Utilization Rate Of Equipment Research Articles

A flexible smart manufacturing system in mass personalization manufacturing model based on multi-module-platform, multi-virtual-unit, and multi-production-line

Since the 21st century, with the gradual improvement of customers' living standards and autonomy, customers are increasingly pursuing personalized products. In order to adapt to this environment, enterprises implement mass personalization manufacturing model. This new manufacturing model needs a complex production system to support, which should adaptive flexible configuration according to the dynamic needs of customers. This configurable and rapid adjustment production system is a flexible smart manufacturing system. This paper studies the flexible layout and optimization of resources for flexible smart manufacturing system in mass personalization manufacturing model, and solves the flexible production preparation problem of sales order based on customer personalization. The main research contents include: flexible layout of production platform, flexible layout of virtual unit, flexible layout and optimization of production line and equipment. As the result of this research, the utilization rate of production layout space and equipment can be improved and the total production cost can be saved. At the same time, the system framework, model algorithm, method and theory studied in this paper have reference value for the research of flexible smart manufacturing system in a new manufacturing model facing mass personalization under the current adaptable industrial trend.

Examining the Efficiency of Automation in Container Terminals

An increase in container traffic, larger tonnage of vessels, scarcity of port area, and shorter turnaround times have driven terminals to process more containers in less time and less space. Thereby, the increasing focus on costs, safety, and environmental control is forcing terminal operators to search for innovative solutions. Automated container terminals are the potential candidates to improve the performance of container terminals and represent a challenge to any subsequent future fluctuations in maritime transport. In this study, we examine the improvement in the performance of container ports by adopting automation through simulation modeling. The effect of the automated guided vehicles and automatic stacking cranes-based automatic container terminal system (AGV-ACT/Automated Guided Vehicles - Automatic Container Terminal system) on container handling operations was evaluated. To create a complete port simulation model, the main objects of the container terminal such as tugboats, berths, quay cranes, stacking blocks, stacking cranes, horizontal transport vehicles, external trucks, and the layout of the terminal are simulated as a whole. Firstly, we created a model representing the existing port to evaluate the overall performance of the port and to validate the simulation model by comparing the actual data with those of the real system. Then, a simulation model for the proposed automatic system was created and evaluated. The simulation model was divided into four main logics: ships arrival and berth allocation, ship loading/unloading, external trucks arrival, and containers storage/retrieval logic. The results of the two systems were compared based on the performance criteria such as ship turnaround time, external trucks turnaround time, and equipment utilization rate. Automation has reduced the turnaround time of the ships and provided a smooth movement for the equipment which showed a high utilization rate. The automated system decreased the ship turnaround time from 9.52 hours to 7.81 hours (18%). The reduction in the waiting times of the container transport vehicles for quay cranes reached 47% and 30% in berths 1 and 2, respectively. On the other hand, external trucks’ turnaround time increased by 124% as only one ASC (Automatic Stacking Crane) is run in each block to perform both seaside and landside operations (seaside operations were prioritized). Automation has improved the overall performance of the terminal. Also, the layout of the automated handling system raised the storage capacity of the port. In the new proposed automated layout, the storage area capacity increased by 27.27%.

Performance Evaluation System Based on Online Monitoring of Internet of Things

Research on performance evaluation system based on online monitoring of Internet of things technology, taking medical imaging equipment as an example. Build the performance management platform of the Internet of things through four aspects: data acquisition, network architecture, CPU, and display output. Select 100 medical imaging devices in clinical use in the hospital and divide them into the control group (50 sets) and the observation group (50 sets) according to different management modes. The control group adopts conventional performance management mode, and the observation group implements Internet of things performance management mode. Compare the differences of equipment operation performance, cost-effectiveness, and service effect between the two groups. The experimental results showed that the equipment utilization rate, operation rate, inspection schedule balance, and technician schedule balance of the observation group were better than those of the control group, and the difference was statistically significant ( P < 0.05). The quarterly cost-benefit increase of x-ray examination equipment, CT equipment, Mr equipment, interventional radiotherapy equipment, color ultrasound instrument, and nuclear medicine equipment in the observation group was higher than that in the control group ( P < 0.05). The satisfaction of imaging doctors, technicians, engineers, and patients with the equipment service quality of the observation group was higher than that of the control group; the difference was statistically significant ( P < 0.05). It is proved that the Internet of things performance management platform of medical imaging equipment can solve the problems of untimely information collection and unscientific scheduling during equipment operation, realize the real-time display and statistics of equipment operation performance, and improve the operation efficiency and service level of medical imaging equipment.

