Effective Maintenance Program Research Articles

Development of operational standards procedures for maintenance and maintenance of public railway infrastructure infrastructure and electrical mechanical and architectural components in Wbs-based station buildings to improve maintenance and maintenance performance

A railway station is a place of departure and stoppage for trains. Poor, inappropriate maintenance and upkeep of infrastructure without strict supervision can result in physical damage to the infrastructure itself, thus losing its initial value and reducing the service life of the infrastructure. If the maintenance and upkeep of infrastructure in the transportation sector is not done properly, it can cause delays or, in the worst case, accidents. To ensure a high level of reliability and availability, the implementation of an effective maintenance program is very important. This is then clarified if poor maintenance and upkeep practices, such as in the transportation sector, can also affect the reliability of the transportation system and even cause life-threatening accidents. Damage or accidents that occur can also lower the company's image and customer or consumer trust. This research aims to develop Standard Operating Procedures (SOP) for maintenance and upkeep work on station buildings, architectural components, and mechanical electrical. The method used is based on a Literature Study, survey, and case study. The result of this research is the development of SOP maintenance and upkeep work on architectural components and mechanical electrical to improve maintenance performance.

Research on case-based reasoning for determining maintenance intervals of civil aircraft systems

The development of a rational and effective maintenance program is an important way to keep the safety and the economy of the aircraft industry. The maintenance program indicates maintenance types and intervals of all components. As development maintenance types of the components are simple, interval is a key to developing the maintenance program. In this paper, Case-Based Reasoning (CBR) is introduced to determine the intervals of components. It focuses on the expression and adjustments of the case. Finally, the reliability data of components in Boeing 737 is taken as an example to certify this method. The results show that this method can determine the maintenance intervals effectively, and so it has important engineering application value.

Abstract P119: Patient Evaluation of Technology and Coach Interaction in the Maintain Prime Weight Loss Maintenance Trial in Primary Care

Background: Participant experiences with lifestyle interventions can influence long-term engagement and outcomes. MAINTAIN PRIME is a pragmatic clinical trial adapted from an effective EHR-based weight maintenance program and designed for implementation by primary care staff. The trial assesses if health coaching with lifestyle tracking tools through the EHR patient portal (MyChart) helps patients better maintain weight loss compared to tracking tools alone. In this report we evaluated interim feedback on technology and coaching. Methods: Participants were adults with BMI ≥25 and intentional weight loss of ≥5% through healthy lifestyle changes. Participants were randomized to health coaching with tracking tools (coaching) or tracking tools alone (tracking) over 24 months. We conducted surveys after 12 months of participation. The System Usability Scale (SUS) and a team-developed survey on MyChart tracking tools and overall satisfaction were given to both groups, while questions adapted from the Measure of Coach and Teacher Alliance-Teacher Report (Alliance) were given to the coaching group only. The SUS and Alliance were analyzed using published methods, and the MyChart survey was analyzed descriptively. Results: Out of 163 participants completing 12 months in MAINTAIN PRIME, 65 (40 in coaching and 25 in tracking groups, 39.9% response rate) responded to at least 1 survey by time of analysis. At baseline, the mean age was 48.1 years, and females represented 64.6% (42/65) of responders. Demographics of responders were similar to non-responders across a range of characteristics (p>0.05). Participants rated the program usability as “good” with mean SUS score 70.2 (SD 18.4). There was no significant difference in SUS score by intervention arm (p=0.52). Most participants (56.9%, 29/51) were satisfied with their experience in the program and 51.0% (26/51) were likely to recommend it to others. Participants rated tracking tools as helpful for daily weight (51.0%, 26/51), steps (37.3%, 19/51), physical activity minutes (33.3%, 17/51), calories (23.5%, 12/51), and fat grams (11.8%, 6/51); 41.2% (21/51) of participants reported no use of tracking methods. Overall, 39.5% (17/43) of participants found tracking tools helpful. On the Alliance questionnaire participants rated aspects of health coaching as 3.3, 3.6, and 2.8 (on a 5-point Likert scale) for the coaching relationship, coaching process, and investment, respectively. Conclusions: MAINTAIN PRIME participants rated the usability of MyChart positively for health coaching and tracking tools, though less than half found tracking tools helpful. Health coaching was rated neutrally, suggesting further evaluation of transferability into a primary care and patient portal-based format is needed. Participant interviews are planned to further assess the acceptability of MyChart for health tracking and coaching.

