Hasil untuk "Industrial safety. Industrial accident prevention"

Christophe Ponsard, Abiola Paterne Chokki, Jean-François Daune

Cyber-Physical Systems (CPS) play a critical role in modern industrial domains, including manufacturing, energy, transportation, and healthcare, where they enable automation, optimization, and real-time decision-making. Ensuring the robustness of these systems is paramount, as failures can have significant economic, operational, and safety consequences. This paper present findings from an industrial survey conducted in Wallonia, covering a wide range of sectors, to assess the current state of practice in CPS robustness. It investigates robustness from how it is understood and applied in relationship with requirements engineering, system design, test execution, failure modes, and available tools. It identifies key challenges and gaps between industry practices and state-of-the-art methodologies. Additionally, it compares our findings with similar industrial surveys from the literature.

Annemarie Jutte, Uraz Odyurt

Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability critically important. Machine Learning (ML), specifically deep learning, is increasingly integrated in industrial CPS, but the inherent complexity of ML models results in non-transparent operation. Rigorous evaluation is needed to prevent models from exhibiting unexpected behaviour on future, unseen data. Explainable AI (XAI) can be used to uncover model reasoning, allowing a more extensive analysis of behaviour. We apply XAI to to improve predictive performance of ML models intended for industrial CPS. We analyse the effects of components from time-series data decomposition on model predictions using SHAP values. Through this method, we observe evidence on the lack of sufficient contextual information during model training. By increasing the window size of data instances, informed by the XAI findings, we are able to improve model performance.

A. Shcherbakov, Rasulya I. Khusnoyarova, Alyana A. Fazlyeva et al.

This article provides a comprehensive analysis of the legal regulation of hazardous industrial facilities (HIFs) in the context of current Russian legislation. It examines the legislative framework governing safety and emphasizes the importance of strict adherence to established standards for accident prevention and environmental protection. One of the documents coordinating safety at HIFs in Russia is Federal Law No. 116 «On Industrial Safety of Hazardous Industrial Facilities». The article also mentions additional regulations, such as licensing and insurance laws, which provide a comprehensive approach to regulation in this area, federal norms and rules, state standards, and Article 9.1 of the Code of Administrative Offenses of the Russian Federation. It emphasizes the need for a systematic approach to industrial safety and continued work to improve regulatory documents. Compliance with industrial safety rules established by regulatory documents is extremely important, as these regulations define mandatory requirements aimed at preventing accidents, protecting the lives and health of employees, and protecting the environment. The article also examines and proposes methods and options for improving regulatory documents in order to increase the level of industrial safety.

V. A. Gart

Introduction. Modernization of production facilities, with increased automation and complexity of technological processes, leads to a greater psychophysiological burden on workers and a higher likelihood of errors. This, in turn, increases the risk of occupational injuries. The increasing number of workplace accidents underscores the economic and social importance of accident prevention, as injuries reduce productivity and increase compensation costs. Modern approaches to occupational risk management require a systematic assessment of not only the probability of an incident and the severity of its consequences, but also the state of protective mechanisms — safety barriers that limit the impact of hazardous factors. Haddon's methodology, originally developed for transportation safety, can be used to identify weak links and analyze the sequence of incidents. Its barrier-oriented principles are theoretically applicable to industrial environments. However, existing research on barrier models in industry is fragmented and does not provide a unified tool for quantifying the effectiveness of barriers and their contribution to reducing injury risks. Therefore, the aim of this study is to develop a method for applying a barrier-oriented approach based on the Haddon model for a comprehensive quantitative assessment of personnel injury risks. Materials and Methods. A barrier safety model was used to solve the problem of reducing occupational injuries. The study consisted of three parts. The first was a comprehensive analysis of the requirements of Russian legislation in the field of occupational risk assessment, as well as scientific publications on the use of a barrier-oriented approach. The second was the description of the methodology for determining the likelihood of a hazard based on the results of an assessment of the reliability of safety barriers. The assessment of safety barriers was conducted according to checklists using the adapted Haddon model. Finally, an illustration of practical application of barrier approach using model example was provided. Results. A methodology for using a barrier-oriented approach to assess injury risks has been developed. A method for quantifying the impact of current hazards has been defined, taking into account the reliability of safety barriers. Risk levels for the hazard realization have been determined. Both the methodological principles proposed in this study and those already applied have been considered, indicating their advantages and limitations. An example of calculating the probability of hazards occurring when lifting and moving goods using hoisting devices has been given. Discussion. The presented methodology for applying the barrier-oriented approach allows us to take into account the influence of organizational factors and human factor on the safety of production processes and to obtain quantitative estimates of the possibility of hazard occurrence. Additionally, this approach provides a comprehensive assessment of safety barriers, considering not only their presence and effectiveness, but also reliability indicators — efficiency and sustainability of operation. This creates a basis for simplifying the process of prioritizing injury prevention measures and optimizing occupational risk management systems. Conclusion. The main results of the research include a practical way to calculate the probability of hazardous production factors, as well as recommendations for gradual implementation of the developed methodology into the practice of occupational safety and health management. The practical significance of this work lies in its potential for integration of the proposed approach with operational monitoring tools in the field of occupational safety and health and in its applicability to solving problems related to worker injury risk management in various production conditions.