Long-term dynamic allocation and maintenance planning of modular equipment to enhance gas field production flexibility

Modular equipment is becoming popular in unconventional gas field development due to cost savings and flexibility in capacity adjustment by dynamic allocation. It is necessary to make long-term investment and maintenance planning to give full play to the advantages of modular equipment. This paper fills the gap of considering individual scheduling and the impact of utilization time on the value of the equipment in the unconventional gas field development by presenting a comprehensive method that considers the various costs of modular equipment and can facilitate tracking the usage of the equipment. A mixed integer linear programming model is developed to get the solution for the modular equipment, including the processing capacity selection, the installation and use plans, mobile scheduling, and depreciation sale plan, to enhance gas field production flexibility and achieve the best net present value. The changes of production and market demand, and the impact of utilization time on equipment depreciation are taken into account comprehensively. A real case study is used to prove the practicality and advantages of the proposed model. The results show the equipment utilization rate has been increased from 60% to 75%, achieving 10% higher economic benefits when using modular equipment compared with the traditional method in gas field production. In addition, the sensitivity analysis is implemented to investigate the influence of uncertain parameters such as output and market demand, equipment service life, and type of equipment on the equipment dynamic allocation and the economic performance. This study provides a powerful decision-making tool for gas field development to reduce costs, increase efficiency and promote clean practical production.

Well design development for multilayer horizons for the simultaneous separate operation by one well

The positive effects of applying the technology for simultaneous separate operation (hereinafter referred to as SSO) include the reduction in capital investments for the construction of wells for each of the operational facilities, the cutback of operating costs and the development period of a multi-layer horizon, the increase in hydrocarbon production and the final oil recovery period from profitable operation of wells. In addition, the use of this technology contributes to increasing the utilization rate of downhole equipment and enhancing the reliability of the downhole device. The simultaneous separate operation technology is economically efficient due to the production of additional oil, a high profitability index and a low payback period. Keywords: azimuth, zenith angle; off-vertical; well profile; doublelift tubing; liner filter; packers; valves.

Investigation on the current situation of safety protection of medical staffs for the prevention and treatment of infectious diseases in medical institutions in Jiangsu Province

Objective: To investigate the current situation of safety protection of medical staffs in medical institutions in Jiangsu Province, and to provide scientific basis for strengthening the safety protection of infectious diseases and protecting the occupational health of medical staffs. Methods: From September to October 2020, 1274 medical staffs in 43 medical and health institutions were randomly selected as the subjects. The self-made questionnaire for infectious disease prevention and protection was used to analyze the pre-job training and exposure to occupational harmful factors of the respondents. The influencing factors of using protective equipment and occupational injury were analyzed by binary logistic regression. Results: A total of 1216 valid questionnaires were collected with effective recovery of 95.4%. There were 312 males (25.7%) and 904 females (74.3%) , with an average age of (35.8±9.2) years and average working years of (13.6±9.9) years. Among them, 1143 (94.0%) had participated in pre-job training, 535 (44.0%) thought they were exposed to occupational harmful factors of infectious disease prevention, 1082 (89.0%) used protective equipment in daily operation, and 462 (38.0%) had occupational injury. According to binary logistic regression analysis, the utilization rates of protective equipment for medical staffs in Centers for Disease Control and Prevention (OR=2.473, 95%CI: 1.327-4.607, P=0.004) , 30-39 years old (OR=1.586, 95%CI: 1.038-2.426, P=0.033) , 40-49 years old (OR=2.257, 95%CI: 1.243-4.098, P=0.007) , 50 years old and above (OR=5.879, 95% CI: 1.755-19.692, P=0.004) and pre-job training (OR=2.580, 95%CI: 1.301-5.116, P=0.007) were higher than their respective control groups. And medical staffs with graduate degree or above (OR=0.342, 95%CI: 0.167~0.699, P=0.003) had lower utilization rate of protective equipment. Female (OR=1.902, 95%CI: 1.364-2.654, P<0.001) , 30-39 years old (OR=1.589, 95%CI: 1.157-2.181, P=0.004) , bachelor degree (OR=2.070, 95%CI: 1.419-3.021, P<0.001) , exposure to occupational harmful factors (OR=2.753, 95%CI: 2.086-3.634, P<0.001) were the risk factors for occupational injury of medical staffs. Centers for Disease Control and Prevention (OR=0.129, 95%CI: 0.086-0.194, P<0.001) and wearing protective equipment according to regulations (OR=0.597, 95%CI: 0.431-0.827, P=0.002) were the protective factors for occupational injury of medical staffs. Conclusion: At present, the occupational injury rate of medical staffs in Jiangsu Province is high due to various factors in the prevention and control of infectious diseases. It is necessary to pay attention to occupational safety protection, strengthen pre-job training and actively advocate "standard prevention", so as to reduce the exposure risk of harmful factors and promote occupational health of medical staffs.

