Equipment Management Research Articles

Enhanced Construction Productivity by Effective Equipment Management through Fleet Operations

Abstract: In construction equipment management, achieving optimum utilization is essential for cost reduction and ensuring efficient completion of tasks. Equipment fleets, which comprise various machines working together, are central to this goal. For instance, tasks like loading, hauling, and compaction often require coordination between an excavator, multiple haul units, and auxiliary machines. These interconnected systems form the backbone of construction projects, with each component contributing to overall productivity. Take, for example, an excavator and a fleet of trucks; they operate as a linked system where the performance of one directly impacts the efficiency of the others. Therefore, effective management involves not only maximizing the efficiency of individual machines but also coordinating their operations to minimize downtime and optimize production. By understanding the interdependence of equipment and implementing strategies to enhance their performance collectively, construction projects can achieve greater efficiency and cost-effectiveness

Medical Equipment Management System Based on the Concept of Whole Life Cycle

Strengthen the legal, compliant, and rational use of medical equipment and further guide the rationalization of medical behaviors. By utilizing the Internet of Things (IoT) and image analysis technology, collect real-time operation data of the equipment, establish a real-time running database for medical equipment, and cooperate with the 12 key links of the "whole life" of the equipment and the 8+6 management system framework to implement lean management of the efficiency, benefit, and effectiveness of medical equipment usage. It realizes the improvement of the quality and efficiency of medical equipment, cost reduction and cost control, and provides data support for scientific decision-making. This study innovates the management model for the entire life cycle of medical equipment, providing a scientific approach to the management of hospital equipment.

Proactive framework for obsolescence management of electrical equipment in oil and gas industry

PurposeEnergy consumption has increased significantly since the 1970s, which has increased demand for sufficient infrastructure in the oil and gas industry. Many top-notch oil and gas companies invested in and equipped their facilities with high-capacity electrical equipment to meet high demand and benefit from high revenues. This is becoming a challenge nowadays for old facilities in the oil and gas industry, as most of the electrical equipment installed has reached or even exceeded its lifetime. Moreover, many of the original equipment manufacturers (OEMs) for electrical equipment from the 1980s are no longer in market today. Therefore, the aim of this study is to develop a proactive, cost-effective obsolescence management framework for electrical equipment in the oil and gas industry, considering the aging factor of the equipment.Design/methodology/approachFirstly, the study begins with gathering available information and identifying criteria. Secondly, the data collection is evaluated by subject-matter-experts (SMEs) in asset management field to ensure compliance with updated international standards and relevant regulatory requirements. Thirdly, a multi-criteria decision-making process is used to rank criteria. Finally, a scoring system is developed to measure the electrical equipment obsoleteness.FindingsThe developed framework will assist decision-makers in making informed decisions about maintenance, replacement or upgrades, using knowledge from previous studies and experts’ input. The result finding indicates that considering aging correction factors when measuring equipment obsoleteness leads to accurately and correctly predicting the electrical equipment obsoleteness score.Originality/valuePrevious studies have addressed obsolescence management without taking equipment age into account, regardless of how the equipment is performing. Thus, the lack of a comprehensive obsolescence management framework that accounts for both cost-effectiveness and the aging factor in the oil and gas industry poses a critical challenge.

Sistem Informasi Manajemen Bengkel Beserta Peralatannya

Effective and efficient workshop management is a crucial element in the shipbuilding industry to ensure smooth production processes and quality final results. In an effort to increase efficiency and productivity, this research optimizes workshop management from equipment to monitoring project work on this system. Especially in the HO (Hull Outfitting) system at PT. PAL INDONESIA. The case study method was used to collect data from field observations, interviews with relevant personnel and analysis of documentation related to application implementation. This application facilitates more detailed real-time monitoring of workshop activities, allowing managers to quickly identify and resolve operational problems and take necessary corrective actions. The use of this application also aims to improve equipment and material management with more efficient scheduling and better integration between various departments. Implementing the HO (Hull Outfitting) system in applications also provides additional benefits, such as more integrated and comprehensive project management, better monitoring of the condition of workshop equipment, and reduced risk of errors and delays. With a web-based application, the equipment calibration and maintenance process is more structured, transparent and responsive to changes. These findings underline the importance of information technology in supporting the optimization of workshop management and increasing productivity in the shipbuilding industry.

Infection prevention practice in home healthcare: a mixed-method study in two Swiss home healthcare organisations.

