Maintenance Technicians Research Articles

Cold chain maintenance done differently: results from a human-centered design study in Niger, Kenya and Tanzania

Cold chain equipment is required to keep vaccines cold, yet the equipment maintenance system is often overlooked and underperforming. Immunization programs in Niger, Kenya, and Tanzania conducted human-centered design studies to better understand the gaps in the maintenance systems and to identify potential solutions from the perspective of maintenance technicians. Researchers conducted 110 key informant interviews in seven regions across the three countries, including a wide range of stakeholders involved in cold chain management and maintenance. The same participants generated innovative solution ideas during co-creation workshops. Five themes related to the maintenance system challenges were identified with nuances between countries. Themes were linked to the health system management structure, data use for maintenance activities, capacity and expertise, limited autonomy, and spare parts availability. Through co-creation, user-generated ideas for improvements had some similarities between countries, including the desire for a peer-to-peer e-learning and networking platform, tailored technical resources, and a reporting system for maintenance. While basic challenges related to cold chain maintenance have been generally understood, this unique study identified underlying drivers grounded in stakeholders’ experiences and perspectives. The identified potential solutions across three countries tended to coalesce in similar ideas to address multiple challenges. Insights and ideas generated by this study may be relevant to other countries’ maintenance systems.

Enhancing Resurrection Practices for Unusable General Inventory Items in Hospital Settings

Background: Effective patient care in hospitals relies on the proper functioning of medical equipment. Malfunctioning general inventory items, such as patient beds, wheelchairs, and saline stands, pose significant challenges to hospital operations and patient care. D.G.H. Negombo needs help maintaining these items due to limited financial resources and inadequate technical expertise.Objective: To improve the resurrection practices of selected unusable general inventory items at D.G.H. Negombo.Methodology: This cross-sectional descriptive study was conducted from August 1, 2022, to November 15, 2023, and involved three phases: pre-intervention (assessment), intervention (implementation), and post-intervention (evaluation). Data collection methods included key informant interviews (K.I.I.), self-administered questionnaires (S.A.Q.), and desk reviews. The study targeted general inventory items marked for condemnation and included unit heads and maintenance technicians in its scope.Results: Pre-intervention assessments identified key issues such as inadequate technical skills, poor coordination, and insufficient infrastructure. Interventions implemented included skill development workshops, improved documentation practices, and enhanced communication strategies. Post-intervention evaluations demonstrated significant improvements in repair times, resource availability, and satisfaction among unit heads. Notably, 78% of wheelchairs, 79% of patient trolleys, and 76% of patient beds were successfully resurrected.Conclusions: The interventions enhanced the resurrection of unusable general inventory items, extended equipment lifespans, and achieved substantial cost savings.

Diagnostics-LLaVA

The recent advancements in the area of Large language models (LLMs) has opened horizons for conversational assistant-based intelligent models capable of interpreting images, and providing textual response, also known as Visual language models (VLMs). These models can assist equipment operators and maintenance technicians in the complex Prognostics and Health Management (PHM) tasks such as diagnostics of faults, root cause analysis and repair recommendation. Significant open source contributions in the area of VLMs have been made. However, models trained on general data fail to perform well in complex tasks in specialized domains such as diagnostics and repair of industrial equipment. Therefore, in this paper we discuss our work on development of Diagnostics-LLaVA, a VLM suitable for interpreting images of specific industrial equipment and provide better response than existing open source models in PHM tasks such as fault diagnostics and repair recommendation. We introduce Diagnostics-LLaVA based on the architecture of LLaVA, and created one instance of the Diagnostics-LLaVA for the automotive repair domain, referred to as Automotive-LLaVA. We demonstrate that our proposed Automotive-LLaVA model performs better than the state-of-the-art open source visual language models such as mPlugOWL and LLaVA in both qualitative and quantitative experiments.