Muhammad Junaid Asif, Abdul Rehman, Asim Mehmood et al.

This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technology based on wireless communication. We proposed a system based on NRF transceivers to establish a strong Wireless Sensor Network (WSN), enabling transfer of real-time data from multiple sensors to a central setup that is driven by ARDUINO microcontrollers. Different key parameters, crucial for industrial setup such as temperature, humidity, soil moisture and fire detection, are monitored and displayed on an LCD screen, enabling factory administration to oversee the industrial operations remotely over the internet. Our proposed system bypasses the need for physical presence for monitoring by addressing the shortcomings of conventional wired communication systems. Other than monitoring, there is an additional feature to remotely control these parameters by controlling the speed of DC motors through online commands. Given the rising incidence of industrial fires over the worldwide between 2020 and 2024 due to an array of hazards, this system with dual functionality boosts the overall operational efficiency and safety. This overall integration of IoT and Wireless Sensor Network (WSN) reduces the potential risks linked with physical monitoring, providing rapid responses in emergency scenarios, including the activation of firefighting equipment. The results show that innovations in wireless communication perform an integral part in industrial process automation and safety, paving the way to more intelligent and responsive operating environments. Overall, this study highlights the potential for change of IoT-enabled systems to revolutionize monitoring and control in a variety of industrial applications, resulting in increased productivity and safety.

Camille François, Ludovic Péran, Ayah Bdeir et al.

The rapid rise of open-weight and open-source foundation models is intensifying the obligation and reshaping the opportunity to make AI systems safe. This paper reports outcomes from the Columbia Convening on AI Openness and Safety (San Francisco, 19 Nov 2024) and its six-week preparatory programme involving more than forty-five researchers, engineers, and policy leaders from academia, industry, civil society, and government. Using a participatory, solutions-oriented process, the working groups produced (i) a research agenda at the intersection of safety and open source AI; (ii) a mapping of existing and needed technical interventions and open source tools to safely and responsibly deploy open foundation models across the AI development workflow; and (iii) a mapping of the content safety filter ecosystem with a proposed roadmap for future research and development. We find that openness -- understood as transparent weights, interoperable tooling, and public governance -- can enhance safety by enabling independent scrutiny, decentralized mitigation, and culturally plural oversight. However, significant gaps persist: scarce multimodal and multilingual benchmarks, limited defenses against prompt-injection and compositional attacks in agentic systems, and insufficient participatory mechanisms for communities most affected by AI harms. The paper concludes with a roadmap of five priority research directions, emphasizing participatory inputs, future-proof content filters, ecosystem-wide safety infrastructure, rigorous agentic safeguards, and expanded harm taxonomies. These recommendations informed the February 2025 French AI Action Summit and lay groundwork for an open, plural, and accountable AI safety discipline.