Preface

Fourth Conference of Computational Methods & Ocean Technology (COTech 2023) November 30 – December 1, 2023, University of Stavanger, Stavanger, Norway The COTech (Computational Methods & Ocean Technology) conference started as part of the research and dissemination activities of the Program Area for research “COTech - Computational methods in Offshore Technology” at Faculty of Science and Technology, University of Stavanger (UiS) with its first event in 2017. This Program Area for Research was founded in 2015 with seven professors, four associate professors, two adjunct professors and five research (PhD) students from the Department of Mechanical and Structural Engineering and Materials Science (IMBM), whose expertise and competence lies primarily within use of computational methods such as finite element methods, boundary and volume element methods, computational fluid dynamics and the like in marine and subsea technology, marine operations, design and analysis of mechanical systems, integrity and reliability of offshore structures and mechanical systems, renewable energy and wind engineering. In the ocean-related engineering area in particular, numerical computation approach is nowadays not only serving as a means to cultivate and realize innovative ideas, but also it is becoming the primary choice to solve complex engineering problems for the harsh and unfriendly environment in the Arctic.Like the previous conference, this year’s COTech conference is conducted as part of the dissemination activities of the Institute Strategic Program (ISP) entitled “Computational Methods and Ocean Technology” established under the research activities of the Department of Mechanical and Structural Engineering and Materials Science. This three-year program (2021 - 2023) intends to bring researchers of the department under four selected research areas:1. Ocean Energy Conversion - installations & dynamic analysis of offshore wind turbines, structural health monitoring, corrosion assisted fatigue, ocean wave energy.2. Aquaculture Technology - efficient farming techniques, advanced numerical modeling and computation, fluid-structure interaction, design effective maintenance programs for aquaculture.3. Marine and Subsea Technology - sediment erosion (scour), scour prediction CFD models, structural integrity and fatigue life of offshore structures, adaptive control of ROVs in subsea application, predictive maintenance of subsea structures4. Innovative Solutions - 3D printing based innovative solutions, inspection drones, augmented reality for maintenance training,…In addition to the thematic areas covered in the last three conferences, the 4th COTech conference accommodated some of the emerging technologies and applications such as machine learning techniques, additive manufacturing technologies, 3D printing in healthcare technology, smart energy storage and bio-inspired design.In general, the conference is intended to provide a platform for academics and professionals working within diverse forms of the computational methods, Ocean/Offshore technology and Oil and Gas technologies to come together, present their recent works in the area, exchange ideas, and establish professional networks. It will serve as a forum for multidisciplinary research and bring together enable them to exchange their research experience and disseminate their results within the involved fields.List of Conference Organizing Committee, Volume Editors, Invited Keynote Speakers, Additional plenary session speakers, Technical Committee Members and Reviewers are available in this Pdf.

