Handling Equipment Research Articles

Prevalence and Risk Factors of Work-Related Musculoskeletal Disorders in Central Sterile Supply Technicians, Nakhon Si Thammarat Province, Thailand

Objective: The study aimed to examine the prevalence of work-related musculoskeletal disorders among central sterile supply technicians (CSSTs) in Nakhon Si Thammarat Province, Thailand, and investigate the risk factors associated with these disorders.Material and Methods: A cross-sectional study was conducted among CSSTs regarding work-related musculoskeletal disorders (WMSDs). Technicians were asked about the presence and severity of disorders throughout the whole body during the sterilization procedure. The survey was distributed to the CSSTs at the central sterilization supply departments (CSSDs) of 32 hospitals in Nakhon Si Thammarat province, Thailand.Results: The prevalence rate of WMSDs in various bodily regions was assessed among technicians at the time of questioning (88.3%), after one week (65.4%), and after one year (59.2%). Various body parts were reported to have developed Musculoskeletal problems, with the lower back being the most frequently reported (88.8%), followed by the upper back (84.9%), and the ankles/feet (38.5%). These MSDs were influenced by age over 30 years (odds ratio [OR] 3.32, 95% confidence interval [CI] 1.59-6.93), work schedule (OR 2.58, 95% CI 1.02-4.96) and the handling of heavy-load equipment (OR 2.56, 95% CI 1.47-10.37) or carts, which significantly increased the risk of developing such illnesses.Conclusion: Many CSSTs from the CSSDs reported WMSDs in various locations on their bodies. Lower back pain was the most common complaint.

Finite Element and Experimental Analysis of Microstructural and Hardness Variations in Plasma Arc Welding of AISI 304 Stainless Steel

AISI 304 is widely regarded as the most common austenitic stainless steel and is utilized in various household and industrial applications, including food handling equipment, machinery components, and heat exchangers. Its popularity stems from its excellent mechanical properties, corrosion resistance, and ease of manufacturing. Given its diverse applications, it is crucial to study the microstructural evolution and mechanical properties of the welded zone, especially considering the potential for weld decay during fusion welding. In this context, two critical thermal-dependent factors for ensuring high-quality welds are grain growth and hardness variation in the heat-affected zone (HAZ) during the welding process. This paper presents an innovative finite element (FE) model developed to analyze the grain growth and hardness reduction that occur in the HAZ during plasma arc welding (PAW) of AISI 304 steel for solid expansion tube (SET) technology. Using the commercial FE software SFTC DEFORM-3D™, a user subroutine was created that integrates a physics-based model with the Hall–Petch (H-P) equation to predict changes in grain size and hardness. This study introduces a comprehensive numerical model, encompassing the user subroutine, heat source fitting, and geometry, which accurately predicts the thermal phenomena associated with grain coarsening and hardness reduction in the HAZ during the welding of austenitic stainless steel. The results from the numerical model, including the customized user routines, show good agreement with experimental data, leading to a maximum error prediction of 10 HV in hardness, 30 µm in grain size, and 10% in HAZ extension.

Evaluating occupational health and safety practices in an airport construction project in Nepal

PurposeThis study examines the implementation and performance of Occupational Health and Safety (OHS) practices in the Pokhara Regional International Airport Project (PRIAP), a key public infrastructure initiative in Nepal. Given airports' significance to Nepal’s economy, particularly for tourism and trade, the research highlights the unique safety challenges in airport construction, addressing gaps in OHS management in developing countries.Design/methodology/approachA case study methodology focused on the PRIAP enabled a thorough analysis of safety practices. Data were gathered using structured questionnaires from various stakeholders. The Cronbach’s alpha and relative importance index (RII) were used to assess response reliability and ranked factors affecting safety performance.FindingsThe study identifies both strengths and weaknesses in the project’s OHS practices. While plant and equipment handling and financial aspects, such as budget allocation for safety measures and accident compensation, were deemed satisfactory, significant deficiencies were found in hazard identification and the investigation of near misses. These results suggest that improvements are needed in proactive safety management, particularly in worker-management communication.Research limitations/implicationsThis study provides valuable insights but is limited by its single-site focus and use of descriptive statistics. Future research should employ advanced statistical methods, like ANOVA, and include multiple construction sites to capture a broader range of OHS challenges. Evaluating the long-term effectiveness of proposed interventions is also essential. Addressing these limitations will enhance the development of comprehensive safety management strategies tailored to the specific needs of construction projects in developing countries.Practical implicationsThis study provides practical recommendations for improving OHS practices in airport construction and similar large-scale projects in developing countries. Enhanced hazard identification and improved communication among stakeholders can help reduce accidents and boost project efficiency.Social implicationsImproving safety regulations and culture can reduce workplace injuries, enhancing workers' well-being and quality of life. This research supports stronger public policies, helping lower economic burdens from accidents, promoting social stability and increasing public trust in regulatory bodies.Originality/valueThis research contributes to the limited literature on OHS in airport construction projects in developing countries, particularly in Nepal. The case study methodology provides a detailed examination of safety practices and offers a framework for improving OHS in similar projects.