Infection prevention and control (IPC) research has long neglected the home healthcare sector with its unique challenges. This study aimed to gain an understanding of the barriers to the implementation of infection prevention practices relevant to this setting, the related attitudes, perceived relevance and priorities from the home healthcare worker perspective in Switzerland. The mixed-method study involved semi-structured interviews (n = 18) and an anonymous web-based survey (n = 144) among nursing assistants and nurses from two home healthcare organizations in northwest Switzerland. Questions in both sub-studies focused on perceived challenges to infection prevention practices, perceived relevance, and related attitudes and mitigation strategies. Using an exploratory-sequential design, survey questions were designed to quantify and complement the findings from the interview study. Healthcare workers in these two organisations felt adequately protected, trained and supported by their organisations regarding IPC (survey agreement rates > 90%). General challenges to IPC in the home environment most agreed on were lack of cleanliness, lack of space, and the priorities of the patient to be respected (survey agreement rates 85.4%, 77.1%, and 70.8%, respectively). Practices and perceived challenges in the case of colonisation with multi-drug resistant organisms (MDRO) and potentially infectious diarrheal or respiratory illnesses varied highly regarding information transfer, use of protective equipment, and use and disinfection practices of multi-use equipment. Challenges to hand hygiene, sharps safety, waste management and decontamination of equipment did not feature as a prominent concern. This study is the first to characterise the implementation of infection prevention practices and the related challenges in home healthcare in Switzerland. Home healthcare workers describe various challenges related to infection prevention practices as largely manageable in their work routine, and generally show satisfaction with the support provided by their organisations regarding IPC precautions. Key findings regarding challenges amenable to interventions include uncertainty and inconsistency regarding the management of MDRO colonisation and acute illnesses, and gaps in information transfer. Those challenges may benefit from both organisational interventions and further research into the level of precautions that are appropriate to the home healthcare setting.

Discussion on the Management Strategy of Imaging Medical Equipment under the New Situation

In the realm of healthcare, particularly in the management of medical imaging equipment, unprecedented challenges and opportunities are encountered. This is especially pronounced in the niche domain of gastrointestinal endoscopy, where innovative management strategies are pivotal in the face of evolving circumstances. With the rapid iteration of technology, the escalating scarcity of medical resources, alongside the rising costs of management and maintenance, coupled with the ongoing flux of regulations and standards, these factors collectively constitute the intricate landscape confronting current management of medical imaging equipment. Addressing the pace of technological advancement, employing proactive technological foresight and flexible updating strategies are paramount. This entails not only technological upgrades of the equipment itself but also continuous training and education for operators to ensure their alignment with technological advancements. Given the scarcity of medical resources, enhancing the utilization and efficiency of existing equipment becomes imperative. This may involve optimizing equipment allocation and scheduling, reducing idle time, while also exploring the application of emerging technologies such as telemedicine to expand service coverage. This article will delve into how, amidst new circumstances, effective management strategies can optimize the utilization and maintenance of gastrointestinal endoscopy to cope with challenges such as the rapid pace of technological evolution, scarcity of medical resources, increasing management and maintenance costs, as well as changes in regulations and standards.

Differential Diagnosis, Prevention Measures, and Therapeutic Interventions for Enhanced Monkeypox (Mpox) Care.

Monkeypox (Mpox) is a rare viral disease that presents considerable challenges in healthcare settings, necessitating enhanced nursing care for effective management. This review thoroughly explores key aspects related to improving nursing care for Mpox. It commences by examining the background information on Mpox, encompassing its etiology, epidemiology, and modes of transmission. The differential diagnosis of Mpox is investigated, elucidating its clinical presentation, symptoms, and diagnostic methods to differentiate it from similar conditions. Prevention and control measures at both the public health and healthcare levels are scrutinized, including surveillance and reporting, contact tracing, isolation, and vaccination programs. In healthcare settings, infection prevention and control strategies, such as proper utilization of personal protective equipment, hand hygiene, and environmental management, are discussed. Furthermore, therapeutic interventions for Mpox, including symptomatic management, antiviral therapy, and supportive care, are outlined, with a specific emphasis on pain management, fever control, and psychosocial support. Nursing care strategies encompass patient assessment and monitoring, infection prevention strategies, psychosocial support, and patient education. The challenges encountered in enhancing nursing care for Mpox are acknowledged, along with research gaps and areas for further investigation. Finally, innovations in nursing practice for improved care, such as technology integration and simulation-based training, are explored. Enhancing nursing care in Mpox is crucial for positive patient outcomes, reducing transmission risks, and promoting overall well-being. By addressing the unique challenges, conducting further research, and embracing innovative practices, healthcare professionals, particularly nurses, can provide optimal care and contribute to better management of Mpox cases.

