Equipment Effectiveness Research Articles

A System Dynamics Stability Model for Discrete Production Ramp-Up

Manufacturing companies are increasingly challenged to deliver customizable products with shorter time to market and higher quality while adhering to sustainability requirements. To meet these challenges, the frequency and importance of production ramp-ups will increase in the future. However, most ramp-ups still fail to meet targets due to unpredictable equipment failures, operator errors, and system complexity. We propose a system dynamics model that captures the unique dynamics of ramp-up phases by integrating stability and disturbance factors that influence the key performance indicators overall equipment effectiveness, process capability, and production output. A systematic literature review informed the identification of stability factors, which were validated through expert interviews in the automotive industry. Our system dynamic simulation results indicate that control factors realistically influence production system behaviour during different ramp-up phases. Despite some limitations regarding the effects of maintenance personnel and engineering changes on key performance indicators, our model effectively simulates realistic ramp-up behaviour. The findings highlight the need for tailored models that consider specific ramp-up contexts and emphasize the importance of data acquisition for enhanced performance prognosis in future research.

Optimal Design of the Hole Shape of the Air Suction Porous Turntable and Analysis of Adsorption Characteristics of Flexible Blades

ABSTRACTTo improve the adsorption effect of air suction sorting equipment, in this study, flexible blades were used as test materials, and porous turntables with circular holes (A), rectangular holes (B), and rectangular‐circular holes (C) were designed. Fluent software was used to simulate and analyze the aerodynamic characteristics of the flow field at the porous turntable, and the blade falling adsorption bench test was built. Under the same test conditions, the adsorption blades of the porous turntable were photographed by a high‐speed camera. Based on the C‐hole turntable and the tuyere air pressure of 380 Pa, it is verified by a single‐factor test that the blade falling in the distance of the porous turntable, the rotating speed of the turntable, and the number of blades extending perpendicular to the direction of movement have a direct effect on the blade adsorption of the porous turntable. To obtain the optimum adsorption conditions for the bench test, an orthogonal test was used, and a certain number of leaves were used for the test while the adsorption efficiency was considered; it is found that when the distance from the porous turntable is 40 mm, the rotation speed of the turntable is 60 r/min and the number of transverse blades of the conveyor belt is 4, and 100% adsorption can be achieved. In summary, the research results and methods of this experiment can provide reference and guidance for the research group to carry out the follow‐up research and development of multi‐stage air suction sorting equipment.

ESTIMATION OF LOADING AND HAULING EQUIPMENT PRODUCTION AT PT. BAGUS JAYA ABADI, SORONG CITY, SOUTHWEST PAPUA PROVINCE

Bagus Jaya Abadi is a mining company located in Sorong City, Southwest Papua Province that uses quarry mining to extract andesite rock. The effectiveness of production equipment, such as excavators and dump trucks, is essential to meet production targets. However, operational challenges and weather conditions often hinder the achievement of these targets. This study aims to calculate the daily production rates of Caterpillar 320D and Komatsu PC 200 excavators when loading Hino 300 and Hino 260 dump trucks and evaluate the work efficiency of these machines. Results indicate that daily production rates for different equipment combinations vary between 145.36 m³/day and 221.93 m³/day, depending on the pairing of machinery. These findings provide a foundation for the company to improve production efficiency and develop strategies to address existing challenges.

Tactical Activities to Improve the Effectiveness of Concrete Batching Plant Based on Overall Equipment Effectiveness Analysis

The growth of infrastructure projects has led to an increased demand for ready-mix concrete. A company that produces ready-mix concrete using a batching plant encountered difficulties in fulfilling customer orders due to the high rate of machine downtime. Overall equipment effectiveness (OEE) was employed to examine these issues at the tactical activities, where the root causes of losses that occur in the OEE components of availability, performance, and quality were addressed. The OEE analysis was extended to encompass maintenance effectiveness measures, as the anticipated solution to the problem was not the replacement of the machine, but rather an enhancement of its operational efficacy. The effectiveness of maintenance activities was measured using MTTF (mean time to failure), MTTR (mean time to repair), and MTBF (mean time between failure). A review of the OEE components revealed a necessity to reduce losses, as evidenced by the availability and performance rates. Although the performance rate has the lowest value, based on the frequent occurrence of failures to the availability component, the improvement process was carried out to overcome problems in the availability variable. The implementation of scheduled maintenance at the beginning of each month and the implementation of daily checks before and after the machine was used resulted in an increase in the OEE value from 56.62% to 71.15%. The incorporation of maintenance analysis into OEE has been shown to result in increased OEE values, as evidenced by a longer mean time between failures, a reduced time for process adjustments, and a decreased asset repair time.