Wheel/rail-force–based maintenance interval extension of the C80 series wagon

PurposeThis study aims to introduce the achievements and benefits of applying wheel/rail-force–based maintenance interval extension of the C80 series wagon in China.Design/methodology/approachChinese wagons' existing maintenance strategy had left a certain safety margin for the characteristics of widely running range, unstable service environment and submission to transportation organization requirements. To reduce maintenance costs, China railway (CR) has attempted to extend the maintenance interval since 2020. The maintenance cycle of C80 series heavy haul wagons is extended by three months (no stable routing) or 50,000 km (regular routing). However, in the meantime, the alarming rate of the running state, a key index to reflect the severe degree of hunting stability, by the train performance detection system (TPDS) for the C80 series heavy haul wagons has increased significantly.FindingsThe present paper addresses a big data statistical way to evaluate the risk of allowing the C80 series heavy haul wagons to remain in operation longer than stipulated by the maintenance interval initial set. Through the maintenance and wayside-detector data, which is divided into three stages, the extension period (three months), the current maintenance period and the previous maintenance period, this method reveals the alarming rate of hunting was correlated with maintenance interval. The maintainability of wagons will be achieved by utilizing wagon performance degradation modeling with the state of the wheelset and the often-contact side bearing. This paper also proposes a statistical model to return to the average safety level of the previous maintenance period's baseline through correct alarming thresholds for unplanned corrective maintenance.Originality/valueThe paper proposes an approach to reduce safety risk due to maintenance interval extension by effective maintenance program. The results are expected to help the railway company make the optimal solution to balance safety and the economy.

Optimisation of Capacitated Planned Preventive Maintenance in Multiple Production Lines Using Optimisation-in-the-Loop Simulation

In a mass customisation manufacturing system, the production schedule is tailored to the customer's specifications. However, the production system must be accompanied by an effective maintenance program to ensure that the production lines operate as intended. The purpose of this study is to optimise planned preventive maintenance across multiple production lines. An optimised Weibull distribution is proposed to model the machine's Mean Time Between Failures (MTBF), and the total expected maintenance cost is calculated using this distribution, taking into account the probability of the machines remaining operational and failing. Because the optimised Weibull distribution is a continuous distribution, in order to simulate the continuous time domain, it will be divided into several sub-systems and optimised using Bayesian optimisation during simulation. The maintenance scheduling is carried out by considering available time capacity after production scheduling was arranged. The study's findings indicate that the proposed method successfully optimised the planned maintenance schedule without interfering production activity with total cost for the proposed maintenance planning as low as IDR 50.017,75/maintenance unit time.

Factors Influencing Pavement Friction during Snowstorms

Operating an effective winter road maintenance program is a necessity for cities that face severe winter seasons. Snowstorms leave roads in a slippery surface condition that disrupts traffic flows and compromises drivers’ safety. Decision-makers use a variety of tools to control snow and ice on the roads, which include applying anti-icing chemicals before snowstorms, applying deicing substances on fresh snow, and clearing snow off the roads using snowplows. However, the influence of these tools on improving the overall road surface conditions has not been investigated. In this study, a location-specific and event-based framework was utilized to understand the impact of the different weather variables as well as maintenance operations on the variability of the pavement friction coefficients during snowstorms in urban environments. Using multilinear regression and ordinary least squares, friction coefficient models were calibrated. The final model was found to be a good fit for the data (R2 = 0.723). The model showed that the total precipitation during snowstorms, extremely low temperatures, and the potential for black ice formation worsen pavement friction significantly. On the other hand, plowing operations, the application of anti-icing chemicals before snowstorms, and frequent deicing operations all have a statistically significant impact on improving pavement friction. The model presented in this paper can be used to predict pavement friction on urban arterial and collector roads during snowstorms of different magnitudes, which could help the authorities in predicting the road surface conditions during forecasted snowstorms and deciding on the best course of action under these conditions.

RISK ASSESSMENT FOR STRUCTURAL STEEL CORROSION IN OIL AND GAS FACILITIES

Steel structure corrosion management is important to ensure the integrity of the assets are not compromised to prevent unnecessary disruption to the operation of oil and gas facilities due to structural failure which can cause significant loss of production. In this paper, with the objective to enhance the cost and time effectiveness, a risk-based approach is being used as means to prioritize and plan for effective inspection, maintenance and repair program to minimize the risk of failure of an asset in oil and gas facilities and optimize resources. Factors contributing to corrosion in oil and gas facilities have been considered in the risk assessment. The outcome of the risk assessment is obtained through careful evaluation of appropriate hazard criteria. From the risk assessment, mitigation program can be developed and implemented effectively. Furthermore, this paper has also recommended improvements and enhancements to the risk assessment which is suitable for application in oil and gas facilities.