Assistance of analytical ferrography in the interpretation of wear test results carried out with biolubricants

Analytical ferrography plays a crucial role in predictive maintenance, which is a proactive approach to asset and equipment management. This technique provides valuable information about the internal condition of machines and components, allowing early identification of potential problems and the scheduling of maintenance interventions before catastrophic failures occur. Ferrography allows you to identify worn particles, non-metallic inclusions and other indicators of wear on components. By analyzing samples of lubricating oil or hydraulic fluid, analytical ferrography can offer insights into the health of internal components such as gears, bearings and other critical elements. Changes in particle concentration and composition may indicate abnormal wear. This work involves the use of analytical ferrography to interpret wear results carried out with two vegetable lubricants with additives, compared to a mineral lubricant, also with additives. To assist in the interpretation of the results, the open source software Image J and a small program developed in Python were used. It was found that it is possible to use these two tools to aid the interpretation of ferrograms.

Development and Usability Evaluation of VulcanH, a CMMS Prototype for Preventive and Predictive Maintenance of Mobile Mining Equipment

This paper details the design, development, and evaluation of VulcanH, a computerized maintenance management system (CMMS) specialized in preventive maintenance (PM) and predictive maintenance (PdM) management for underground mobile mining equipment. Further, it aims to expand knowledge on trust in automation (TiA) for PdM as well as contribute to the literature on explainability requirements of a PdM-capable artificial intelligence (AI). This study adopted an empirical approach through the execution of user tests with nine maintenance experts from five East-Canadian mines and implemented the User Experience Questionnaire Plus (UEQ+) and the Reliance Intentions Scale (RIS) to evaluate usability and TiA, respectively. It was found that the usability and efficiency of VulcanH were satisfactory for expert users and encouraged the gradual transition from PM to PdM practices. Quantitative and qualitative results documented participants’ willingness to rely on PdM predictions as long as suitable explanations are provided. Graphical explanations covering the full spectrum of the derived data were preferred. Due to the prototypical nature of VulcanH, certain relevant aspects of maintenance planning were not considered. Researchers are encouraged to include these notions in the evaluation of future CMMS proposals. This paper suggests a harmonious integration of both preventive and predictive maintenance practices in the mining industry. It may also guide future research in PdM to select an analytical algorithm capable of supplying adequate and causal justifications for informed decision making. This study fulfills an identified need to adopt a user-centered approach in the development of CMMSs in the mining industry. Hence, both researchers and industry stakeholders may benefit from the findings.

Research on the evolutionary control of unsafe behavior of construction personnel based on multi-field coupled-homogeneous analysis model.

Unsafe behavior among construction personnel poses significant risks in petroleum engineering construction projects. This study addresses this issue through the application of a multi-field coupled homogeneous analysis model. By conducting case analyses of petroleum engineering construction accidents and utilizing the WSR methodology, the influencing factors of unsafe behaviors among construction personnel are systematically categorized into organizational system factors, equipment management factors, and construction personnel factors. Subsequently, employing Risk coupling theory, the study delves into the analysis of these influencing factors, discussing their coupling mechanisms and classifications, and utilizing the N-K model to elucidate the coupling effect among them. Furthermore, a novel approach integrating coupling analysis and multi-agent modeling is employed to establish an evolutionary model of construction personnel's unsafe behavior. The findings reveal that a two-factor control method, concurrently reinforcing equipment and construction personnel management, significantly mitigates unsafe behavior. This study provides valuable insights into the evolution of unsafe behavior among construction personnel and offers a robust theoretical framework for targeted interventions. Significantly, it bears practical implications for guiding safety management practices within petroleum engineering construction enterprises. By effectively controlling unsafe behaviors and implementing targeted safety interventions, it contributes to fostering sustainable development within the petroleum engineering construction industry.