Identification of wheel surface cracks under high noise environment based on texture segmentation and combination descriptor

ABSTRACT The wheel is easy to produce defects after a long time of use. Train maintenance technicians must overhaul and maintain train wheels on time and regularly to ensure the safe operation of trains. The existing manual detection has disadvantages of low efficiency and strong subjectivity. Compared with other defect forms, the identification accuracy of wheel surface crack is low due to the high noise and weak features, this paper proposes a feature enhancement and identification method for wheel surface crack based on texture segmentation and combination descriptor. Firstly, a morphology-based texture segmentation method is proposed to separate cracks and noise. Then, the crack characteristics are enhanced by filtering. Finally, a crack diagnosis method based on combination descriptor is proposed, which is evaluated from two dimensions of crack morphology and distribution characteristics. In order to verify the effectiveness of the proposed method, the images of the wheel collected from the freight car workshop were used for verification, and the detection rate reached 93.78%. The experimental results show that the proposed method is more effective in the case of weak crack features and surface dirt, and can better adapt to the identification of surface cracks on wheel in complex engineering applications.

Development of an application for training management of the maintenance team in a metallurgical industry in the suape industrial complex – cabo de Santo Agostinho

This work presents the development of an application designed to complement traditional training management methods within an organization. The application, developed on the PowerApps platform using a Low-Code approach, aims to facilitate the monitoring and management of employee training in the maintenance department of a company located in the Suape industrial complex, Cabo de Santo Agostinho. Its main objective is to provide a digital platform that allows for the verification of the training status of maintenance technicians, identifying which are in "Attention," "Expired," and/or "OK" status. Traditionally, this data is managed manually, in a time-consuming and error-prone process. The transition to a digital system ensures data accuracy, reduces the time required to access and update information, and improves the overall efficiency of the department's activity scheduling process. During the testing phase, conducted between January and August 2024, comparative data was collected on the training consultation process, before and after the implementation of the application. Preliminary results indicated a significant improvement in the efficiency and productivity of the maintenance department, comparable to other works that used PowerApps as a quick and low-cost solution.

Power Distribution Transformer Maintenance Skills Required byElectrical Engineering Technology Students ofPolytechnics inNorth-East Nigeria

Electric power distribution industry in North-East, Nigeria is faced with inadequate number of power transformer maintenance personnel which has led to numerous abandonment of broken down power transformers. Transformer faults have been blamed for many power outages of long duration in many towns and communities in North-East, Nigeria.It is against this backdrop that thisstudy determined the power distribution transformer maintenance skills required by Electrical Engineering Technology students of polytechnics in North-East Nigeria. Three research questions and three hypotheses guided the study which employed a descriptive survey research design. The population of the study was 144 comprising of 135 Electrical Engineering Technology Lecturers, 3 Power Transformer Maintenance Technicians and 6 Electric Power Distribution Company-Based Supervisors. The entire population was used hence, there was no sampling. The instrument used for data collection was a structured questionnaire titled: Power Distribution Transformer Maintenance Skills Required Questionnaire (PDTMSRQ) developed by the researchers. The instrument was validated by three experts and a reliability of 0.74 was obtained using Cronbach Alpha reliability method. Mean statistic was used to answer the research questions while ANOVA was used to test the two null hypotheses of the study at 0.05 level of significance. The findings of the study revealed that the Electrical Engineering Technology students of polytechnics in North-East Nigeria required preventive, predictive and corrective maintenance skills. The study recommended the following: Lecturers should encourage the students’ skill acquisition process by exposing them to various maintenance activities in order for them to imbibe the different methods of power transformer maintenance; Students should be trained to recognize sounds and sights of faulty equipment in order to predict the parts or components that needed replacement or repairs.

Safety Culture and Worker Perception in Highway Maintenance Operations: A Survey of Alabama Department of Transportation Maintenance Technicians