Overall Prompting Effectiveness for Optimising Human-Machine Interaction in Cyber-Physical Systems

This paper presents the Overall Prompting Effectiveness (OPE) framework, designed to enhance interactions with systems employing generative AI(genAI) through prompt engineering. Leveraging principles from Total Productive Maintenance (TPM): Overall Equipment Effectiveness (OEE), the OPE framework provides a systematic tool for iterative refinement of prompts, crucial for optimising human-AI interactions in cyber-physical-social-human systems. Evaluating prompting results in three actionable categories: Availability, Performance, and Quality, OPE aims to generate more accurate, relevant, and effective AI responses. Preliminary applications and workshops with prompt engineers underscore the potential of OPE to significantly improve the efficiency and effectiveness of AI engagements. The integration of OPE within Large Language Models (LLMs) or other genAI systems promises to expand automation capabilities, enhancing the intellectualisation and personalisation of CPS. This framework fosters continuous improvement in prompt quality and contributes to the synthetic knowledge management and smart reasoning mechanisms essential for advanced CPS. Our findings suggest that OPE could play a significant role in cognitive engineering, offering a novel methodology for enhancing decision-making and problem-solving in intelligent systems. This aligns with the current research directions in CPS, emphasising the need for tools supporting technology's socialisation and personalisation in complex integrated environments.

Industrial Internet of Things Enabled Kata Methodology of Assembly Line Productivity Improvement: Insights from a Case Study

Lean manufacturing focuses on perfection, trying to eliminate all types of Muda (waste), Mura (inconsistency), Muri (overburden), defects, injuries, and accidents through a continuous improvement process. Assembly lines are the final stages of manufacturing before the product is delivered to customers. Kata methodology provides a practical approach to achieving perfection in assembly lines, but its effectiveness is often hindered by delays in data collection, analysis, and diagnostics. In this study, we address these challenges by leveraging industrial internet of things (IIoT) solutions in an industrial setting. The research question of this paper is as follows: “Why was the full potential of traditional Kata to achieve assembly line perfection not realized, and will IIoT-integrated Kata address the limitations of the traditional Kata?” We demonstrate the integration of IIoT and Kata methodology in a factory assembling automobile heating, ventilation, and air conditioning (HVAC) systems to enhance assembly line productivity. We observe that the integration of IIoT with Kata methodology not only addresses existing limitations but drives substantial gains in assembly line performance. We validate improvements in both productivity and efficiency through quantitative and qualitative outcomes. We underscore the pivotal role of real-time data for Kata’s effectiveness, discuss the process for digital transformation, and explain the need for data monetization. We recommend the development of an IIoT-savvy workforce, traceability of 4M (men, method, materials, and machine), and present the task scorecards and dashboards for real-time monitoring and decision-making. We highlight the positive impact of IIoT-enabled traceability on overall equipment effectiveness (OEE). The company reduced its workforce from 15 to 13 operators, increased OEE from 75% to 85%, and improved average throughput from 60 to 90 assemblies per hour. The time for traceability of 4M (men, machines, material, and method) was reduced from hours to minutes. The factory eliminated 350 paper documents to achieve a paperless shop floor. This real-world case study serves as a model for companies looking to transition from traditional continuous improvement processes to IIoT-supported lean manufacturing.