Digital Lab

This research paper explores the implementation of a "Digital Lab" platform designed to revolutionize traditional lab management in education. The platform facilitates real-time collaboration between faculty and students, irrespective of physical locations, fostering engagement and knowledge sharing. This paper presents the problem of student disengagement, outlines the platform's objectives, and discusses the key features, including scheduling, resource allocation, and equipment management. The paper also addresses the need for real-time monitoring to enhance student accountability and productivity. Keywords: Laboratory management, Student engagement, Real-time collaboration, Remote learning, Real-time monitoring

Comparative Analysis of the Medical Equipment Management Process in Colombo Gampaha and Kaluthara Districts

Comparative Analysis of the Medical Equipment Management Process in Colombo Gampaha and Kaluthara Districts

Transforming equipment management in oil and gas with AI-Driven predictive maintenance

The oil and gas industry faces significant challenges in managing equipment maintenance due to the complexity and criticality of its assets. Traditional maintenance approaches are often reactive and inefficient, leading to costly downtime and safety risks. However, the emergence of artificial intelligence (AI) and predictive maintenance technologies offers a transformative solution to these challenges. This paper explores the role of AI-driven predictive maintenance in revolutionizing equipment management in the oil and gas sector. AI-driven predictive maintenance leverages machine learning algorithms to analyze equipment data and predict when maintenance is required before a breakdown occurs. By monitoring equipment performance in real-time, AI can identify potential issues early, allowing operators to take proactive maintenance actions. This approach helps minimize downtime, reduce maintenance costs, and improve overall equipment reliability and safety. The implementation of AI-driven predictive maintenance requires a comprehensive strategy that includes data collection, analysis, and integration with existing maintenance practices. Successful adoption of AI-driven predictive maintenance can lead to significant benefits for oil and gas companies, including increased equipment uptime, extended asset lifespan, and enhanced operational efficiency. This paper reviews the current landscape of equipment management in the oil and gas industry, highlighting the limitations of traditional maintenance practices and the need for a more proactive approach. It then examines the principles and benefits of AI-driven predictive maintenance, showcasing real-world examples of its successful implementation. Finally, the paper discusses the challenges and considerations for implementing AI-driven predictive maintenance and provides recommendations for oil and gas companies looking to transform their equipment management practices. Keywords: Transforming Equipment; Management; Oil and Gas; AI-Driven; Predictive Maintenance.

Design of CuS composite carbon-based Ni Al-LDH multifunctional phase change composite with electromagnetic shielding performance and heat storage capacity

CuS-based composites are widely used in the fields related to photothermal energy storage and electromagnetic shielding and are excellent candidates for composites with phase change materials. To meet the requirements of micro-integration and electromagnetic resistance of electronic products and optimize the thermal management of electronic products, it is necessary to prepare new flexible composite phase change materials. In this paper, through the design of MPC@Ni Al-LDH/CuS double-layer structure, two-step vacuum filtration method is used, and the highly conductive materials CuS and MPC are introduced into the manufacture of PCM films. With the help of Ni Al-LDH, flame retardancy is introduced. The electromagnetic wave absorption performance is enhanced, and the existence of nano-cellulose (CNF) makes the film have excellent mechanical properties. Ni Al-LDH/MPC and CuS substrates with stable and high mechanical properties are prepared by ultrasonic treatment. According to scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), differential scanning calorimetry (DSC) and thermogravimetry (TG) characterizations, PEG successfully entered the MPC/CuS skeleton by vacuum filtration, and flexible phase change composite bilayers (MLPC) were obtained. Due to the synergistic effect of structure and components, the obtained composite film has many different excellent functions. Specifically, when MPC@Ni Al-LDH is 15 wt%, the phase transition enthalpy, thermal conductivity, electromagnetic shielding, and electrical conductivity are 146.8 J/g, 1.07 W/m·K, 38.8 dB and 126.4 S/m, respectively. The 3600 s infrared temperature measurement results show that the sample has stable thermal properties. Due to the presence of CuS, when MPC@Ni Al-LDH is 5 wt%, its absorbance can be kept at 1.51 L/(g·cm), and its photothermal conversion efficiency can reach 90.6 %. The MPC/CuS structure in the composite film provides many heat transfer channels, which reduces the phonon scattering in the heat transfer process and significantly increases thermal conductivity. Therefore, this multifunctional flexible phase change film can be used in photothermal conversion devices and for thermal management of electronic equipment, and it has broad application prospects in wearable equipment design due to its excellent electromagnetic shielding ability and infrared thermal stealth ability.