Mariia Sulimovska

У статті сформульовано актуальне завдання оцінювання захищеності інформації з обмеженим доступом, яка циркулює в підсистемі органів військового управління системи управління оперативного угруповання військ (сил) під час виконання операцій у зоні проведення бойових дій та запропоновано її вирішення. Аналіз функціонування оперативного угруповання військ (сил) підтверджує, що ця проблема є актуальною і потребує вирішення в умовах широкомасштабної збройної агресії російської федерації проти України. Метою статті є вдосконалення методики оцінювання захищеності інформації з обмеженим доступом, яка циркулює в підсистемі органів військового управління, що здійснене для запобігання витоку інформації та недопущення втрати її матеріальних носіїв й унеможливлення використання цих відомостей противником. Методи дослідження: системний аналіз, метод моделювання, експертні оцінки, метод порівняльного аналізу, метод SWOT-аналізу, метод статистичного аналізу, метод сценарного аналізу. Зазначений методологічний підхід дав змогу належно оцінити захищеність інформації з обмеженим доступом. Аналіз останніх досліджень і публікацій, присвячених оцінюванню захищеності інформації свідчить про необхідність актуалізації та вдосконалення такого оцінювання з урахуванням загроз захищеності, зумовлених високою динамікою бойових дій. У статті показано, що вирішення цієї проблеми потребує системного підходу та ефективного застосування показників оцінювання захищеності інформації з обмеженим доступом в підсистемі органів військового управління. Запропоновано визначення коефіцієнту захищеності інформації з обмеженим доступом, який характеризує ступінь ефективності функціонування системи забезпечення захисту інформації в підсистемі органів військового управління під час виконання операцій. Цей показник обмежується статтями Зводу відомостей, що становить державну таємницю та пунктами Переліку службової інформації, що належать до структур сектору оборони України (Збройних Сил України та Міністерства оборони України). Удосконалена методика оцінювання захищеності інформації з обмеженим доступом складається з восьми блоків, що охоплюють формування вихідних даних, розрахунок коефіцієнтів захищеності та оцінку потенційної шкоди від витоку інформації або втрати відомостей. Методика також передбачає виявлення причин невідповідності вимогам, розробку рекомендацій для підвищення ефективності забезпечення захисту та визначення загального рівня безпеки інформації. Її реалізація дає змогу забезпечити відповідність системи забезпечення захисту інформації з обмеженим доступом в підсистемі органів військового управління встановленим вимогам та мінімізувати ризики втрати матеріальних носіїв інформації. Науковою новизною є впровадження чотирьохступеневої системи обмеження доступу до інформації з грифами секретності «Особливо важливо», «Цілком таємно», «Таємно» та грифом обмеження доступу «Для службового користування». Ця система передбачена в проєкті Закону України «Про безпеку класифікованої інформації» з урахуванням положень Стратегії національної безпеки України, стандартів безпеки НАТО та Європейського Союзу. Її впровадження дає змогу створити нову методику оцінювання захищеності інформації з обмеженим доступом та вдосконалити нормативно-правову базу. Удосконалена методика сприяє розвитку теорії безпеки інформації, впроваджуючи міжнародні стандарти НАТО та Європейського Союзу в контексті національної оборони України. Це дає змогу створити уніфіковану систему оцінювання захищеності інформації та адаптувати підходи до оцінювання захищеності інформації з урахуванням сучасних загроз і специфіки оперативного середовища. Практична значущість методики надає можливість своєчасно оцінювати рівень захищеності інформації, виявляти причини виникнення загроз і розробляти заходи для мінімізації ризиків витоку або втрати відомостей. Її впровадження підвищує ефективність управління оперативним угруповання військ (сил) в зоні проведення бойових дій. Напрямом подальших досліджень є удосконалення моделі оцінювання шкоди оперативному угрупованню військ (сил) у разі витоку інформації з обмеженим доступом, яка циркулює в підсистемі органів військового управління, а також розробка та впровадження відповідних положень у нормативно-правові акти, що регламентують організацію та забезпечення безпеки інформації.

Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy et al.

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. In this article, we present a comprehensive survey of the emerging DT-enabled services and applications across industries, beginning with an overview of DT fundamentals and its components to a discussion of key enabling technologies for DT. Different from literature works, we investigate and analyze the capabilities of DT across a wide range of industrial services, including data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. In particular, we present an in-depth technical discussion of the roles of DT in industrial applications across various domains, including manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Throughout the technical analysis, we delve into real-time data communications between physical and virtual platforms to enable industrial DT networking. Subsequently, we extensively explore and analyze a wide range of major privacy and security issues in DT-based industry. Taxonomy tables and the key research findings from the survey are also given, emphasizing important insights into the significance of DT in industries. Finally, we point out future research directions to spur further research in this promising area.

Tomislav Duricic, Peter Müllner, Nicole Weidinger et al.

Many industrial sectors rely on well-trained employees that are able to operate complex machinery. In this work, we demonstrate an AI-powered immersive assistance system that supports users in performing complex tasks in industrial environments. Specifically, our system leverages a VR environment that resembles a juice mixer setup. This digital twin of a physical setup simulates complex industrial machinery used to mix preparations or liquids (e.g., similar to the pharmaceutical industry) and includes various containers, sensors, pumps, and flow controllers. This setup demonstrates our system's capabilities in a controlled environment while acting as a proof-of-concept for broader industrial applications. The core components of our multimodal AI assistant are a large language model and a speech-to-text model that process a video and audio recording of an expert performing the task in a VR environment. The video and speech input extracted from the expert's video enables it to provide step-by-step guidance to support users in executing complex tasks. This demonstration showcases the potential of our AI-powered assistant to reduce cognitive load, increase productivity, and enhance safety in industrial environments.

Jinfan Liu, Yichao Yan, Junjie Li et al.

Video anomaly detection (VAD) is a challenging task aiming to recognize anomalies in video frames, and existing large-scale VAD researches primarily focus on road traffic and human activity scenes. In industrial scenes, there are often a variety of unpredictable anomalies, and the VAD method can play a significant role in these scenarios. However, there is a lack of applicable datasets and methods specifically tailored for industrial production scenarios due to concerns regarding privacy and security. To bridge this gap, we propose a new dataset, IPAD, specifically designed for VAD in industrial scenarios. The industrial processes in our dataset are chosen through on-site factory research and discussions with engineers. This dataset covers 16 different industrial devices and contains over 6 hours of both synthetic and real-world video footage. Moreover, we annotate the key feature of the industrial process, ie, periodicity. Based on the proposed dataset, we introduce a period memory module and a sliding window inspection mechanism to effectively investigate the periodic information in a basic reconstruction model. Our framework leverages LoRA adapter to explore the effective migration of pretrained models, which are initially trained using synthetic data, into real-world scenarios. Our proposed dataset and method will fill the gap in the field of industrial video anomaly detection and drive the process of video understanding tasks as well as smart factory deployment.

An Guo, Yuan Zhou, Haoxiang Tian et al.

Autonomous driving systems (ADSs) have undergone remarkable development and are increasingly employed in safety-critical applications. However, recently reported data on fatal accidents involving ADSs suggests that the desired level of safety has not yet been fully achieved. Consequently, there is a growing need for more comprehensive and targeted testing approaches to ensure safe driving. Scenarios from real-world accident reports provide valuable resources for ADS testing, including critical scenarios and high-quality seeds. However, existing scenario reconstruction methods from accident reports often exhibit limited accuracy in information extraction. Moreover, due to the diversity and complexity of road environments, matching current accident information with the simulation map data for reconstruction poses significant challenges. In this paper, we design and implement SoVAR, a tool for automatically generating road-generalizable scenarios from accident reports. SoVAR utilizes well-designed prompts with linguistic patterns to guide the large language model in extracting accident information from textual data. Subsequently, it formulates and solves accident-related constraints in conjunction with the extracted accident information to generate accident trajectories. Finally, SoVAR reconstructs accident scenarios on various map structures and converts them into test scenarios to evaluate its capability to detect defects in industrial ADSs. We experiment with SoVAR, using accident reports from the National Highway Traffic Safety Administration's database to generate test scenarios for the industrial-grade ADS Apollo. The experimental findings demonstrate that SoVAR can effectively generate generalized accident scenarios across different road structures. Furthermore, the results confirm that SoVAR identified 5 distinct safety violation types that contributed to the crash of Baidu Apollo.