Research on MMC de-icing system capable of power grid interconnection

Voltage sourced converter (VSC) de-icing device has been gradually applied because of its advantages, such as no requirements on by-pass transformer, no harmonic output on AC side, and small floor area. However, the DC de-icing device will only operate in winter, resulting in low utilization rate. In order to improve the utilization rate of equipment and the power supply reliability of the distribution network, this paper analyzes the current situation of DC de-icing technology and proposes a VSC-HVDC de-icing system composed of two sets of voltage-source DC de-icing devices, which can improve the de-icing efficiency in parallel; Some strategies are proposed, such as AC power balance control of sectionalized busbar under VSC interconnection of de-icing devices as well as emergency power transfer for AC single-end power loss. The paper also builds an EMTDC simulation model of the VSC DC de-icing system and carries out a simulation test, which verifies the functions of the VSC-HVDC de-icing system, such as ice-melting, VAR compensation, AC power balance, and emergency power transfer for AC single-end power loss, etc. The related functions are also verified in the engineering site, which shows that the VSC-HVDC de-icing system proposed in this paper can improve the power supply reliability of distribution substations.

A Study on the Automatic Control System for Quality Assurance of Clinical Pathology Examination Applying Machine Learning Technology

The object of research is a study on a machine learning-based integrated quality control system to provide accurate test results quickly by improving the accuracy of test results and improving the utilization rate of test equipment by analyzing clinical pathology Examination data. As for the development method for research, IEC 62304, the international standard for medical S/W life cycle used in medical software development, was applied, and the S/W life cycle rule was applied to all processors by integrating agile methodology. Random Forest, XGboost (extreme Gradient Boosting), LightGBM (Light Gradient Boosting Machine), and DNN (Deep Neural Networks) to improve Rule Check accuracy to predict abnormality of inspection results, and to monitor abnormal results in real time by rule check calculation method technique was applied. In addition, to improve user convenience, automatic control and user interface technology using a dashboard function applied with machine learning technology, and automatic interlocking interface technology for various heterogeneous inspection devices were applied. Validation and verification were conducted through a qualified testing body (TTA) to ensure reliability. The following results were found through this study. As a result of implementing a module that applied big data-based machine learning technology to the algorithm used for quality control judgment of the first knowledge-based expert system, it was possible to implement a module with more than 95% accuracy. there was. Second, in order to determine whether a real-time alarm function was provided, the development module was linked to the clinical pathology information system and as a result of the experiment, it was found that it was operating normally. In addition, reliability was secured through certification by an accredited certification body. Third, as a communication support method for the interface of the inspection equipment, stability and various technologies were secured through a number of communication tests and certification tests such as RS232C, TCP/IP, and Serial HL7. Fourth, through multiple database tests (Oracle, MSSQL, MySQL, MS Access, etc.), cost savings were secured by resolving duplicate investment by providing database neutrality and interface with other systems. Fifth, utility and user satisfaction were enhanced by providing program functions for outputting the result report in various formats and configuring the UI settings, and the UI settings were modularized to reduce the program development costs and allow the modules to be reused. Through the results of research, small and medium hospitals can improve the reliability of inspection results through the machine learning-based quality control module, and through real-time monitoring of the inspection equipment, it is possible to quickly determine whether there is a failure and improve the operation rate of the inspection equipment. In addition, by providing a module that can be linked with the existing information system, it was made easy to link, and the convenience of the user was improved by providing various UI environments. As a result, it can be expected that the hospital's competitiveness and medical service will be improved by resolving the difficulties of quality control that small and medium-sized hospitals had and providing prompt and accurate test results.

