Equipment Effectiveness Research Articles

Levels of Effectiveness of Water Curtain Equipment Applied When Mitigating Fire Compartment Installation of Logistics Facilities

Mock-up tests and fire simulations were performed to verify the effectiveness of water curtain equipment in mitigating fire compartment installation of logistics facilities. The radiant-heat-blocking effect of the water curtain equipment differed significantly based on the type of drencher head, and a blocking effect was observed. Additionally, the radiant temperature and heat flux were significantly reduced when the installation intervals of the drencher heads of the water curtain equipment were reduced. Therefore, improving the standards related to the water curtain equipment of logistics facilities, e.g., providing drencher head specifications, restricting the sizes of the openings, and narrowing the installation intervals of the drencher heads, is necessary to ensure the fire safety of water curtain equipment.

Integration of lean manufacturing system with novel intuitive fuzzy syncretic lean frame work to improve the overall equipment effectiveness

Lean manufacturing embraces the principle of doing more with less by removing non-value-added activities from manufacturing processes to preserve effectiveness, flexibility, and profitability. Predictive maintenance in production stages are more critical since it involves machines which are prone to failure and a post failure maintenance stagnates the production which creates bottlenecks due to machine failures. Hence in this work a novel intuitive fuzzy syncretic lean frame work has been implemented to incorporate the need of intelligent systems. The framework is divided into phases which employs Fuzzy logic with embedded smart sensors for effective utilization of man machine and materials in order to improve the effectiveness of a production floor. A novel time based forecasting is done in the design phase which implements the lean tool Takt time. The manufacturing phase uses the sensors to determine the predictive maintenance of the machines thereby implementing continuous flow as the lean tool and the inspection phase uses smart sensor system for real time continuous monitoring of the machining process thereby incorporating Poka-yoke as a lean tool. Thus by implementing the framework the overall equipment effectiveness is achieved which helps in achieving continuous flow of products and defect free products in any production firm.

Neural network and layer-wise relevance propagation reveal how ice hockey protective equipment restricts players' motion.

Understanding the athlete's movements and the restrictions incurred by protective equipment is crucial for improving the equipment and subsequently, the athlete's performance. The task of equipment improvement is especially challenging in sports including advanced manoeuvres such as ice hockey and requires a holistic approach guiding the researcher's attention toward the right variables. The purposes of this study were (a) to quantify the effects of protective equipment in ice hockey on player's performance and (b) to identify the restrictions incurred by it. Twenty male hockey players performed four different drills with and without protective equipment while their performance was quantified. A neural network accompanied by layer-wise relevance propagation was applied to the 3D kinematic data to identify variables and time points that were most relevant for the neural network to distinguish between the equipment and no equipment condition, and therefore presumable result from restrictions incurred by the protective equipment. The study indicated that wearing the protective equipment, significantly reduced performance. Further, using the 3D kinematics, an artificial neural network could accurately distinguish between the movements performed with and without the equipment. The variables contributing the most to distinguishing between the equipment conditions were related to the upper extremities and movements in the sagittal plane. The presented methodology consisting of artificial neural networks and layer-wise relevance propagation contributed to insights without prior knowledge of how and to which extent joint angles are affected in complex maneuvers in ice hockey in the presence of protective equipment. It was shown that changes to the equipment should support the flexion movements of the knee and hip and should allow players to keep their upper extremities closer to the torso.

Comparison of desirability function (DF) and overall equipment effectiveness (OEE) with mathematical model for optimization in fruit juice production process

Comparison of desirability function (DF) and overall equipment effectiveness (OEE) with mathematical model for optimization in fruit juice production process

Evaluation of OEE at Lifelong India Using Lean Practices: A Case Study

Today, the industry is facing issues related to nonvalue-added activities (NVA). By integrating lean practices, industries can systematically evaluate and enhance their overall equipment effectiveness (OEE), leading to more efficient and effective production processes. This alignment not only boosts productivity by eliminating nonvalue activities but also contributes to higher quality outputs and reduced operational costs as well. Manufacturers are required to use value-added approaches in their manufacturing management due to the intense rivalry in real-world markets and growing client needs. Through continuous improvement, lean manufacturing (LM) has been demonstrated to be a significant technique for getting rid of nonvalue-added operations in manufacturing organizations. OEE at Lifelong India is assessed using lean tools and techniques, including Pareto analysis, Why–Why analysis, Kaizen concept and evaluation of Kaizen ideas, as well as before-and-after comparison, in order to assess the operational performance of the organization. A questionnaire was designed with data collection in mind, and business professionals in the field were surveyed and contacted personally. This study indicates that widespread implementation of lean principles leads to an increase in OEE of 95.89%, a level of OEE that is unmatched in the industry and ensures flawless output.