Development of an offshore ground motion prediction equation for peak ground acceleration considering path effects based on S-net data

Ground motion prediction equations (GMPEs) in offshore regions are important not only for earthquake early warning systems and strong motion prediction but also for evaluating the durability of subsea structures and tsunami risks associated with seafloor slope failures. Since soil conditions and propagation paths differ between onshore and offshore areas, it is desirable to develop a GMPE specific to the seafloor. Previous GMPE models have some problems, such as being influenced by buried observation equipment and path effects. In this study, to predict the distribution of seafloor seismic acceleration, we developed a new GMPE regressed on the peak ground acceleration (PGA) data of S-net using minimum necessary seismic parameters as explanatory variables. Residual analysis using the conventional GMPE emphasized the path effects through the offshore area, which were corrected by the depth up to the plate boundary. The new model successfully predicted PGA with smaller errors compared to conventional onshore and offshore GMPEs. The residuals between the observed and predicted PGAs were used to examine the factors responsible for the effects of the S-net site conditions. The new GMPE can predict PGAs within 300 km of the epicenter from the moment magnitude (Mw 5.4–7.4), focal depth, earthquake type, and source distance. In this model, the distance attenuation coefficient is smaller than in conventional models, and consequently, the PGAs along the trench axis that are amplified due to path effects can be reproduced. This means that PGAs will be unexpectedly larger than those estimated by conventional GMPEs even far from the hypocenter. Our model improves the accuracy of PGA prediction and avoids underestimation in assessing seafloor slope failure and earthquake resistance near the trench.Graphical abstract

High-resolution optical image reconstruction based on adaptive sparse dictionary

Image spatial resolution reflects the ability of an optical system to capture detailed information about an object. Compared to Low-resolution (LR) images, High-resolution (HR) images contain greater pixel density and textural detail. In the experiments, it is difficult to obtain ideal HR images due to the effects of acquisition equipment and image degradation. To address the problems, this paper proposes a HR optical image reconstruction method based on adaptive sparse dictionary. The experimental show that the area of the modulation transfer function (MTF) curve of the reconstructed image is improved by 16.41%, which represents the increase in the frequency components it contains. Meanwhile the cut-off resolution is improved from 0.2692cy/pix to 0.4018cy/pix. The method in paper achieves good results in both reconstruction efficiency and accuracy. The peak signal-to-noise ratio (PSNR) of the reconstructed image is improved from 20.1650 to 28.0192. The feature similarity (FSIM) and detail retention are above 90%.

Operational Adaptability Improvement of High-Speed Trains Through Multi-Objective Control on Carbody Lateral Vibration

To improve the operational adaptability of high-speed trains, a control method is proposed to mitigate carbody lateral vibration by leveraging the dynamic vibration absorption effect of multi-suspended equipment. A comprehensive analysis of five typical wheel/rail contact relationships, closely related to vehicle operational status in the long-term service, is conducted and incorporated into the established rigid-flexible coupling dynamic model. Based on the proposed improved niche genetic algorithm (INGA), an objective function, which holistically assesses the vibration of the carbody and suspended equipment, is constructed to undertake the optimization analysis. The results show that the dynamic vibration absorption effect of the suspended equipment proves effective in controlling carbody lateral vibration, thereby enhancing operational adaptability. However, the improvement in vehicle performance varies under different operating conditions, influenced by the competitive relationship between multiple control objectives. While carbody lateral vibration performance could be further improved without considering equipment vibration tolerance, such improvements are limited, indicating that it is reasonable and necessary to consider equipment vibration tolerance in the research of carbody vibration control. This study furnishes valuable insights for improving the adaptability of high-speed train operations and provides ideas for further research on carbody vibration control using the suspended equipment.

Preliminary study on the impact of 900 MHz radiation on human sperm: An in vitro molecular approach

The use of technologies that produce and emit electromagnetic fields (EMF) is growing exponentially worldwide. The biological effects of EMF-emitting equipment, such as mobile phones and other wireless devices, have been studied in the last decade using in vitro and in vivo methods. Infertility is a growing health problem, and nearly half of cases are because of male-factor. This study investigated the direct in vitro effects of 900 MHz radiation exposure on sperm parameters, genetic status, apoptotic markers, and the PI3K/AKT signaling pathway in healthy normozoospermic men. Semen samples were divided into four groups, two control (30 min and 1 h) and two EMF exposure (30 min and 1 h). Sperm parameters (motility, progressive motility, acrosomal index, morphology), genetic status (DNA fragmentation and chromatin integrity), apoptotic markers (cytokine-c and caspase-3 expression) and the PI3K/AKT signaling pathway (phosphoinoitide 3-kinase-PI3K- and phosphorylated AKT- p-AKT-) were analysed. Sperm motility were significantly reduced in 30 min EMF exposure while a significant increase in the expression of p-AKT were observed in 1 h EMF exposure group. An increased vacuolisation, acrosomal defect, extension of subacrosomal space, uncondensed chromatin structure, apoptotic signs and disrupted axoneme were observed in both EMF groups which were not observed in the control group. Other sperm parameters (morphology and acrosomal index), genetic status, apoptotic markers and the PI3K expression rates had no significant change.