The impact and importance of serious games in maritime education: an empirical application

ABSTRACT Gamification and serious gaming have emerged as alternative approaches in learning and decision-making across various domains. In maritime education and the inland waterways sector, where traditional methods may fall short in engaging learners effectively, the development of tailored serious games presents a unique opportunity. This research assesses the educational value of a serious game designed for the maritime industry and inland waterways. The game was developed through a systematic process involving a literature review, stakeholder consultations, and expert input. The methodology included iterative design, user testing, and feedback collection from participants across various sectors. The game features tasks simulating port operations, equipment handling, and inland navigation, followed by quizzes to reinforce learning. Data analysis was performed to evaluate user engagement, knowledge retention, and satisfaction levels. Evaluation results indicate high user engagement, improved knowledge retention, and participant satisfaction. This research underlines the potential of serious games in maritime education, offering innovative solutions to bridge the gap between theoretical knowledge and practical application, thereby maximizing learning outcomes and preparing individuals comprehensively for the challenges of the maritime industry and inland waterways sector.

INTERACTIVE TRAINING OF PERSONNEL ON ELECTRICAL SAFETY ISSUES FOR AN OIL PUMPING COMPANY

The article is devoted to electrical safety issues in the oil industry, where a significant proportion of injuries are associated with personnel errors in the performance of their work functions. In order to reduce personnel errors and, consequently, reduce the level of injuries and accidents associated with the action of the human factor, a simulator has been developed for training employees of an oil pumping enterprise in the safe handling of electrical equipment. The article analyzes modern approaches to training, including traditional methods and the use of simulators that simulate both current work and emergency situations. Practical application of such solutions will improve the competence of workers in electrical safety issues by practicing the skills of performing work in conditions close to real ones, which emphasizes the relevance of developing simulators for the oil industry. The simulator includes the creation of an intuitive interface and integration with training management systems, consisting of two modules covering safety procedures, working with electrical equipment and filling out work permits. In conclusion, areas for further research are outlined, including the development of new modules to improve work efficiency.

Modest Method for Estimating CO2 Emissions from Container Handling Equipment at Ports

The maritime industry is under increasing pressure to reduce CO2 emissions, with the International Maritime Organization (IMO) setting a target to reduce greenhouse gas emissions, including emissions from the port sector, by 40% by 2030. However, accurate and reliable methods for estimating CO2 emissions at container ports, which are significant contributors to maritime emissions, are still lacking. This study aims to address this by evaluating a novel method for estimating CO2 emissions at container ports. The proposed method utilizes the cargo handling equipment movement theory, quantifying both vertical and horizontal movements based on the amount of container handling equipment at the port. The emissions for each piece of equipment are estimated by multiplying the movement quantity by the respective emission factor. To validate the model, a robustness test compares the estimated CO2 emissions with actual energy consumption data from the port. A case study was conducted at a container port with an annual capacity of over 500,000 TEUs and a parallel layout type. The estimated CO2 emissions were approximately 8183 tons per year, with container cranes contributing 56%, rubber-tire gantry cranes contributing 27%, terminal trucks contributing 14%, and reach stackers contributing 3%. The method demonstrated accuracy, with a deviation of less than 1%. This method offers a fast and reliable approach for estimating baseline CO2 emissions at container ports, providing valuable insights for port authorities and policymakers to develop more effective emission-reduction strategies.