Using Overall Equipment Effectiveness as a Driver for Improving the Productivity of Continuous Mining Systems

Using Overall Equipment Effectiveness as a Driver for Improving the Productivity of Continuous Mining Systems

Prediction of Overall Equipment Effectiveness in Assembly Processes Using Machine Learning

Abstract Nowadays, a lot of data is generated in production and also in the domain of assembly, from which different patterns can be extracted using machine learning methods with the support of data mining. With the support of various modern technical and Information Technology (IT) tools, the recording, storage and processing of large amounts of data is now a routine activity. Based on machine learning, efficiency metrics including Overall Equipment Effectiveness (OEE), can be partially predicted, but industrial companies need more accurate and reliable methods. The analyzed algorithms can be used in general for all production units or machines where production data is recorded by Manufacturing Execution System (MES) or other Enterprise Resource Planning (ERP) systems are available. This paper presents and determinates which most used machine learning methods should be combined with each other in order to achieve a better prediction result.

The psychosocial background of dental care avoidance: A qualitative study.

Dental care avoidance affects individuals' oral health status. There is limited literature examining the context of dental avoidance behavior. The aim of the study is to examine attitudes toward dental care services among adults. Overall, 16 patients participated in semi-structured interviews. The interviews were analyzed using inductive thematic analysis. Through independent reviews of the themes that comprise the patients' experience, a consensus was established among the researchers. Ten major themes were identified that encapsulate patients' attitudes toward dental care attendance: Effect of environment and equipment, Fear and anesthesia, Procrastination, Dissatisfaction with the dental care system, Expectations of dentists, Quality of dental care, Edentulousness and social status, Financial involvement, Aesthetics, and Dentists' behavior. Compliance with oral health maintenance can be enhanced by specific training for professionals and dentistry students and by fine tuning the dental care system. This is the first comprehensive study in Hungary investigating attitudes among dentist patients toward dental care. The results suggest that there are many factors that may affect dental care attendance. Thus, these findings make a potentially fundamental contribution to the improvement of dental care and support practitioners in enriching their understanding of dental avoidance behavior.

Implementation of a performance management system for environmental sustainability in an industrial organization

Abstract The paper explores the implementation of process performance management systems in the automotive industry, specifically focusing on improving the assembly line of an organization within this sector thanks to the introduction of cobots in the line of manufacturing electronic modules used in car seat control systems. With an emphasis on environmental sustainability and circular economy (CE) concepts, the study investigates the positive effects of optimizing mechanical and electromechanical systems within the assembly line. Leveraging concepts such as KAIZEN and Gemba Kaizen, along with the guiding principles of Just-In-Time (JIT), Continuous Improvement and Automation with a Human Touch (JIDOKA), the research aims to elucidate the potential benefits of such enhancements. Key performance indicators (KPIs) including Overall Equipment Effectiveness (OEE), First Pass Yield (FPY), and scrap rates were considered. Rejects, primarily stemming from human error in part handling, emerged as the major challenge facing this assembly line. To address this issue, collaborative robots were introduced to automate part handling, replacing manual processes with precise and reliable automation. Before the implementation, the cycle time stood at 13.6 units, which was reduced to 12.5 units post-implementation, resulting in a significant increase in productivity equating to 3000 more parts produced per week. OEE increasing from 80% to 87.74%, FPY rising from 96.42% to 98.48%, and the scrap rate decreasing from 0.06% to 0.02%. By addressing inefficiencies at the assembly line level, organizations can achieve significant improvements in performance metrics while concurrently contributing to a greener and more sustainable future.