Comparing PCA-based fault detection methods for dynamic processes with correlated and Non-Gaussian variables

Maintenance strategies have been playing an increasingly important role in improving engineering systems’ performance, supporting the growth of availability and reliability, and delivering significant savings to their operation. In this scenario, the ability to predict the needs for assets’ maintenance at a given future time is one of the major challenges. Consequently, detecting a fault in its early stages becomes a critical part of the development and implementation of an effective maintenance program. In this growing research field, data-based multivariate statistical methods have been standing out over other approaches, with Principal Component Analysis being one of the most-cited methods in the literature. Adaptive and non-adaptive variations of this method have been developed and applied to overcome issues regarding stationarity and data autocorrelation. Accordingly, this article proposes a study in which three adaptive methods combined with three process monitoring metrics are compared to perform early fault detection. Among these methods, two are novelties that incorporate the ability to deal with nonstationary and autocorrelated data. Different types of faults and data distributions are considered and a multi-criteria decision analysis method is applied to define the best alternative among the considered combinations of methods and metrics. The results demonstrate consistency and how the different types of faults can influence the analysis.

A study of the different relations between disruptive events and human factors and their effects on maintenance performance

Understanding the factors that affect the quality of maintenance tasks is critical to ensure an effective maintenance program. In this paper, we present a comprehensive framework to evaluate de impact of human and environmental/managerial factors on inspection quality, specifically regarding the probability of defect induction by this kind of activity that usually has solely informative purposes. We discuss the influence of Disruptive External Events (DEEs) on the probability of human error. A DEE can disrupt appropriate conditions for performing inspection tasks, making maintenance staff more subject to errors that can result in defect induction. We present a delay-time based mathematical model for an inspection-maintenance policy applied to a non-repairable single-component technical system, incorporating to the model a probability of defect induction at inspections that may vary according to parameters related to DEEs and human reliability. We investigate how likely a defect induction can be depending on the capacity of the team to recover proper conditions to more reliable inspections. An important finding concerning the induction of defects calls attention to the need to invest in more appropriate conditions to carry out interventions on the system. The results obtained highlight the importance of a deeper investigation integrating technical aspects of the systems with relevant subjects from areas related to human behavior and social sciences.

The effect of society participation, budget, and organization on the effectiveness of pond maintenance program in Kobalima District, Malaka Regency

Abstract: Purpose: The discussion of this research is Society Participation, Budget, and Organization on the Effectiveness of Pond Maintenance Program in Kobalima District, Malaka Regency. Research Methodology: This study uses quantitative research methods with sampling techniques in research using the Slovin formula and data analysis techniques using regression, namely looking for the effect of each independent variable on the dependent variable, and the instrument used in this study is intended to produce accurate data by using a Likert scale. Results: Each independent variable, namely society participation, budget, and organization, partially has a significant influence on the effectiveness of the pond maintenance program. Simultaneous society participation, budget, and organization also have a significant effect on the effectiveness of the pond maintenance program. Limitations: Research variables are complex and research results may change in the future. Contribution: Research findings can serve as a basis for evaluation and the basis for maintaining existing good performance in promoting an effective pond maintenance program. Keywords: 1. Budget 2. Organization 3. Participation

Construction and Evolution of Fault Diagnosis Knowledge Graph in Industrial Process