Using Simulation Optimization to Solve Patient Appointment Scheduling and Examination Room Assignment Problems for Patients Undergoing Ultrasound Examination.

This study investigates patient appointment scheduling and examination room assignment problems involving patients who undergo ultrasound examination with considerations of multiple examination rooms, multiple types of patients, multiple body parts to be examined, and special restrictions. Following are the recommended time intervals based on the findings of three scenarios in this study: In Scenario 1, the time interval recommended for patients’ arrival at the radiology department on the day of the examination is 18 min. In Scenario 2, it is best to assign patients to examination rooms based on weighted cumulative examination points. In Scenario 3, we recommend that three outpatients come to the radiology department every 18 min to undergo ultrasound examinations; the number of inpatients and emergency patients arriving for ultrasound examination is consistent with the original time interval distribution. Simulation optimization may provide solutions to the problems of appointment scheduling and examination room assignment problems to balance the workload of radiological technologists, maintain high equipment utilization rates, and reduce waiting times for patients undergoing ultrasound examination.

Demand-side Management Based on Model Predictive Control in Distribution Network for Smoothing Distributed Photovoltaic Power Fluctuations

With the rapid increase of distributed photovoltaic (PV) power integrating into the distribution network (DN), the critical issues such as PV power curtailment and low equipment utilization rate have been caused by PV power fluctuations. DN has less controllable equipment to manage the PV power fluctuation. To smooth the power fluctuations and further improve the utilization of PV, the regulation ability from the demand-side needs to be excavated. This study presents a continuous control method of the feeder load power in a DN based on the voltage regulation to respond to the rapid fluctuation of the PV power output. PV power fluctuations will be directly reflected in the point of common coupling (PCC), and the power fluctuation rate of PCCs is an important standard of PV curtailment. Thus, a demand-side management strategy based on model predictive control (MPC) to mitigate the PCC power fluctuation is proposed. In pre-scheduling, the intraday optimization model is established to solve the reference power of PCC. In real-time control, the pre-scheduling results and MPC are used for the rolling optimization to control the feeder load demand. Finally, the data from the field measurements in Guangzhou, China are used to verify the effectiveness of the proposed strategy in smoothing fluctuations of the distributed PV power.

A Cross-Cultural Study on the Capability Development Difference of Educational Management Technology in China and the West

Abstract Against the background of “Internet plus,” western countries have taken a lead in modernizing educational management technology to fit the times. The application of education management technology in China is in a period of rapid development. There are certain differences between China and western countries. In order to adapt to the intelligent trend of contemporary education management reform and improve the national macro education management level, there should be cross-cultural thinking on the differences in the development of educational management technology capabilities between China and the West. Based on the literature analysis of Chinese and Western education management technology and education management theory, and based on the research data of 8 domestic colleges and universities education management technology, we explored the development differences between China and the West in teaching evaluation, multimedia teaching, and teaching decision-making. The results showed that ideology, national conditions and technology are the main influencing factor of the differences in the development of educational management technology capabilities between China and the West. We need to create a cross-cultural education concept conflict, cross-cultural perspective to re-plan the teacher’s positioning, and fundamentally change the concept of teachers to accept Western education management models in China. The application proportion of education management technology should be allocated based on the actual teaching situation, to increase the teaching utilization rate of multimedia equipment, and reduce unnecessary multimedia teaching. Data-driven intelligent teaching decision-making technology should be developed to guide teaching behavior scientifically and efficiently. Finally, we should construct a modern management system in line with national conditions, as well as narrow the gap between Chinese and western educational management.