PRODUKTIVITAS ALAT BERAT PADA PEMBANGUNAN PROYEK IRIGASI RENTANG LSS-07 DI RAMBATAN WETAN KABUPATEN INDRAMAYU

The selection of heavy equipment affects the efficiency and profitability of construction work. The level of effectiveness of heavy equipment is assessed based on the productivity of the equipment. Productivity is the result of dividing output by input. The selection of heavy equipment is something important and must be considered so that its use is efficient and effective because it will affect the productivity of the machine. In the Rentang irrigation network construction project, there are several jobs that use heavy equipment such as piling and excavation work. The heavy equipment chosen must be right so that the project or work runs smoothly. The purpose of this study was to determine the productivity of heavy equipment, volume, number of heavy equipment and the time and cost of implementing heavy equipment. This study is limited to the problem of heavy equipment productivity, volume and time and cost of using heavy equipment. The heavy equipment used in the Rentang irrigation construction in Rambatan Wetan, Indramayu Regency is the PC 200 Excavator, the Sany SY215C Mini Excavator, and the Dump Truck. The productivity of the literature excavation excavator is 344 m3/hour, while the field data excavation is 377.68 m3/hour, the literature excavation dump truck according to the location of the dump truck work in Rambatan Wetan Village, Sindang District is 133.64 m3/hour.

PENGUJIAN ALAT DESTILASI MINYAK SEREH DENGAN KAPASITAS 10 KG

Testing of a 10 kg capacity lemongrass oil distillation apparatus was carried out to evaluate the performance and efficiency of the distillation process. This study includes setting main parameters such as distillation temperature, process time, and type of raw material used. The main goal is to ensure that the distillation equipment can produce lemongrass oil with optimal quality according to its capacity. The testing method involves measuring the distillation results in terms of citronella oil yield and chemical composition. This analysis provides in-depth insight into the effectiveness of distillation equipment in maintaining the quality of the lemongrass oil produced. The test results show that setting the temperature and distillation time has a significant effect on the final result, with certain conditions producing better quality lemongrass oil. The implication of this research is the importance of an in- depth understanding of operational parameters in the distillation process to maximize the production of consistently high quality lemongrass oil.

Analysis of the mining equipment replacement time. A case study focused on drilling rig

Mining equipment is subjected to degradation throughout its operation lifetime, being the definition of the replacement time for mining equipment a vital question. Requiring accurate information about the performance of the equipment to identify the optimal replacement time. This study determines the replacement time using an improved method, Overall Mining Equipment Effectiveness (OMEE), that analyses the technical factors from mining equipment performance in real-time, such as the technical availability rate, the mechanical availability rate, the production rate and the productivity index. The suitability of the method has been tested using a real open pit mine and information gathered from six drilling rigs, which have been performing around 27,000 engine hours each, over the last twelve years. The results obtained show that the OMME methodology is reliable to analyse the mining equipment performance and determine the technical replacement time.

Reducing Downtime Loss in the Automotive Parts Stamping Process Using Why-Why Analysis: A Case Study.

This research aims to reduce downtime in the production process of automotive part stamping and to enhance the overall efficiency of the machinery, the case study focuses on an 800-ton stamping press in a factory. Data were collected by analyzing the overall equipment efficiency (OEE) using the developed program named Thingworx and observing employees' operations from October to December 2022. The results showed that the OEE was below the target value set by the factory. Most problems occurred during mode change activities with waste investigation such as overprocessing and waiting. It was found that the main factors impacting downtime during the production process are issues from mold changeovers, problems with metal scraps stuck in the machinery, and mold repair issues. Why-Why analysis technique and lean tools including SMED, visual control, and continuous improvement, were used to decrease time spent on non-value added activities. The results from the research showed that the average time for mold changeovers decreased from 8.77 minutes to 3.51 minutes, a reduction of 60.22%. The average time for removing metal scraps decreased from 4.72 minutes to 0.81 minutes, a reduction of 82.76%. Additionally, the time for mold repairs decreased from 1,404 minutes to 448 minutes, a reduction of 68.09%. These improvements led to an overall equipment effectiveness of the 800-ton stamping press increasing from 55.85% to 65.65%, representing a 9.8 percentage point increase. Furthermore, it enabled a reduction in production downtime costs by 298,025 baht per month.