The survey entitled “Field Survey of Alabama Department of Transportation (ALDOT) Transportation Maintenance Technicians (TMTs) Perception of Worker Safety” investigates the safety perceptions and concerns of maintenance workers within ALDOT through a multifaceted analysis approach. The findings reveal critical insights that can significantly enhance ALDOT’s safety practices, training programs, and overall safety culture. Disparities in safety perceptions across different ALDOT’s areas were found, emphasizing the need for ALDOT to tailor its strategies to meet the unique needs of each area, ensuring that safety measures are both relevant and effective. The study emphasizes the importance of implementing targeted interventions focused on high-risk activities and prevalent safety concerns, allowing ALDOT to prioritize resources effectively. Additionally, the research highlights the necessity for continuous improvement by regularly evaluating safety initiatives based on feedback and best practices. This ongoing evaluation ensures that safety measures remain relevant and effective in addressing the evolving needs of TMTs. By integrating these insights into its safety management practices, ALDOT can cultivate a more proactive and resilient work environment that not only addresses immediate safety concerns but also establishes a sustainable culture of safety prioritizing employee well-being. The study provides a roadmap for future improvements in workplace safety and initiates discussions on the implications and recommendations for enhancing ALDOT’s and other transportation agencies’ safety management practices.

Human fatigue in the aircraft maintenance environment

The complexity of technologies in modern aircraft makes their maintenance a critical function. The work environment is diverse and dynamic, with uninterrupted working hours and multiple demands, which can result in inadequate sleep and excessive workload for Aircraft Maintenance Technicians. This causes fatigue and increases the likelihood of human errors, directly affecting safety. A study was conducted with 312 participants to investigate how fatigue affects maintenance professionals. Participants responded to questionnaires that included four culturally validated scales to measure levels of fatigue, sleepiness, workload, and quality of life. Statistical analyses were performed to correlate sociodemographic factors and work-related aspects with levels of fatigue. The results revealed a positive and significant correlation between fatigue, sleepiness, and workload, and a significant negative correlation with quality of life. It was found that 52.9% of participants experienced some level of fatigue, highlighting the prevalence of fatigue among the sampled population. Statistically significant differences were also found in participants aged 36 to 50, those working shifts, and those working during nighttime hours. Therefore, regulations and practical measures are needed to assess and manage fatigue-related risks, tailored to the aircraft maintenance environment, given that current regulations on human fatigue in aviation primarily focus on flight crew, paving the way for potential changes in the European Aviation Safety Agency regulations.

Maintenance cost optimisation in critical single-component systems: A technician’s training approach based on a joint learning–forgetting and fuzzy maintenance quality model

Effective maintenance in critical systems is crucial to ensure their operability and safety. Maintenance technicians play an important role in achieving the safety and reliability objectives of critical system components. However, the role of the technical team in maintenance quality is often overlooked. Our study addresses this knowledge gap by developing a methodology to optimise the training scheduling of maintenance technicians in single-component systems, focusing on a learn-and-forget approach. Our main objective is to improve maintenance efficiency by mitigating the negative impact of technician expertise level. To this end, we implemented a simulation-based optimisation, modelling the evolution of technician experience and its influence on maintenance costs. As a case study, we used an urban aerial passenger ropeway system, demonstrating that proper training of technical staff can significantly reduce both corrective and preventive maintenance costs. Our methodology identified three strategic areas for training technical staff throughout the system lifecycle. The results highlight the importance of investing in the training scheduling of technical equipment in critical systems and suggest that an appropriate training strategy can improve operational efficiency and reduce maintenance costs. In conclusion, our research underlines the need to actively consider the human factor in the maintenance of critical systems to ensure their optimal performance and long-term safety.

A Lifecycle Approach for Artificial Intelligence Ethics in Energy Systems

Despite the increasing prevalence of artificial intelligence (AI) ethics frameworks, the practical application of these frameworks in industrial settings remains limited. This limitation is further augmented in energy systems by the complexity of systems composition and systems operation for energy generation, distribution, and supply. The primary reason for this limitation is the gap between the conceptual notion of ethics principles and the technical performance of AI applications in energy systems. For instance, trust is featured prominently in ethics frameworks but pertains to limited relevance for the robust operation of a smart grid. In this paper, we propose a lifecycle approach for AI ethics that aims to address this gap. The proposed approach consists of four phases: design, development, operation, and evaluation. All four phases are supported by a central AI ethics repository that gathers and integrates the primary and secondary dimensions of ethical practice, including reliability, safety, and trustworthiness, from design through to evaluation. This lifecycle approach is closely aligned with the operational lifecycle of energy systems, from design and production through to use, maintenance, repair, and overhaul, followed by shutdown, recycling, and replacement. Across these lifecycle stages, an energy system engages with numerous human stakeholders, directly with designers, engineers, users, trainers, operators, and maintenance technicians, as well as indirectly with managers, owners, policymakers, and community groups. This lifecycle approach is empirically evaluated in the complex energy system of a multi-campus tertiary education institution where the alignment between ethics and technical performance, as well as the human-centric application of AI, are demonstrated.