Energy and exergy analysis of a novel solar-air composite source multi-functional heat pump

As multi-functional heat pump with higher equipment utilization rate will face more complicated operation condition, the integration with composite heat source will be good solution to improve the operational stability and output performance. In this paper, a novel solar-air composite source multi-functional heat pump (SA-CMHP) has been proposed. Different from conventional single-source heat pump, the proposed system has two evaporators operating in parallel in space heating mode. As the distribution of refrigerant at evaporation side is associated with the output performance of SA-CMHP, the space heating performance under different refrigerant distribution ratio (γ) has been studied based on energy and exergy methods. Besides, economic performance of SA-CMHP for space heating has been analyzed and compared with single-source heat pump. The results indicate that with the increase of γ, the variation of evaporation capacity, power consumption, heating capacity, COP and exergy efficiency tends to increase at first and then decrease. When solar irradiation is 200W/m2, 300W/m2 and 400W/m2, COP and exergy efficiency reach the highest value at γ of 0.6, 0.7 and 0.8. When ambient temperature is 4 °C, 7 °C and 10 °C, COP and exergy efficiency reach the peak values at γ of 0.6.

Practical Application of QR Code Electronic Manuals in Equipment Management and Training.

Objective: To explore the application value of QR code electronic manuals in operating theater equipment management and training.Methods: The control group adopted the traditional management mode. Training was carried out before each device was put into use in the department. A unified operation process and a paper card manual for common faults were formulated and hung next to each device. For the observation group, the electronic manuals generated by the QR code were pasted on the operating theater equipment for management and training. The management and training effect was compared between the two groups.Results: The efficiency of equipment management and training using the QR code electronic manuals was significantly higher than that of traditional training, and the difference was statistically significant (P < 0.05).Conclusion: The QR code manuals are very effective in operating theater equipment management and training. They can be read and learned in time to improve the operating theater equipment utilization rate, accuracy rate, and equipment management and training quality.

Dispatch Optimization Model for Haulage Equipment between Stopes Based on Mine Short-Term Resource Planning

The working environment of underground mines is complicated, making it difficult to construct an underground mine production plan. In response to the requirements for the preparation of a short-term production plan for underground mines, an optimization model for short-term resource planning was constructed, with the goal of maximizing the total revenue during the planning period. The artificial bee colony optimization algorithm is used to solve the model using MATLAB. According to the basic requirements of underground mine ore haulage and ore hoisting, a haulage equipment inter-stopes dispatch plan model was constructed, with the primary goal of minimizing the haulage equipment wait time. A non-dominated sorting genetic algorithm is used to solve the optimization model. An underground mine is examined using the two models, and the optimization results are compared and verified with the scheme obtained by using traditional optimization algorithms. Results show that based on the improved optimization algorithm, the use of short-term production planning schemes to guide mine production operations can increase the haulage equipment utilization rate, thereby increasing mine production revenue.

A Non-Dominated Genetic Algorithm Based on Decoding Rule of Heat Treatment Equipment Volume and Job Delivery Date

This paper investigated the flexible job-shop scheduling problem with the heat treatment process. To solve this problem, we built an unified mathematical model of the heat treatment process and machining process. Up to now, this problem has not been investigated much. Based on the features of this problem, we are intended to minimize Cmax, maximize the space utilization rate of heat treatment equipment, and minimize the total delay penalty to optimize the scheduling. By taking the dynamic process arrival under consideration, this paper proposed a set of decoding rules based on the heat treatment equipment volume and job delivery date to achieve a hybrid dynamic scheduling solution during one scheduling procedure. When the utilization rate of heat treatment equipment volume is maximized, and the job delivery date is taken under consideration, it is preferred to minimize the number of workpiece batches in the same job, and reduce the waiting time of the pending job. In combination with the improved adaptive non-dominated genetic algorithm, we worked out the solution. Furthermore, we verified the effectiveness of the proposed decoding rules and improved algorithm through algorithm comparison and calculation results. Finally, a software system for algorithm verification and algorithm comparison was developed to verify the validity of our proposed algorithm.

Design of Intelligent Robot Flexible Sorting Center

In order to make up for the shortcomings of traditional robot sorting flexibility and limited operation efficiency, the concept of intelligent robot flexible sorting center is proposed in this paper. We firstly conceive its characteristics, then construct its structure, which consists of a robot with changeable claws, a claw storage, an automatic setback stereoscopic warehousing system, an order goods conveying system, a visual recognition information system. Thus make the intelligent sorting intensive system with more functions enables the robot to adapt to a variety of picking methods, showing higher flexibility, higher order sorting quality, higher equipment utilization rate, relatively stable sorting capacity and great adaptability, its application scope can be continuously expanded to meet the needs of more diversified goods.