Collaborative Optimization of a Matrix Manufacturing System Based on Overall Equipment Effectiveness

When several traditional flow-shop lines operate in parallel, the operation mode with no communication between production lines will no longer be the optimal production paradigm. This paper describes matrix manufacturing systems (MMS) in a general manner from the perspective of related works, comparing different manufacturing organizational forms and their characteristics. Subsequently, MMS are extracted during the parallel production of multiple surface mount technology (SMT) lines. An overall equipment effectiveness (OEE) online calculation model and a collaborative optimization method are proposed based on the OEE of the MMS. The innovative idea of this study is to divide existing multiple parallel SMT lines into MMS. The efficiency of each matrix unit (MU) was calculated, and a collaborative optimization method was proposed based on an indicator (OEE). In this paper, an example of eight SMT lines is presented. The partitioning of MUs, OEE calculation of each MU, and the low OEE unit collaborative optimization method are described in detail. Through a case study, the architecture of the collaborative optimization model for the MMS was constructed and discussed. Finally, the improvement in the OEE proved the effectiveness and usability of the proposed architecture.

Methodology of Shipboard Spare Parts Requirements Based on Whole Part Repair Strategy

This paper introduces an assessment method for shipboard spare parts requirements based on a whole-part repair strategy, aimed at enhancing the availability and combat effectiveness of naval equipment. Addressing the shortcomings of traditional repair strategies, this study innovatively adopts a whole-part rotation repair approach to reduce repair times and improve the rapid response capability of equipment. An evaluation model for support probability and fill rate is established, and Monte Carlo simulation techniques are applied to simulate the impact of different maintenance strategies on spare parts demand and equipment availability. This study also conducts a sensitivity analysis of key parameters, including Mean Time Between Failures (MTBF), repair demand probability, and faulty part repair cycle, to assess their influence on spare parts requirements and equipment availability. The results indicate that the whole-part repair strategy can effectively reduce spare parts demand and enhance equipment availability. In conclusion, the whole-part repair strategy demonstrates a distinct advantage in shipboard spare parts management, optimizing inventory management while ensuring combat readiness. This research provides a novel analytical approach for naval logistics and maintenance planning.

Development and Application of Digital Twin Control in Flexible Manufacturing Systems

Flexible manufacturing systems (FMS) are highly adaptable production systems capable of producing a wide range of products in varying quantities. While this flexibility caters to evolving market demands, it also introduces complex scheduling and control challenges, making it difficult to optimize productivity, quality, and energy efficiency. This paper explores the application of digital twin technology to tackle these challenges and enhance FMS optimization and control. A digital twin, constructed by integrating simulation models, data acquisition, and machine learning algorithms, was employed to replicate the behavior of a real-world FMS. This digital twin enabled real-time dynamic optimization and adaptive control of manufacturing operations, facilitating informed decision making and proactive adjustments to optimize resource utilization and process efficiency. Computational experiments were conducted to evaluate the digital twin implementation on an FMS equipped with robotic material handling, CNC machines, and automated inspection. Results demonstrated that the digital twin significantly improved FMS performance. Productivity was enhanced by 14.53% compared to conventional methods, energy consumption was reduced by 13.9%, and quality was increased by 15.8% through intelligent machine coordination. The dynamic optimization and closed-loop control capabilities of the digital twin significantly improved overall equipment effectiveness. This research highlights the transformative potential of digital twins in smart manufacturing systems, paving the way for enhanced productivity, energy efficiency, and defect reduction. The digital twin paradigm offers valuable capabilities in modeling, prediction, optimization, and control, laying the foundation for next-generation FMS.

Optimizing Quality Control on Electric Vehicle Production Lines with AI and Machine Learning

The study explores the use of AI and ML technologies to optimize quality control in EV production lines. By applying neural networks and machine learning algorithms, the research achieved significant improvements: a 74.4% reduction in torque deviation, a 75.9% enhancement in speed consistency, and a 70.8% decrease in defect rates. These gains also resulted in a 16.0% reduction in production cycle time and a 50.0% decrease in downtime, leading to an 8.4% increase in Overall Equipment Effectiveness (OEE). The methods employed included AI-driven predictive maintenance, real-time monitoring, and statistical process control (SPC). Despite the clear benefits, challenges such as integrating these technologies with existing systems and ensuring robust data infrastructure remain. Future research should focus on refining these approaches and extending their application across the automotive industry.