Indoor Infrastructure Maintenance Framework Using Networked Sensors, Robots, and Augmented Reality Human Interface

Sensing and cognition by homeowners and technicians for home maintenance are prime examples of human–building interaction. Damage, decay, and pest infestation present signals that humans interpret and then act upon to remedy and mitigate. The maintenance cognition process has direct effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern technologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recommend courses of remedial action. The demonstrated technologies include robotic sensing in confined areas, LiDAR scans of structural shape and deformation, moisture and gas sensing, water leak detection, network embedded ML, and augmented reality interfaces with multi-user teaming capabilities. The sensor information passes through a private local dynamic network to processors with neural network pattern recognition capabilities to abstract the information, which then feeds to humans through augmented reality and conventional smart device interfaces. This networked sensor system serves as a testbed and demonstrator for home maintenance technologies, for what can be termed Home Maintenance 4.0.

Employability skills of maintenance technicians in container ports: Implications for maritime technical and vocational education and training

The study investigated the employability skills of maintenance technicians engaged in container ports in Sri Lanka. The specific objectives were to investigate 1) employability skill gaps between technicians’ evaluations of the level of current possession and the expected level to be possessed for the current job tasks, 2) employability skill gaps between technicians’ evaluations of the expected level of skills for current job tasks and immediate superiors’ evaluation of the importance of the same for current tasks, and 3) maintenance technicians’ exposure to skill development strategies after joining the respective container port terminals. The study was conducted in the two main container ports of Sri Lanka- Colombo and Hambantota. Responses were pooled from two independent sample groups- maintenance technicians and their immediate superiors. Maintenance technicians had graduated from technical and vocational education and training institutions with levels 3 or 4 National Vocational Qualification. Findings identified employability skill preferences of maintenance technicians and their immediate superiors, which led to possible skill gaps. The findings highlight the importance of TVET institutions identifying the preferences of business sectors, they should be prepared to impart employer-preferred skills to their trainees and to bridge any gaps in expectations. This will lead employees to develop realistic expectations of employer preferences. Hence, the findings of the study have implications for technical and vocational education and training institutions, students enrolled in these institutions, employees engaged in container ports, and their employers. Highlights Employability skills are vital to be employed and to remain employed Skill gaps have consequences for job seekers, employers, and training institutes This study investigated employability skills of technicians in container ports

Exploring positive psychological factor on safety behavior of Chinese aircraft maintenance technicians: The interplay of workplace well-being, work engagement, and leadership

The safety behaviors of aircraft maintenance technicians (AMTs) are crucial in ensuring aviation safety. It is, therefore, vital to explore the factors associated with AMT safety behaviors and the underlying mechanisms. This study, drawing on self-determination theory and the broaden-and-build theory, explores the relationship between workplace well-being (WWB) and AMT safety behaviors within the framework of positive psychology. A sample of 593 Chinese AMTs (561 males and 32 females; average age = 27.28, SD = 3.73) anonymously completed questionnaires on demographic variables, WWB, work engagement, safety-specific transformational leadership (SSTL), and safety behavior. We utilized SPSS 26.0 and the PROCESS macro (models 4 and 7), along with Amos 24.0, to conduct an empirical test of a moderated mediation model elucidating the relationship between WWB and safety behavior. The findings reveal a positive association between WWB and AMT safety behaviors, with work engagement acting as a partial mediator. Furthermore, SSTL was found to negatively moderate the positive association between WWB and work engagement, as well as the association between WWB and safety behavior through work engagement. Notably, the positive association between WWB and work engagement, and thus safety behavior, becomes more pronounced under lower SSTL conditions. In conclusion, this study makes theoretical contributions and offers practical insights for improving aircraft maintenance safety management practices.