Comparative Analysis of Physical and Engineering Properties of New Egyptian Paddy Rice (Giza 183) Adapted to Mitigate Effects of Climate Change

One of the major challenges for crop breeding scientists is climate change. Their task is to develop new crop varieties that can withstand this phenomenon. For this study, a new Egyptian paddy variety called Giza 183, which is designed to adapt to mitigate the effects of climate change, was chosen. We focused on examining the physical and engineering properties of this variety in order to design strategies for storage, handling, transportation, drying, parboiling, and processing equipment in rice mills. The goal was to minimize post-harvest losses during the milling process, thereby maximizing high-quality yields while reducing losses. The physical properties of the rice grains, such as the length, width, and thickness, were measured at an average moisture content of 13.7% ± 0.25% (wet basis). The results reveal that the mean values of length, width, and thickness averaged 7.50 mm, 3.18 mm, and 2.19 mm, respectively. Additionally, the geometric mean diameter, the equivalent mean diameter, surface area, arithmetic mean diameter, and volume were approximately 3.74 mm, 2.38 mm, 37.37 mm2, 4.29 mm, and 28.23 mm3, respectively. The mean of sphericity was 49.9%, and the grain shape (length/width) was 2.19. The true density was measured at 1218.28 kgm−3, while the bulk density was 572.17 kgm−3. The porosity was found to be 53.03%. Furthermore, the milling production rates for brown rice, hull, white rice, and broken rice were determined to be 76.83%, 23.15%, 67.97%, and 17.36%, respectively. The average weight of one thousand grains was 25.49 g. A linear regression model for describing the mass of rough rice grain was investigated. The mass was estimated with the single variable of the grain aspect ratio (width/length) with a determination coefficient of 0.9908. Information gained from the current study will be useful in designing post-harvest processing and storage structures in rice processing industries.

Analysis of Preventive Maintenance on Forklifts and Reach Trucks by Calculating Mean Time Between Failure and Mean Time to Repair at PT. DSV Solutions Indonesia

The aim of this research is to analyze preventive maintenance for material handling equipment, specifically Forklifts and reach trucks, at PT. DSV Solutions Indonesia over a one-year period (January-December 2023). The analysis employs the Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR), and Availability methods. The findings reveal that the Forklift has an MTBF of 35,926 minutes, MTTR of 85 minutes/breakdown, and an availability of 77.83%, while the reach truck has an MTBF of 26,865 minutes, MTTR of 95 minutes/breakdown, and an availability of 90.14%. Based on this analysis, a recommended preventive maintenance schedule is devised, suggesting maintenance every 25 working days for Forklifts and 19 working days for reach trucks. The evaluation of the improvement in preventive maintenance indicates that Forklifts require maintenance 12 times and reach trucks 16 times in a year, resulting in a significant reduction in downtime and repair costs, ultimately enhancing overall operational efficiency. In conclusion, the enhancement of preventive maintenance schedules proves beneficial in increasing the operational uptime of Forklifts and reach trucks within the operational environment over the course of one year.

Robust integrated multi-mode scheduling of flexible loading and unloading operations with maintenance services in a port container terminal

This study proposes an unparalleled integrated scheduling model for simultaneous loading, unloading, and maintenance operations in a port container terminal, wherein several heterogeneous handling equipment serve inbound and outbound vessels. In this regard, a multi-mode loading approach and the possibility of multiple allocations are also considered, wherein outbound vessels can be loaded by containers belonging to inbound vessels or the storage area. In addition, the proposed model covers all cases of equality and inequality in the number of inbound and outbound containers. More importantly, a flexible loading approach based on a class-based stowage plan is considered to better utilize equipment and increase the efficiency of the loading process. Additionally, since the timing of maintenance operations undoubtedly affects scheduling and entails miscellaneous uncertainties, a two-phase data-driven method is presented to estimate robust maintenance operation times. The first phase involves a hybrid machine learning strategy that combines the Savitzky–Golay Filter (SGF), the Takagi–Sugeno–Kang (TSK) fuzzy system, and minibatch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) for the estimation of maintenance operation times. The second phase employs the distributionally robust optimization (DRO) technique that leverages φ-divergence to address the uncertainties associated with the estimated times. Finally, a case study is conducted to demonstrate the effectiveness and applicability of the proposed framework, accompanied by an examination of various simulation experiments. The results obtained indicate that the implementation of a flexible loading strategy can lead to a 24% reduction in the loading time of vessels.