Evaluation of the effect of artificial intelligence training equipment in physical training of table tennis players from a biomechanical perspective

In table tennis competitions, the movement data of table tennis players plays an important role in daily training. In recent years, artificial intelligence technology has been widely used in sports competitions. With the development of artificial intelligence, how to use artificial intelligence to analyze sports video to obtain sports data of athletes has become more and more important. This paper is to use artificial intelligence to research and analyze the athletes in the table tennis competition, and then obtain the sports data of the athletes. This has important guiding significance for athletes and coaches in their daily training. Table tennis is a widely developed sport in China, and as China’s “national ball”, table tennis has always been in a leading position in the world table tennis competitions. It is widely loved by the public for its simple and easy access to sports facilities, low site requirements and sports methods. In this study, mathematical statistics and experimental methods were used. Combined with the application of the functional sports screen function test, 20 table tennis players from Shandong Sport University were selected as the test objects, and their sports performance was tested. The total score of 10 first-level athletes was 162 points, and the average score was 16.2 points. The total score of the 10 second-level athletes was 144 points, and the average score was 14.4 points. The performance of the first-level athletes was significantly higher than that of the second-level athletes. It showed that the first-level athletes were generally better than the second-level athletes in all aspects.

Perbaikan Nilai Overall Equipment Effectiveness dengan Metode Total Productive Maintenance pada PT. Electric Vehicle Trimotorindo

This research was conducted to increase the Overall Equipment Effectiveness (OEE) value at PT Electric Vehicle Trimotorindo, which is an electric vehicle manufacturing company. The main problem faced by the company is the decline in OEE value every month due to lack of machine maintenance and deterioration in production quality. The method used in this study is Total Productive Maintenance (TPM), which involves identifying the factors that cause production losses through the analysis of Six Big Losses. The results show that the OEE value has increased from 78.61% to 80.36% after improvements through TPM, especially in increasing the quality rate from 88.48% to 92.23%. The conclusion of this study is that the application of TPM can improve the effectiveness of machine use and production quality, which ultimately contributes to the improvement of the company's productivity.

The Effect of Lean Manufacturing on Production / Operation for the Small and Medium Enterprise in Malaysia

At the start of 2022, the government announced its focus on supporting the development of small and medium enterprises (SMEs) to improve living standards following the COVID-19 pandemic. SMEs contribute significantly to the national economy, with the clothing industry playing a major role. This research applies lean manufacturing techniques to enhance the performance of SMEs in the clothing sector, specifically in T-shirt printing. Therefore the first objective was to collect, analyze processing times and recording of all issues encountered during production. The second objective involved using value stream mapping (VSM) to analyze the T-shirt printing process from raw material supply to finished product packaging. We also employed a why-why analysis to pinpoint the underlying causes of inefficiencies and devise specific solutions. The last objective focused on process improvement using VSM, along with the Kanban system, 5S and Make to Stock (MTS) to optimize block preparation and T-shirt printing. We selected Flexsilk Printshop as the case study. The findings showed a 66.59 % reduction in waiting time, a 30.77 % improvement in lead time, an increase in overall equipment effectiveness (OEE) from 93.3 to 97.45 % and a 50.41 % increase in efficiency.

A Comparative Evaluation Of Efficacy Between Besdata, Ambu Ascope, And Macintosh Laryngoscope For Intubation In Adult General Surgical Patients