Jonas Rafi, Petra Lindfors, Per Carlbring

Objectives: Responsible workplaces strive to minimize the harmful effects of alcohol and drug abuse. However, gambling is still a neglected area in workplace research. This study describes workplace gambling and investigates variables associated with at-risk and problem gambling (ARPG) and knowing about colleagues who gambles during work, using cross-sectional data from a cluster-randomized controlled trial on gambling prevention in the workplace (N=3,629). Methods: Measures included ARPG and knowledge about colleagues who gamble during work. Results: Of the respondents, 168 (4.7%) knew of someone who gambles at work. Knowing about a colleague who gambles during work was more common among employees who were men (odds ratio [OR] 2.98; 95% confidence interval [CI], 2.07–4.29), aged 16–34 years (OR 1.97; 95% CI, 1.19–3.28), knew about a gambling policy (OR 1.57; 95% CI, 1.03–2.39), and who themselves were classified as ARPGs (OR 2.95; 95% CI, 1.60–5.35). Similarly, being classified as an ARPG was significantly associated with being a man (OR 2.14; 95% CI, 1.43–3.20), aged 16–34 (OR 2.35; 95% CI, 1.21–4.54) or 35–44 (OR 2.36; 95% CI, 1.30–4.27) years, being a subordinate (OR 2.53; 95% CI, 1.02–6.30), and knowing about a colleague who gambles during work (OR 4.02; 95% CI, 2.38–6.79). Conclusions: Gambling during work is a prevalent phenomenon. Organizations should consider implementing gambling policies that facilitate helping workers who are problem gamblers. To determine policy contents and measures to implement, the type of gambling and its effect on employees should be explored.

Kaira Devi, Priskila Hananingrum, Y. Denny A. Wahyudiono

Introduction:Work stress can occur in many professions, including nursing, which is inseparable from individual characteristics. Inpatient is one of the units at Ploso Regional Public Hospital, Jombang, which has time-consuming work that requires observation on an ongoing basis. This study aimed to understand the relationship between individual characteristics, such as age, gender, marital status, working period, and personality type, with the level of work stress experienced by the inpatient installation unit nurses at Ploso Regional Public Hospital, Jombang. Methods: Observational descriptive study was applied with a cross-sectional design. Age, gender, marital status, working period, and personality type were the independent variables used in this study, while the dependent variable was work stress. The sample used was the total accessible population of nurses in the inpatient unit with 33 respondents. The data collection method used was a general questionnaire for personal variables (age, gender, marital status, working period), Personality Type Questionnaire for personality type, and Health and Safety Executive (HSE) Questionnaire for work stress. Data were analyzed using chi-square correlation and spearman correlation test. Results: In the inpatient installation unit, most nurses were male between the ages of 24-37, had a working period of less than five years, were married, and had type A personality. The individual characteristics which had a moderate relationship with work stress were age (ρ = 0.419), marital status (ρ = 0.461), and working period (ρ = 0.359). Gender (ρ = 0.246) and personality type (ρ = 0.179) had a weak relationship with work stress. Conclusion: Age, marital status, and working period had a moderate relationship with work stress, while gender and personality type had a weak relationship.

Ankush Meshram, Markus Karch, Christian Haas et al.