A novel fuzzy multi-criteria decision-making for enhancing the management of medical waste generated during the coronavirus pandemic

The coronavirus pandemic significantly increased the use of essential medical supplies, resulting in a surge in medical waste generation. This surge has spurred extensive research into sustainable disposal methods for safe and environmentally responsible medical equipment management. Addressing this multifaceted issue falls within the domain of multi-criteria decision-making. This study presents a comprehensive framework for selecting optimal medical waste treatment methods, considering economic, technological, environmental, and social factors. This is the first study to address the problem of selecting a medical waste disposal technology using the Fuzzy Dombi Bonferroni. The mean operator to combine expert opinions, the fuzzy preference selection index method to evaluate the criteria and the fuzzy compromise ranking of alternatives from distance to ideal solution method to rank the alternatives. According to the weightings, the social dimension holds the highest significance at 0.3217. Disinfection efficiency ranks as the most critical criterion, weighing in at 0.0823. The autoclave is rated as the top disposal technique, with a utility function value of 5.4579. Sensitivity analyses ensured the stability and reliability of the models. The adaptability of the applied model to sustainable practices such as energy conversion, material recycling, and resource recovery represents an essential aspect of policymaking in waste management. This assessment can guide policy formulation or improvement processes for waste disposal.

A BWM-TOPSIS Linear Programming Model for Evaluating the Performance of Health-Promoting Hospitals with McKinsey 7s Framework in Organizational Management

This research addresses the critical aspect of evaluating operational performance in health promotion hospitals, which play a vital role in providing medical services to local communities. The research proposes an integrated method for performance assessment, utilizing the Best-Worst Method (BWM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) linear programming model. Taking the case of health promotion hospitals in Maha Sarakham province, Thailand, and considering the McKinsey 7s framework's seven criteria, BWM is employed to determine the criteria weights. Subsequently, the TOPSIS linear programming model selects the ideal health promotion hospital based on these weights. The BWM analysis reveals criteria weights in the following order: system, staff, skill, style, structure, strategy, and shared value. The TOPSIS linear programming model identifies SH12 as the top-performing health promotion hospital with a closeness coefficient value of 0.8821. Additionally, a Spearman's rank correlation test validates this proposed method against the original TOPSIS approach, yielding a correlation value of 1.0. These findings provide valuable guidance for organizations, particularly in shaping strategic policies and resource allocation within medical service units, medical equipment, and personnel management in organizational settings. This study offers that the proposed method is simpler and will aid in the ongoing analysis of strengths and weaknesses in the improvement of organizations and development, helping organizations adapt to changes.

Application of IoT technology for enhancing the consumer willingness to return E-waste for achieving circular economy: A Lagrangian relaxation approach

Poor management of waste electronic and electrical equipment (e-waste) has resulted in serious challenges to the environment and, consequently, to living organisms. Increasing consumer willingness to return household e-waste is a practical solution for better e-waste management. In this paper, for the first time, a circular supply chain network is structured by applying internet of things (IoT) technology to increase consumer willingness to return household e-waste and to manage the network more effectively. For this purpose, we formulate a mixed-integer linear programming model whose objective is to minimize strategic costs (setup costs and IoT deployment costs) and operational costs (transportation costs, costs associated with IoT, and processing costs in centers), simultaneously. In addition, we developed a heuristic algorithm based on Lagrangian relaxation to solve the proposed MILP model. The performance of the proposed algorithm is evaluated by comparing its results with GAMS results using eight small-sized simulated problems. Furthermore, eight large-size problems are simulated and solved by the proposed algorithm. Finally, the data of an Iranian knowledge-based company is employed to validate the presented mathematical model and algorithm, and the sensitivity analysis process is used to examine the accuracy of the obtained results.

The effect of nomophobic behaviors among nurses on their clinical decision-making perceptions