Different Shades of Green: An Analysis of the Occupational Health and Safety Risks Faced by Wind Farm Workers

The growth of the wind power sector has been marked by environmental, economic, and political drivers. Its starring role is also visible in the emergence of the so-called “green jobs”. Notwithstanding, its evolution ought not to compromise issues related to occupational risks. This exploratory study examines psychosocial risks in the operation and maintenance of onshore wind turbines in a leading Portuguese company. We conducted interviews with main stakeholders (human resources, OHS professionals, and team leaders); developed an “activity diary” for the operation and maintenance technicians to describe their activity and perceived impacts on health, complemented with collective interviews; and applied the Work and Health Survey. The results revealed the following particular risks and health impacts: working under adverse weather conditions, working at heights and in confined spaces, spending long work hours inside of the nacelles to achieve an optimum balance between favourable wind slots to intervene and avoiding additional trips up and down the wind turbines without lifts (70–120 m), and the feeling of early ageing. At a time when these workers are striving for recognition of their profession as a “rapid wear profession”, it is a pivotal moment to discuss these results to guarantee sustainable conditions for future generations of workers.

Service accessibility strategy for aircraft maintenance routing with interorganizational collaborations on outsourcing maintenance

Airline companies are increasingly outsourcing their fleets’ heavy maintenance to independent maintenance service providers. This paper investigates the aircraft maintenance routing problem (AMRP) under the Maintenance, Repair, and Overhaul (MRO) outsourcing mode. Considering interorganizational maintenance implementation, an airline company’s accessibility to maintenance service is affected by the varying maintenance capabilities of the maintenance service provider, which depends on heterogenous maintenance resource availability (e.g., the accommodation capacity of maintenance hangars and the availability of maintenance technicians and aviation spare parts). To enhance the airline’s service accessibility to maintenance service, we propose an efficient maintenance planning strategy with a collaborative mechanism based on service information sharing and service capability evaluation from the airline’s perspective. Afterward, a time-complexity reduction approach is presented to enhance the discrete-time-stamp-indexed mathematical model formulation. The efficiency and effectiveness of the proposed approach were evaluated through various problem scenarios, based on the operational data from a regional airline. Managerial implications regarding maintenance strategy and the accuracy of maintenance capability evaluation are also discussed.

Hybrid multi-criteria decision making approach proposal for evaluating workloads of aircraft maintenance technicians.

Aircraft maintenance technicians (AMTs) have the most difficulty in terms of total workload criteria working in line maintenance. This is a very important problem for the Aircraft Maintenance Organization. A systematic and scientific approach is required for its solution. This study proposes a new Multi-Criteria Decision Making (MCDM) based approach to evaluating the total workloads of AMTs to identify the most challenging AMT tasks in the aircraft maintenance organization. A new hybrid MCDM approach is proposed by integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order Preference by Similarity (TOPSIS) methods to compare AMTs on the basis of workloads according to license categories. The hybrid method proposed in this study evaluates the total workload under three main titles: mental, physical, and environmental workload. Focusing on AMTs working in line maintenance of an aircraft maintenance organization, this study revealed that the most important workload criteria determined by the DEMATEL method are lower back strain, upper back strain, time pressure, and air temperature criteria. The results of the TOPSIS method showed that the license categories of AMTs are sorted according to the workloads as follows: A, B2, B1, and B1 + B2. The AMTs holding a "Category A" license have fewer workloads than the other categories. The findings of the study reveal some measures that might allow authorities to minimize the workload of AMTs. In addition, the study contributes to the literature because there are few studies that systematically analyze total workloads by using MCDM methods.