Hygienic Production Practices and Microbiological Quality of Sheep Milk in Ararso District of Jarar Zone, Somali Regional State, Ethiopia

This study was conducted to evaluate the hygienic production practices and microbiological quality of sheep milk in Ararso district of Jarar Zone, Somali Regional State, Ethiopia. A stratified sampling strategy was used to choose 180 households specifically for this investigation. A total of 60 pooled raw sheep milk samples (each containing 200 mL) were collected from the udders and milk handling equipment of selected milk producers in the research area. The samples were examined to determine microbiological quality. The data were gathered via a questionnaire, field observation, key informant interviews, and focus group discussions. The vast majority of respondents in pastoral (86.7%) and agro-pastoral (64.4%) production systems were illiterate. The majority of respondents (70.6%) in the research area cleaned the sheep home (kraal) once every two days. The majority (98.3%) of respondents in the research area milk their sheep in open kraals with no roof or walls. As a consequence, 36.7% of pastoral and agro-pastoral respondents (81.1%) reported cleaning milk vessels on a regular basis. Almost all of the responders in the research area used plastic equipment for milking and handling. The majority of responders in pastoral and agro-pastoralist categories placed barn hygiene first, with indexes of 0.24 and 0.23, respectively. The average total bacterial count (TBC), coiform count (CC) and yeast and mould count (YMC) of raw sheep milk samples were 5.13±0.21, 2.89±0.27, and 0.77±0.21 log10 cfu/mL, respectively. Raw sheep milk samples taken from producers’ milk handling equipment had a substantially higher mean total bacterial count (5.78±0.32 log10 cfu/mL) compared to samples collected from the udder (4.48±0.23 log10 cfu/mL). Milk samples from pastoral and agro-pastoral households had an average coliform count of 3.18 and 2.60 log10 cfu/mL, respectively. The average YMC in milk samples from pastoralists and agro-pastoralists were 0.74 and 0.80 log10 cfu/mL, respectively. In general, pastoralists and agro-pastoralists in the district do not practice hygienic milking and handling. Consequently, the implementation of hygienic milk production and handling practices is essential to enhance the safety and quality of sheep milk in the study area. Additionally, further research should be undertaken to investigate the microbiological aspects and assess the safety and quality parameters of sheep milk in greater detail.

Evolution and development tendencies of material handling machines

The tools used during mobilities are very diverse, but their operation and structure can be traced back to the same basic principles that created the material handling machines during the previous centuries. Today, knowledge of material handling machines has become a basic necessity not only for industrial and service processes, but also for people's everyday lives, since our lives are almost unimaginably filled with different means of transportation, or without using the vehicles that transport and load our daily consumer goods. As in all areas, material handling is becoming more and more modern, and equipment that serves social and economic needs at a high level is used. One of the most defining characteristics of today's consumer society is extremely rapid change, which also affects our devices, so the design of material handling machines is also constantly changing. An important question of competitive service is how to meet rapidly changing needs. In my article, I review the development of material handling equipment, or the most important handling machines used in modern systems. Based on the outlined processes and technical changes, I will try to show where material handling is headed, what trends prevail today or are expected in server systems of the near future.

Impact of COVID-19 pandemic on greenhouse gas and criteria air pollutant emissions from the San Pedro Bay Ports and future policy implications

The Ports of Los Angeles and Long Beach, collectively known as the San Pedro Bay Ports, serve as vital gateways for freight movement in the United States. The COVID-19 pandemic and other influencing factors disrupted freight movement and led to unprecedented cargo surge, vessel congestion, and increased air pollution and greenhouse gas emissions from seaport and connected freight system operations beginning in June 2020. In this study, we conducted the first comprehensive monthly assessment of the excess particulate matter, oxides of nitrogen (NOx), and carbon dioxide (CO2) emissions due to the heightened congestion and freight transport activity from ocean-going vessels (OGVs), trucks, locomotives, and cargo handling equipment (CHE) supporting seaport operations. Excess emissions peaked in October 2021 at 23 tons of NOx per day and 2001 tons of CO2 per day. The strategic queuing system implemented in November 2021 significantly reduced the number of anchored and loitering OGVs and their emissions near the ports, even during continued high cargo throughput until Summer 2022. Looking forward, we analyzed projected emissions benefits of adopted California Air Resources Board regulations requiring cleaner and zero-emission trucks, locomotives, and CHE over the next decade. If a repeated port congestion event were to occur in 2035, NOx emissions from land-based freight transport should be lessened by more than 80%. Our study underscores the potential emissions impacts of disruptions to the freight transport network and the critical need to continue reducing its emissions in California and beyond.