Analisis Produktivitas pada Mesin BM 206 D-2 Menggunakan Metode Total Productive Maintenanace (TPM) dengan Pendekatan Overall Equipment Efectiveness (OEE) di PT. Berlina Tbk

Productivity is key to success in the manufacturing industry, particularly at PT.BERLINA Tbk, which specializes in plastic packaging manufacturing. This study focuses on enhancing the operational effectiveness of the BM 206 D-2 machine trough the implementation of Total Productive Maintenance (TPM) and measurement of Overall Equipment Effectiveness (OEE) as well as the identification and mitigation of Six Big Losses. The research involves two sampling periods, each spanning two quarters. During the first period, the average OEE value of 66% indicated that the greatest losses were due to machine breakdown or Breakwon Losses, related to deficiencies in operator and technician skills, inadequate planes maintenance, and machine cleanliness. Following the implementation of improvements based on these findings, the average OEE incrased to 71% in the second period. These results underscore the importance of enhancing technical skills, effective maintenance, and strict cleanliness to improve productivity and reduce production losses.

Experimental study on temperature distribution of double-layer solid cylinder under local heating source

Abstract Heating equipment is widely used in production and life, the transient temperature of the heated object reflects the effect of heating equipment, but also an important basis for the design of heating equipment. In the internal temperature measurement of micro heating equipment, some of the temperature measurement instruments are large in size, which makes it difficult to realize precision measurement, and the use of infrared measurement, laser temperature measurement and other methods cannot be used to accurately measure the temperature of the internal points of the material without destroying the material and equipment at the same time. In this study, based on the thermocouple temperature measurement technology and considering the problem of fragility and breakage caused by the small diameter of very fine thermocouple wires, a multi-point temperature synchronization measurement platform is constructed to realize the precise measurement of the temperature at multiple points inside the micro-heating element. Transient temperatures were measured at different locations of a water-containing porous medium inside a 15 mm long heating element under static heating and dynamic suction conditions in the case study. The results show that moisture and suction have a significant effect on the temperature inside the porous media layer. During the suction process, the temperature drop near the suction opening was larger, and the temperature drop near the wall was about 47% of the temperature drop inside. This study is a guide to the design of heating structures for vacuum drying equipment, electrically heated atomization systems and other micro-miniature heating equipment.

The Influence of the Assembly Line Configuration and Reliability Parameter Symmetry on the Key Performance Indicators

In the context of the demand for mass customization of products, a trade-off between highly efficient automated systems and flexible manual operators is sought. The linear arrangement of workstations made it possible to divide the process into many simple operations, which increases production efficiency, but also results in an increase in the number of workstations and a significant extension of the line. A human operator is usually treated as a quasi-mechanical object, and a human error is considered, similarly, as a failure of a technical component. However, human behavior is more complex and difficult to predict. A mathematical model of a new production organization is presented, including dividing the traditional production line into shorter sections or replacing the serial assembly line with a U-line with cells. Moreover, the reliability of operator and technical means are distinguished. Work-in-progress inventories are located between line sections to improve system stability. The stability of the assembly line is examined based on the system configuration and probabilistic estimates of human failure. The influence of the symmetry of reliability parameters of people on key performance indicators (KPI (headcount), KPI (surface) and KPI (Overall Equipment Effectiveness) is examined. KPI (solution robustness) and KPI (quality robustness) are also presented in order to evaluate the impact of a disruption on the assembly line performance. New rules for assigning tasks to stations are proposed, taking into account the risk of disruptions in the execution of tasks. For comparison of assembly problems, heuristic methods with newly developed criteria are used. The results show the impact of symmetry/asymmetry on assembly line performance and an asymmetric distribution of manual assembly times that is significantly skewed to the right due to human errors. On the assembly line, the effects of these errors are cumulative and lead to longer assembly times and lower KPIs.