamese Mekong Delta: A Cross-Sectional Study in An Giang Province

Introduction: Grassroots health workers are crucial in Vietnam's healthcare system. As the frontline of healthcare, closest to the community, they are considered the backbone for disease prevention, control efforts, and initial healthcare for the population. The Ministry of Health in Vietnam has endeavored to improve infrastructure, equipment, and workforce quality, along with providing mental health care for grassroots healthcare workers to effectively carry out health education, disease prevention, and well-organized healthcare services. This paper aims to investigate factors affecting depression, anxiety, and stress among grassroots health workers in An Giang Province located in the Vietnamese Mekong Delta region. Methods: A population-based cross-sectional study was conducted using data from the 2023 Grassroots health workers in An Giang Province. A total of 466 grassroots health workers were selected. The Research method to collect quantitative data from the questionnaire tools was applied and data analysis was conducted using the SPSS 22.0. Results: The research findings showed that 18.3%, 28.8%, and 16.8% of participants exhibited symptoms of depression, anxiety, and stress, respectively, predominantly at mild, moderate, severe, and extremely severe levels. Risk factors impacting mental health included income and benefits, COVID-19 infection, and prolonged symptoms affecting physical health, as well as workplace infrastructure. Conclusions: Improving salary policies, physical health care, and upgrading workplace infrastructure will reduce the risk of mental health issues among grassroots health workers, both during the pandemic and in the future.

The issues of development and functioning of common market of medical equipment and articles within the framework of the Eurasian Economic Union

The market of medical devices within the framework of the Eurasian Economic Union is regulated by special legislation that ensures formation of common market and compliance of products with all necessary requirements. This allows to ensure high level of quality of medical equipment and articles that contributes into improving safety and efficiency of medical procedures. The development of uniform requirements, considering world practices, is an important step, since it allows to guarantee high standards not only at level of single states, but also at level of the entire Union. This approach facilitates reinforcement of confidence to medical production of manufacturers from he Eurasian Economic Union countries. The article examines normative legal base regulating issues of formation and functioning of common market of medical equipment and articles within the framework of the Eurasian Economic Union. The analysis of normative legal base of the Russian Federation in section related to medical articles market was carried out. The analysis of the regulatory framework of the Russian Federation in terms of issues related to the market of medical devices was also carried out. The corresponding conclusions were made based on the study results.