RESOURCE UTILIZATION ANALYSIS OF HIGHWAY PROJECTS USING ARENA

The construction sector is a significant contributor to the Gross Domestic Product of a developing country. Infrastructure improvement plays a vital role in this wherein highway construction is a dynamic sector requiring proper planning and scheduling multiple resources. Appropriate integration among various associated stakeholders is essential for a project’s success, aided by supply chain management. Resource planning is one of the basic concepts in supply chain management, with material and equipment management being the critical area. The main objective of this study is to develop a conceptual supply chain simulation model using ARENA, to analyze the equipment idling and utilization rate, keeping inter-arrival time for dispatch, the number of equipment, and working hours as constant. This model employs the real-time ‘best fit’ material utilization data as input. Material utilization data collected from 62 construction projects are analyzed to arrive at a ‘best fit’ probability distribution. This study’s conceptual supply chain simulation model helps formulate suitable material and equipment delivery plans to lessen risk in construction projects.

Evaluation of Rural Dwellings’ Energy-Saving Retrofit with Adaptive Thermal Comfort Theory

The purpose of energy-saving retrofit of rural dwellings is to obtain a more comfortable indoor thermal environment with reasonable investment. The utilization rate of heating and air conditioning equipment for dwellings in poor rural areas is very low, and the buildings operate in natural ventilation mode all year round. Since the existing research on energy-saving retrofit is aimed at air-conditioned buildings, the research methods and results are not applicable to rural dwellings. This paper proposes a set of energy-saving retrofit evaluation methods suitable for natural ventilation buildings and applies it to the research on energy-saving retrofit of rural dwellings in cold climate regions of China. The specific process is as follows: First, this paper analyzed the current situation using field research and established a typical building model. Second, the DesignBuilder software was used to simulate all 725 schemes. Subsequently, the three main retrofit measures (replacing the external insulation windows, setting the external wall insulation layer and setting the roof insulation layer) were analyzed separately, and the optimal parameters of each retrofit measure were obtained. Finally, the entropy weight method was used to perform a multi-objective optimization analysis on all retrofit plans. The results show that 6+12A+6-mm insulating glass windows + 50-mm external wall insulation + 90-mm roof insulation is the optimal energy-saving reconstruction scheme. Compared with the benchmark building, the energy-saving rate of the optimal scheme is increased by 23.81%, and the annual adaptive thermal discomfort degree-hours are decreased by 13.17%.

Real-Time Data Scheduling of Flexible Job in Papermaking Workshop Based on Deep Learning and Improved Fuzzy Algorithm

The traditional real-time data scheduling method ignores the optimization process of job data that leads to delayed delivery, high inventory cost, and low utilization rate of equipment. This paper proposes a novel real-time data scheduling method based on deep learning and an improved fuzzy algorithm for flexible operations in the papermaking workshop. The algorithm is divided into three parts: the first part describes the flexible job shop scheduling problem; the second part constructs the fuzzy scheduling model of flexible job data in papermaking workshop; and finally the third part uses a genetic algorithm to obtain the optimal solution of fuzzy scheduling of flexible job data in papermaking workshop. The results show that the optimal solution is obtained in 48 seconds at the 23rd attempt (iteration) under the application of the proposed method. This result is much better than the three traditional scheduling methods with which we compared our results. Hence, this paper improves the work efficiency and quality of papermaking workshop and reduces the operating cost of the papermaking enterprise.

Methods to Predict the Rest Life of Gear System

Under the development of large-scale, complicated and automatic rotating machinery, people’s requirements for efficiency, safety and reliability are increasing daily. It has an important impact on prolonging equipment life, improving equipment utilization rate, increasing equipment safety, shortening maintenance time and reducing maintenance cost based on condition monitoring, identification and diagnosis of rotating machinery at the initial stage of fault. Taking the gear transmission system as the research object, this paper collects and enumerates the methods of gear system life prediction, and proposes a combined mathematical model of WD-GM (1,1) to predict the degeneration trend and failure time of gears. The prediction accuracy can reach 95%.