The steel industry production line is complicated and contains a substantial amount of equipment, leading to serious problems in fault diagnosis such as wrong inspection strategies, fault location, maintenance, and so on. To realize accurate and efficient equipment fault diagnosis, this paper proposes a steel production line equipment fault diagnosis knowledge graph (SPLEFD-KG) based on a novel relation-oriented model with global context information for jointly extracting overlapping relations and entities (ROMGCJE). A low-level self-learning SPLEFD-KG is first constructed using the triples extracted by ROMGCJE. However, this low-level SPLEFD-KG is incomplete, and only contains sparse paths for fault reasoning. To overcome this problem, a reinforcement learning framework is applied to mine hidden semantic knowledge to complete the missing relation. Besides, the graph neural networks are introduced to compute the embedding vector of new entities outside of the SPLEFD-KG for continuously completing missing entities. Finally, the low-level self-learning SPLEFD-KG evolves to one high-level SPLEFD-KG, which can provide information-rich and accurate fault-related knowledge. Extensive experiments conducted on the steel production line equipment failure dataset indicate that the novel SPLEFD-KG significantly improves fault diagnosis results and provides effective maintenance programs.

Aircraft operators maintenance decisions supporting method

A key element of exploitation processes constitutes maintenance operations and tasks. While being conducted in the proper way, they have a crucial effect on achieving the assumed by aircraft designer and operator goals. Properly conducted maintenance operations allow to meet all the technical objects readiness requirements as well as to achieve desired acceptable risk level. Maintenance system effectiveness might be generally a crucial task for company or entity responsible for the maintenance. In this context, particularly relevant become technical object maintenance procedures and tasks developed by their manufacturers. Experience of the article authors quite early shows the need of the mainte-nance programmes modification. Aircraft manufacturers usually are not so eager to develop and implement mainte-nance programme modifications. Presented situation is very much the case in aviation transport. This was the reason why authors of this article decided to prepare and develop this elaboration which might constitute the assistance and supports complex technical objects users in maintenance decision. The main purpose of this article is to present maintenance decisions’ supporting method for the aircraft operators. This article provides guidelines which include a description of risk in the context of aviation maintenance and introduction of some methodologies, tools and criteria that support identification, analysis and evaluation of risk. Authors included idea, how the aircraft preventive maintenance could be used to mitigate aircraft failure risk during flight operations. It also shows how to adopt and develop effective maintenance program using tools for adequate risk analysis, optimal interval assignments, and selection of the most effective maintenance task. Authors presented methodology and de-scribed steps of the logic diagram analysis for the aircraft systems and their components, in order to manage and adopt aircraft maintenance program to fulfil aircraft airworthiness requirements and operational availability. The whole methodology was described on the basis of the F 16 aircraft maintenance system and with reference to the maintenance data. This article might also constitute an introduction to the aircraft maintenance programme development method.

Continuum risk-based asset integrity management system for geothermal steam pipelines: Kamojang Unit 4, Indonesia

This work examines the use of pressure drop in geothermal steam lines using a continuum approach to the implementation of risk-based analysis. The study is performed by observing the behaviour of changes in pressure drop along the steam pipeline in the Kamojang geothermal field. The relevance of this study is in the context of the implementation of physical asset management based on the PAS 55 guidelines that emphasise risk-based management. This is using the risk-based inspection (RBI) method utilising the API RP-580 standard. Application of flow analysis as a continuum risk-based approach in asset integrity management system is feasible due to its ability to be performed while the equipment is online. It can serve as a first tear assessment before conventional pipeline thickness measurements for setting an effective and efficient maintenance program. This method is also suitable for pipelines that are difficult to access with conventional thickness measurement methods.Steam pipelines in dry fields can have a higher thining rate and effectively shortened life when compared with steam lines from two-phase and wet geothermal fields due to the limited silica carryover. The steam pipeline for Kamojang Unit 4 is in reasonable conditions to continue operating for its intended lifetime of 30 years. Steam washing with slightly mineralised (SiO2 and Cl rich) water/brine is recommended to extend the life of the pipeline.