Assessment of Equipment Handling Practices in the Hospitality Industry: A Case Study of Kathmandu’s Key Departments

This study investigates equipment handling practices within the hospitality industry in Kathmandu, focusing on the frequency of use, types of equipment handled, training provided, and safety measures observed. A descriptive research design was employed, utilizing a quantitative survey approach that targeted 125 participants across three key departments: food production, food and beverage service, and housekeeping. Random sampling techniques were applied to conduct in-depth inspections, evaluate staff training, and assess the documentation and maintenance routines. The findings reveal that a significant portion of staff handles equipment daily, with food production equipment being the most commonly used. While training on equipment handling is regularly provided, issues such as the lack of written guidelines, limited access to personal protective equipment (PPE), and infrequent maintenance checks were identified as critical concerns. Additionally, safety protocols, particularly for heavy equipment, and the clarity of operational instructions were found to be inadequate in some cases. The study underscores the importance of consistent training, proper documentation, and the implementation of safety protocols to enhance equipment handling practices in the hospitality sector.

An Immersive VR Training Scenario for Safe Methanol Bunkering in the Maritime Industry

Abstract The maritime industry, pivotal in global commerce, faces critical challenges in mitigating environmental impacts, especially greenhouse gas emissions. The International Maritime Organization (IMO) targets a substantial reduction in emissions by 2050, necessitating innovative approaches to fuel usage. Methanol, recognized for its lower carbon intensity, emerges as a viable alternative fuel. However, its flammability and toxicity introduce complex safety and operational demands. To address these challenges, we have developed a state-of-the-art Virtual Reality (VR) training program specifically for methanol bunkering operations. This training, utilizing Unity 3D and Meta Quest 2, offers a highly interactive and realistic experience. Trainees engage in a comprehensive simulation that covers the entire bunkering process, including safety checks, equipment handling, and emergency response protocols. The VR environment allows for dynamic adjustments by trainers, enhancing the realism and educational value of the scenario. Our program also includes an assessment component that evaluates the trainee’s performance across various metrics such as safety protocol adherence, decision-making, and situational awareness. The anticipated outcome of this VR training initiative is to significantly improve the preparedness of maritime personnel in handling alternative fuels, thereby supporting the industry’s transition towards sustainable practices and contributing to broader environmental protection goals.

Research on the inverse kinematics of heavy-load manipulator and end-effector for fusion reactor

The environment in Tokamak fusion reactor is hostile to remote handling (RH) equipment that maintains in-vessel components. Many maintenance tasks include transferring components, pipe cutting, and welding in the vacuum vessel (VV). To fulfill these maintenance works, a 7- degree-of-freedom (DOF) heavy load manipulator and a 3-DOF end-effector are designed and connected together to form a 10-DOF redundant robot. The inverse kinematics for such a high redundancy robot, considering obstacle avoidance in the complex space of VV, is a challenge. To solve this problem, the Jacobian method is adopted, and a method specially designed for obstacle avoidance of redundant robots working in the VV is integrated to simplify algorithm calculation and improve inverse solution efficiency. The algorithm is applied to solve the inverse kinematics of the redundant robot for the maintenance of the divertor plasma facing components (PFC) in VV. The results show that the inverse kinematics of the redundant robot can be solved quickly with high positioning accuracy. The method can also be used for other fusion reactor maintenance robots with some adjustments. The maintenance efficiency of redundant robot can be improved with the method which can be valuable for the whole remote handling process.

Machine learning-aided risk-based inspection strategy for hydrogen technologies

Although technically challenging, effective, safe, and economical transport is crucial for enabling a widespread rollout of hydrogen technologies. A promising option to transport large amounts of hydrogen lies in employing retrofitted natural gas pipelines. Nevertheless, H2-rich environments tend to degrade pipeline steels, reducing their load-bearing capability and accelerating crack propagation. Regular inspection and maintenance activities can preserve the pipelines’ integrity and guarantee safe operations. The risk-based inspection (RBI) approach is based on estimating the risk for each component item. It focuses most inspection activities on high-risk components to reduce costs while maximizing the plant’s safety and availability. However, the RBI standards do not consider hydrogen-induced degradations and cannot be adopted for industrial equipment operating in H2 environments. This study proposes a novel ad-hoc methodology for the risk-based inspection planning of hydrogen handling equipment. A machine-learning model to predict the fatigue crack growth in gaseous hydrogen environments is developed and integrated with the conventional RBI approach. The proposed methodology is validated on three pipelines transporting hydrogen and natural gas in different concentrations. The results show how similar operating conditions can determine different degradation rates depending on the environment and highlight how hydrogen-enhanced fatigue can reduce the pipelines’ lifetime.