AimThis study aimed to explore the impact of nomophobic behaviors among hospital nurses on their clinical decision-making perceptions. This understanding can offer insights to enhance the work environment, improve the clinical decision-making ability of nurses and guide medical institutions in the management of related equipment and policy development. BackgroundThe term "nomophobia" refers to the anxiety and fear individuals experience when they cannot use their smartphones or when smartphones are not accessible. Nursing clinical decision-making is a complex process, including a meticulous assessment of the patient's pathological condition and medical history, alongside the application of nursing knowledge and experiential learning rooted in critical thinking. The concept of clinical decision-making perceptions is defined as a deliberate cognitive understanding of one's decision-making processes, which significantly influences the clinical decision-making capabilities of healthcare professionals, thereby impacting the quality of patient care. The factors influencing these clinical decision-making perceptions have been the subject of extensive research. However, there is no Chinese research on the impact of nurses ' nomophobic behaviors on their clinical decision-making perception. DesignA cross-sectional descriptive survey using online-based delivery modes was used. MethodsA descriptive cross-sectional survey design was employed. Using convenience sampling, we surveyed the nurses from a tertiary hospital in Nanjing in May 2023. Data were gathered using a sociodemographic data form, the Nomophobia Questionnaire and the Clinical Decision-Making in Nursing Scale. Techniques including the independent sample t-test, one-way ANOVA, Pearson correlation analysis and linear regression analysis were employed to probe the degree of nomophobia and its effects on their perception of clinical decision-making. Out of 284 questionnaires gathered, 272 were deemed valid, resulting in a 95.8% effective response rate. ResultsThe data revealed that participants exhibited a medium level of nomophobia (54.01 ± 24.09) and clinical decision-making perceptions (144.94 ± 20.08). A robust negative correlation was discerned between nomophobia and clinical decision-making perceptions (r: −0.365, P<0.001). This study highlighted that as the degree of nomophobia intensified, nurses' clinical decision-making perceptions decreased with the increase in nomophobia. ConclusionNomophobic behaviors can hamper nurses' perception of clinical decision-making, potentially leading to inaccuracies or errors. Nurses must use mobile phones judiciously, practice self-regulation and mitigate the disruptive effects of nomophobia on their decision-making. In addition, medical institutions should foster relevant education or craft policies to regularize mobile phone use, augmenting nurses' efficiency and decision-making prowess, enhancing patient care quality, diminishing medical errors and ensuring patient health and safety.

Assessing Special Education Teachers’ School-Related Happiness during Covid-19 Pandemic

Abstract: This research aimed to determine the significant relationship between the profile and the level of happiness of the respondents. It utilized a descriptive correlational method. The respondents were 45 SPED teachers of three identified division in Cebu City, Cebu, Philippines. A teacher’s questionnaire forschool happiness scale was used to describe teachers’ happiness during the COVID-19 pandemic. The level of happiness was categorized into three namely; physical equipment, collaboration and school management. In physical equipment, a three-item questionnaire was used to describe teachers’ happiness with school facilities. For collaboration, eight-item questionnaire. And for school management four-item questionnaire. Overall, there are 15 questions for school happiness scale. The frequency counts, means, percentages and chi-squarewere used to treat the data. For the relationship between the respondents’ profile and their school-related happiness in terms of physical equipment has no significant difference. While for the relationship between the respondents’ profile and their school-related happiness in terms of collaboration has no significant. And for the relationship between the respondents’ profile and their school-related Happiness in terms of school management has no significant difference in terms of their gender and length of service. However, the relationship between the respondents’ profile and their school-related Happiness differed significantly based on their Civil status and academic rank.

컨테이너터미널의 이송장비 자동화(YT·AGV) 경제적 타당성 분석

Purpose - The purpose of this study is to understand the limitations of yard transfer equipment composition through the economic feasibility analysis of yard transfer equipment by examining the transport equipment operation algorithm and work process composition of terminals. Design/Methodology/Approach - Yard Transfer Equipment YT is widely used at domestic and international terminals. The Domestic G terminal is interested in the construction of yard transfer equipment automation. In the study, the actual transport equipment operation algorithm process and work process composition of Gwangyang G Terminal and L Terminal in China were investigated, and economic feasibility was investigated. Findings - As a result of economic feasibility analysis, it was shown that e terminal operated by YT transfer equipment lacked economic feasibility, but the terminal operated by AGV transfer equipment attained economic feasibility. In the case of terminals operated by AGV transfer equipment, the B/C ratio was 1.8, NPV was about 27 billion won, and IRR was 13. Therefore, the terminal operated by AGV transfer equipment has economic feasibility. Research Implications - It is expected that safety accidents, cost reduction, and efficient transfer equipment management will be possible through the economic performance of yard transfer equipment. In addition, an economic feasibility analysis was presented so that terminal managers can decide on efficient investments when deciding to introduce and build yard transfer equipment, and reflect this to actively cope with the automation of yard transfer equipment.