Flexible Pavement Crack’s Severity Identification and Classification using Deep Convolution Neural Network

Effective road maintenance program is vital to ensure traffic safety, serviceability, and prolong the life span of the road. Maintenance will be carried out on pavements when signs of degradation begin to appear and delays may also lead to increased maintenance costs in the future, when more severe changes may be required. In Malaysia, manual visual observation is practiced in the inspection of distressed pavements. Nonetheless, this method of inspection is ineffective as it is more laborious, time consuming and poses safety hazard. This study focuses in utilizing an Artificial Intelligence (AI) method to automatically classify pavement crack severity. Field data collection was conducted to allow meaningful verification of accuracy and reliability of the crack’s severity prediction based on AI. Several important phases are required in research methodology processes including data collection, image labelling, image resizing, image enhancement, deep convolution neural network (DCNN) training and performance evaluation. Throughout the analysis of image processing results, the image output was successfully classified using MATLAB software. The good agreement between field measurement data and DCNN prediction of crack’s severity proved the reliability of the system. In conclusion, the established method can classify the crack’s severity based on the JKR guideline of visual assessment.

Older Adults’ Experience of Health and Life Events as Reported Online Over 150 Consecutive Weeks

Key activities and life events that impact quality of life and health may be gleaned from cross-sectional annual surveys or for medical data, derived intermittently from electronic health records. These methods cannot reflect the day-to-day and week-to-week changes that typically occur in domestic life. To assess the frequency and types of major life activities and events occurring at finer-grained temporal scale, we queried online, every week, three domains of activity and function (life events such as having an overnight visitor, travel away from home; health-related events such as medication changes, falls, ER/hospital visits, health limitations; and internal states such as pain, mood, or loneliness). Over a mean assessment period of 2.9 ± 1.2 years, 16,738 online surveys were completed by 129 community-residing volunteers with mean age 84 years. Overall the most frequent events reported were physical health limitations (14%), travel away from home (12%) and overnight visitors (9%). Needing new in-home assistance for medication management, bathing, dressing or grooming was rare (1%). Accidents were also rare (1%). Low mood, pain ratings (0-10 scale) and loneliness were infrequently reported; 4% low mood, 8% pain rated > 5, 3% reporting loneliness. Low mood and increased pain intensity were highly correlated with health changes (medication changes, ER/hospital visits, health limitations, falls; all p<0.0001). Continuous home-based online assessment of life activities and health can provide a more detailed and timely characterization of older adult function. These data may be used to guide more timely and effective health maintenance programs and interventions.

Failure Modes Effects and Criticality Analysis and Fault Tree Analysis Case Study of Waste Heat Recovery Plant in a Cement Factory, United Arab Emirates

This article reports a case study of the application of FMECA and FTA methods to inform the design of effective maintenance program for a waste heat recovery power plant in the hot arid climate of the United Arab Emirates. It illustrates the strengths and weaknesses of these approaches through a case study report of a live plant in a cement factory. The article highlights the implications and importance of plant-specific contextual factors in conducting quality FMECA and FTA.

Build an Effective Valve Operations and Maintenance Program

Knowing how, when, and why to service critical valve assets can help your utility operate efficiently as well as save time and money.

Reap the Benefits of a Fire Hydrant Maintenance Program

Water utilities excel when they place value on and maintain each system asset in a manner that reflects its value. An effective fire hydrant maintenance program offers a wide range of system benefits.

UAV PHOTOGRAMMETRY FOR CULTURAL HERITAGE PRESERVATION MODELING AND MAPPING VENETIAN WALLS OF BERGAMO

Abstract. In July 2017, the system of Bergamo City Walls was registered in the UNESCO World Heritage List, together with other Venetian fortresses in Italy, Croatia and Montenegro. This important historical document needs continuous care and caution in order to be preserved complete, despite the continuous atmospheric and anthropic attacks, giving rise to dangerous deterioration processes on the artefact. The UAV photogrammetry is a suitable surveying method for such an extended system, able to collect all the geometrical, material and deterioration information needed for an effective maintenance program, also quick enough to allow for a repeated monitoring of the entire wall circuit. This paper presents the UAV survey campaign planned, and partially already completed, in order to test the methodological choices and solve all the operational difficulties to use drones in an urban environment, mainly because short distance shooting of nearly vertical surfaces was required.