Human factors in aviation maintenance: understanding errors, management, and technological trends

Aircraft maintenance and inspection are complex systems that work on a time-based schedule and require teamwork of different professionals to maintain the airworthiness of aircraft. Errors in maintenance and inspection processes cause in-flight engine shutdowns, flight delays, flight cancellation, sometimes resulting in accidents and incidents that cause significant economic consequences. Due to the substantial impact on both safety and financial aspects of an air carrier, this paper focuses on hangar maintenance as the work is carried out across several shifts by different technicians, addressing various human factor issues that contribute to errors. The paper will also briefly discuss shift work and the health problems of maintenance technicians, human factor issues affecting maintenance, the significance of understanding human factor models, and the impact of maintenance and inspection errors with case studies, particularly aircraft accidents predominantly caused by human factor issues. Additionally, the paper also explores recent advances and trends in aircraft maintenance technologies, highlighting their transformative potential through predictive maintenance, robotics, augmented and virtual reality, big data analytics, blockchain, and additive manufacturing. These technologies promise enhanced efficiency, safety, and effectiveness for maintenance practices. The paper concludes by presenting insights into error management methods and providing recommendations for future research. By integrating traditional insights with cutting-edge technological considerations, this comprehensive analysis aims to significantly contribute to the evolution of safety protocols and practices within the aviation maintenance domain.

Differences between Experts and Novices in the Use of Aircraft Maintenance Documentation: Evidence from Eye Tracking

Maintenance is a highly procedural activity requiring motor and cognitive engagement. The aim of this experimental study was to examine how expertise affects maintenance tasks, in particular, the use of procedural documents. A total of 22 aircraft maintenance technicians were divided into two groups according to their level of expertise. Helicopter maintenance was evaluated in a real work environment, using an eye tracker, a fixed camera, and NASA-TLX to measure workload. Both groups reported a high mental load. Novices showed elevated levels of effort and mental demand. Experts were faster at all levels of the task and spent less time consulting maintenance documentation. The acquisition of procedural information was greater at the start of the task, where the gap between groups was more pronounced. This may be related to the overall planning of the task, in addition, the task was atomized, with frequent back-and-forth between execution and information intake, for all participants. Novices had a longer document consultation duration, spread over a greater number of consultations, but did not have a higher average consultation time. The results indicate a higher mental load for novices, potentially linked to an increased atomization of the task, as shown by the frequency of consultations.

Fault Detection and Prediction for Power Transformers Using Fuzzy Logic and Neural Networks

Transformers are indispensable in the industry sector and society in general, as they play an important role in power distribution, allowing the delivery of electricity to different loads and locations. Because of their great importance, it is necessary that they have high reliability, so that their failure does not cause additional losses to the companies. Inside a transformer, the primary and secondary turns are insulated by oil. Analyzing oil samples, it is possible to diagnose the health status or type of fault in the transformer. This paper combines Fuzzy Logic and Neural Network techniques, with the main objective of detecting and if possible predicting failures, so that the maintenance technicians can make decisions and take action at the right time. The results showed an accuracy of up to 95% in detecting failures. This study also highlights the importance of predictive maintenance and provides a unique approach to support decision-making for maintenance technicians.

A case study of factors impacting fatigue in aircraft maintenance technicians (AMT)

Purpose: When we talk about "fatigue" in aviation maintenance, it's a term that is widely used but can have different meanings depending on the situation. In the context of maintenance personnel, "fatigue" can encompass physical tiredness, emotional exhaustion, the decline in skills from performing mentally demanding tasks over a long period, chronic fatigue due to insufficient rest, and even the unmet need for sleep. So, it's crucial to consider the specific context of aviation maintenance when discussing fatigue and its implications. Design: The research for this study is conducted by gathering information from a variety of sources, including case studies, journal articles, magazines, books, and internet searches. These secondary sources offer valuable insights that contribute to the overall understanding of the topic. Findings: The study investigates factors contributing to fatigue in Aviation Maintenance Technicians (AMTs). Findings reveal that irregular and extended working hours, compounded by unpredictable schedules, contribute to persistent fatigue. High workload and time pressure amplify mental and physical strain, posing risks to safety. Sleep disruption and circadian rhythm disturbances adversely affect cognitive abilities. Environmental factors, including noise and harsh weather conditions, contribute to overall fatigue. Cumulative fatigue resulting from consecutive workdays without sufficient recovery time raises safety concerns. Organizational culture and support significantly impact AMT's experiences of fatigue, emphasizing the importance of a supportive work environment. Originality Value: This study takes a distinctive approach to examining the complex aspects of fatigue in aviation maintenance. It provides a comprehensive understanding by considering various factors that contribute to fatigue and their potential impact.