High-Level Feature Fusion Deep Learning Model for Fault Detection in Handling Equipment in Dry Bulk Ports

The flexibility of handling equipment in dry bulk ports is poor, and frequent equipment fault induced by the high-load and high-power working conditions greatly impacts the overall port handling operations, making accurate fault detection play an important role in improving the efficiency and stability of dry bulk port operations. However, as we know, most fault detection methods for port handling equipment depend heavily on monitoring sensor data, which is not applicable in the dry bulk port due to high configuration and maintenance cost, as well as the high false alarm rate of monitoring sensors caused by strong background noise. To solve the problem, this study proposes a High-Level Feature Fusion Deep Learning Model, which uses different deep learning sub-models to extract features of structured and unstructured data. It fuses the extracted feature vectors to achieve fault detection in the handling equipment, establishing the mapping relationship between the fault (e.g., waiting for the pre-loading process, equipment fault, and others) and multi-source heterogeneous operation and maintenance data for the handling equipment, including reclaimers, belt conveyors, dumpers, and ship loaders. To verify the effectiveness of the proposed method, the actual data of a coal port in Northern China is employed as an example. The results show the deep learning model can achieve high prediction accuracy (over 86%) with high efficiency (0.5 s for each sample), which provides decision support for the fault detection in dry bulk port handling equipment.

Kinematic Simulation of Divertor Remote Handling Equipment for DTT

Kinematic Simulation of Divertor Remote Handling Equipment for DTT

인천항 대기오염물질 배출량 산정 및 저감효과 분석

As global awareness of air pollution issues caused by ports increases, international organizations and developed countries are monitoring pollution levels and establishing various eco-friendly policies to reduce emissions. Domestically, the relevant laws were enacted in 2020 to systematically manage the sources of port pollutants in the five major ports. This study aims to estimate the emissions of air pollutants generated by Incheon Port and analyze the effects of major eco-friendly policies such as Emission Control Areas (ECA), Vehicle Speed Reduction (VSR), and Alternative Maritime Power (AMP). For the year 2023, activity data for all ships, cargo handling equipment, and vehicles were collected, applying methodologies from reputable institutions such as the European Environment Agency (EEA) and the Environmental Protection Agency (EPA). According to national guidelines, air pollutants are categorized into eight types: CO, NOx, SOx, TSP, PM10, PM2.5, VOC, and NH3. The analysis revealed that the total emissions of air pollutants from Incheon Port were approximately 6,362 tons, with ships accounting for over 60% of the total emissions. Among the pollutants, NOx was the highest at 4,597.4 tons, followed by CO at 862.4 tons, and TSP at 314.6 tons. Among the ports, emissions were highest at the New Port, followed by the South Port, Inner Port, and North Port. The results of this study provide essential baseline data for monitoring the air pollution levels of Incheon Port and serve as critical evidence for environmental management and policy development. For sustainable future management, it is crucial to secure reliable data and develop a platform that links data collection, analysis, and visualization functions for more systematic operation.

Enhancing Housekeeping Workforce Competency in the Hospitality Industry: A Comprehensive Training Approach

This study examines the influence of comprehensive training programs on the proficiency of housekeeping personnel in the hotel sector. Data were collected through semi-structured interviews, focus group discussions, and participant observations at different hotels using a qualitative study approach. The findings suggest that organized training programs have a substantial impact on improving technical skills, such as proficiency in advanced cleaning procedures and equipment handling, as well as enhancing soft skills, such as effective communication and customer service. The integration of several learning methods, including simulation-based training and virtual reality, was discovered to be extremely successful in involving workers and enhancing the acquisition of skills. Although faced with obstacles such as reluctance to change and limited resources, the use of proactive solutions, such as engaging staff in training development and providing ongoing professional development, effectively addressed these concerns. The results emphasize the need of a comprehensive training strategy that encompasses both technical and soft skills in order to enhance overall service quality and operational efficiency. Suggestions for future practice including consistently refreshing training material, involving personnel in the development process, and overcoming obstacles to implementation in order to maintain increases in housekeeping performance and visitor satisfaction