Background: In the context of general surgical operations, patient safety and procedure success are directly tied to the effectiveness of endotracheal intubation equipment. The comparative effectiveness of these devices in actual clinical situations is essential, notwithstanding the many technical breakthroughs that have been made. Objective: The purpose of this research was to compare the performance of three different intubation devices— the Besdata, the Ambu aScope, and the Macintosh Laryngoscope—in adult patients undergoing general surgical procedures. Methods: Between 2019 and 2022, researchers from Jawaharlal Nehru Medical College of AMU in Aligarh's Department of Anaesthesiology and Critical Care gathered data. Ninety patients were recruited, ranging in age from 20 to 70 years and in weight from 40 to 70 kg. After getting participants' consent, they were split into three groups at random. The Ambu aScope was used to intubate patients in Group A, the Besdata was used in Group B, and the Macintosh laryngoscope was used in Group M. Age, gender, height, and weight were recorded, as well as the participant's Mallampati status. Results: There was universal success with intubation using all three devices. Average intubation times were found to be quickest using the Ambu aScope, then the Besdata, and finally the Macintosh Laryngoscope. The incidence of postoperative sore throat was lowest in patients intubated using the Macintosh Laryngoscope and greatest in those intubated with the Besdata. Ambu aScope had the best percentage of success on the first attempt. There were no statistically significant variations between patients in terms of demographic information or Mallampati grade. Conclusion: While each of the three tools was useful, it also had its own set of advantages and disadvantages. It is important to consider the patient's anatomy, the clinician's level of expertise, and the clinical setting before settling on an intubation device.

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.

Otomatisasi Perhitungan OEE pada Mesin Filling ILAPAK 50g Menggunakan PLC dan HMI

This study addressed the limitations in calculating Overall Equipment Effectiveness (OEE) manually, which frequently led to inaccuracies and inefficiencies in industrial processes. The purpose of this research was to design an automated OEE calculation system for the ILAPAK 50g filling machine to improve data accuracy and reduce dependency on manual input. A Design Science Research (DSR) methodology was employed, involving stages of system analysis, design, implementation, and evaluation. The system utilized key components, including an Omron CP2E PLC, proximity sensors, relays, and a Human-Machine Interface (HMI) for real-time data acquisition. The findings indicated that the automated system significantly improved data accuracy, achieving reliable, continuous OEE calculations across different machine shifts. The system successfully replaced manual logbook methods, reducing human estimation errors, and displayed OEE data locally on the HMI, making it accessible for operational decisions. Furthermore, the implemented automation reduced overall downtime, enhanced machine availability, and minimized errors associated with manual record-keeping. This research has practical implications for industries aiming to optimize production efficiency. The automated OEE system demonstrated potential for scalability to other machines in manufacturing settings, highlighting its adaptability and utility in modern industrial environments. Future research could explore integration with cloud-based databases to enhance data storage and accessibility, providing a foundation for advanced predictive maintenance and performance monitoring across multiple machines.

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.

Penerapan Metode Total Productive Maintenance Dengan Overall Equipment Effectiveness (OEE) Pada Mesin Grinding di PT. VPRK

This research focuses on analyzing the implementation “of Total Productive Maintenance (TPM)” at PT. VPRK “by” utilizing “Overall Equipment Effectiveness (OEE) as an indicator” to assess “the” performance of grinding machines at PT. VPRK. The aim of the research is to evaluate the effectiveness and efficiency of the machine by identifying inhibiting factors that influence the performance of the grinding machine. The TPM method is applied to increase availability, quality and overall machine performance. OEE is used as a critical measuring tool to assess productivity and operational efficiency. The research results show that the OEE value of grinding machines in the January 2023 period is 79.78%. This value is not in accordance with the world-class OEE value standard, which is 85%. The biggest factor that influences the low OEE value is because the machine downtime is quite high, which affects the machine availability value so the machine availability value is 81.16%. Keywords: Maintenance, Overall Equipment Effectiveness, Total Productive Maintenance

Efektivitas Mesin Slitter Dengan Menggunakan Metode OEE di Perusahaan Packaging

XYZ is a company engaged in manufacturing produce packaging products that use machines in the production process. The Slitter machine is one of the main machines in this company's production flow, however, according to research results, downtime often occurs causing the production flow to stop so that losses can occur for the company due to not achieving targets. This research aims to determine the level of effectiveness of the slitter machine at PT. The research method used is an analysis of Overall Equipment Effectiveness calculations and identification of the main causes of low machine effectiveness by applying OEE and Six Big Losses analysis. The results of this research show an OEE value of 81.61% which has not yet reached the ideal World Class condition of 85% and is the biggest factor in the value of losses in Performance Efficiency is 14.606%. Keywords: Downtime, Overall Equipment Effectiveness, Packaging, Six Big Losses.

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.