Since 2010, multiple cyber incidents on industrial infrastructure, such as Stuxnet and CrashOverride, have exposed the vulnerability of Industrial Control Systems (ICS) to cyber threats. The industrial systems are commissioned for longer duration amounting to decades, often resulting in non-compliance to technological advancements in industrial cybersecurity mechanisms. The unavailability of network infrastructure information makes designing the security policies or configuring the cybersecurity countermeasures such as Network Intrusion Detection Systems (NIDS) challenging. An empirical solution is to self-learn the network infrastructure information of an industrial system from its monitored network traffic to make the network transparent for downstream analyses tasks such as anomaly detection. In this work, a Python-based industrial communication paradigm-aware framework, named PROFINET Operations Enumeration and Tracking (POET), that enumerates different industrial operations executed in a deterministic order of a PROFINET-based industrial system is reported. The operation-driving industrial network protocol frames are dissected for enumeration of the operations. For the requirements of capturing the transitions between industrial operations triggered by the communication events, the Finite State Machines (FSM) are modelled to enumerate the PROFINET operations of the device, connection and system. POET extracts the network information from network traffic to instantiate appropriate FSM models (Device, Connection or System) and track the industrial operations. It successfully detects and reports the anomalies triggered by a network attack in a miniaturized PROFINET-based industrial system, executed through valid network protocol exchanges and resulting in invalid PROFINET operation transition for the device.

Tianyu Zhang, Gang Wang, Chuanyu Xue et al.

With the introduction of Cyber-Physical Systems (CPS) and Internet of Things (IoT) technologies, the automation industry is undergoing significant changes, particularly in improving production efficiency and reducing maintenance costs. Industrial automation applications often need to transmit time- and safety-critical data to closely monitor and control industrial processes. Several Ethernet-based fieldbus solutions, such as PROFINET IRT, EtherNet/IP, and EtherCAT, are widely used to ensure real-time communications in industrial automation systems. These solutions, however, commonly incorporate additional mechanisms to provide latency guarantees, making their interoperability a grand challenge. The IEEE 802.1 Time Sensitive Networking (TSN) task group was formed to enhance and optimize IEEE 802.1 network standards, particularly for Ethernet-based networks. These solutions can be evolved and adapted for cross-industry scenarios, such as large-scale distributed industrial plants requiring multiple industrial entities to work collaboratively. This paper provides a comprehensive review of current advances in TSN standards for industrial automation. It presents the state-of-the-art IEEE TSN standards and discusses the opportunities and challenges of integrating TSN into the automation industry. Some promising research directions are also highlighted for applying TSN technologies to industrial automation applications.

Zeyi Liu, Songqiao Hu, Xiao He

Real-time safety assessment (RTSA) of dynamic systems is a critical task that has significant implications for various fields such as industrial and transportation applications, especially in non-stationary environments. However, the absence of a comprehensive review of real-time safety assessment methods in non-stationary environments impedes the progress and refinement of related methods. In this paper, a review of methods and techniques for RTSA tasks in non-stationary environments is provided. Specifically, the background and significance of RTSA approaches in non-stationary environments are firstly highlighted. We then present a problem description that covers the definition, classification, and main challenges. We review recent developments in related technologies such as online active learning, online semi-supervised learning, online transfer learning, and online anomaly detection. Finally, we discuss future outlooks and potential directions for further research. Our review aims to provide a comprehensive and up-to-date overview of real-time safety assessment methods in non-stationary environments, which can serve as a valuable resource for researchers and practitioners in this field.

Yuan Luo, Song Han, Jingjing Liu

Machine learning is expected to enable the next Industrial Revolution. However, lacking standardized and automated assembly networks, ML faces significant challenges to meet ever-growing enterprise demands and empower broad industries. In the Perspective, we argue that ML needs to first complete its own Industrial Revolution, elaborate on how to best achieve its goals, and discuss new opportunities to enable rapid translation from ML's innovation frontier to mass production and utilization.

Hamid AKBARI, Fahimeh SARBANDI

Introduction: The productivity of an organization is closely related to the improvement of the safety and health of employees and the development of knowledge and skills of human resources in advancing the organization goals. Based on a combination of questionnaire and survey, this study examines the impact of implementing safety management practices on the performance and job satisfaction of employees in Iran's production units. Research Method: This descriptive-cross-sectional study was conducted in 1400 on 200 employees and managers of the Hacoupian clothing industrial company located in Tehran province. 130 of them were selected based on random sampling using the Morgan table. Data collection tools included a researcher-made questionnaire, which was further confirmed by experts by applying their opinions regarding its validity and reliability. It was approved by experts. The analysis method in this study is mainly descriptive and the type of research is relational. Data and research hypotheses were respectively tested using Structural equation modeling (SEM) and Partial least squares (PLS) approach through SPSS26 software. Results: Findings showed the appropriate fit of measurement and structural models. In addition, results demonstrated the positive effect of improving safety on the job satisfaction of employees in production units, as well as the negative effects of not paying attention to the health of the working environment on the quality of employees' performance. Conclusion: The more companies and governments pay attention to the issue of operational health and safety, the organizational and environmental situation will be formed in such a way that it will optimally motivate employees and increase the quality of production and operations in the organization.

Ahmed Bassam Al-Arnous, Nadia Abdelhamid Abdelmegeed Abdelwahed

Even in the best-case scenarios, working in the energy sector is tough because of the numerous possible risks that can arise during routine tasks. Therefore, the top priority of firms’ management is their responsibilities for their employees’ safety as they undertake various roles. In this study, the researchers investigated the effect of safety measures on the safety accountability (SA) of the Saudi Arabian Aramco Company’s frontline workers. The researchers used a quantitative approach and collected data through a survey questionnaire. We applied a random sampling technique to target the company’s frontline workers. Initially, the researchers distributed 450 questionnaires and received back 242 valid samples. This represented a 53% response rate. Next, the researchers applied Structural Equation Modeling (SEM) to assess the directions of the hypothesized paths. This study’s findings demonstrate that safety policy (SP), safety training (ST), safety communication (SC), safety commitment (SCT) and safety incentives (SIs) have positive and significant effects on frontline workers’ safety accountability (SA). In addition, this study’s findings provide guidelines to policy makers, government authorities and company heads to implement further initiatives that adopt precautionary and safety measures to protect their frontline workers’ lives. Further, this study’s findings show the benefits of opening avenues of research to concentrate on safety measures such SP, ST, SC, SCT and SIs in order to create the frontline workers’ responsibilities for safety accountability (SA). Finally, the empirical evidence, which the researchers obtained from the Aramco Company’s frontline workers, adds to the depth of knowledge on this subject; validates the environmental science and management literature; and provides road maps for other companies to investigate safety challenges

Nala Astari Pramesti, Shintia Yunita Arini

Introduction: Asosiasi untuk Demokrasi dan Kesejahteraan Sosial (Ademos) was founded as a form of anxiety towards rural communities whose majority of the population does not receive enough attention and access to economic development. One of the empowerment programs is a program to improve the quality of the Bojonegoro batik craftsmen. Workers can work more than 8 hours a day in a sitting and bending position for long periods of time. This study aimed to determine the correlation between the length of work and exercise routines on musculoskeletal complaints among batik craftsmen of Ademos, Bojonegoro Regency. Methods: This research was a descriptive analytic study using a cross-sectional design. The research was conducted in July-August 2020 on Ademos batik craftsmen in Bojonegoro Regency. The total population of the study was 42 batik craftsmen who were selected using a total sampling technique. The variables studied included tenure, exercise routines, and musculoskeletal complaints. Data collection was carried out through questionnaire sheets, observations and the Nordic Body Map Questionnaire. Results: The results of the study found that there was a significant correlation between working period and musculoskeletal complaints (p=0.032) experienced by Batik craftsmen of Ademos Bojonegoro. On the other hand, there was no correlation found between exercise routines and musculoskeletal complaints (p=0.361) on Batik craftsmen of Ademos Bojonegoro. Conclusion: The significant factor causing musculoskeletal complaints in Ademos Bojonegoro Batik craftsmen was the working period factor.