Safety Analysis Techniques Research Articles

Analisis Break Even Point dan Margin Of Safety Sebagai Alat Perencanaan Laba pada UMKM Bakmie Sultan Karawang

In principle, the main goal of every company is to achieve optimal profits for its owners. To be able to compete effectively with other companies, companies need to improve their operational performance more efficiently and effectively. Bakmie Sultan Karawang, a developing MSME business, still does not have accurate information regarding the profits generated from minimum sales of their noodles. This research aims to explore the role of Break Even Point (BEP) analysis in planning and increasing company profits. This research method uses a quantitative descriptive approach by applying BEP and Margin of Safety analysis techniques. The results of the break even point analysis show that the total business BEP reached Rp. 94,267,790.38, with details for each product Bakmie Komplit, Bakmie Bakso, Bakmie Pangsit, Bakmie Manis, and Bakmie Regular. Msargin of Safety (MOS) reached 93.03%, equivalent to Rp. 1,258,132,209.62, gives an idea of how much of a decline in sales can be handled without incurring a loss or breaking even. The estimated profit target for 2024 is 30%, or Rp. 177,263,404,629, which is a guide for the company in achieving the expected profit. Recommendations are provided so that companies can optimize BEP strategies to maintain sales above the break-even point and reduce potential losses. It is hoped that the results of this research will provide support for companies in designing optimal profit plans through BEP and MOS analysis.

Classification of traffic accidents’ factors using TrafficRiskClassifier

The TrafficRiskClassifier model introduced in this study adopts an innovative approach that incorporates migration learning, image classification, and self-supervised learning, aiming to significantly improve the accuracy and efficiency of traffic accident risk analysis. Compared with traditional traffic safety analysis techniques, this model focuses on utilizing contextual information and situational data of traffic accidents to achieve a higher level of risk classification accuracy. The core of this approach is to deeply mine and analyze the detailed information in the accident environment, to provide more scientific and effective support for traffic accident risk prevention and response. Initially, by integrating migration learning with image classification techniques, the model proficiently extracts pivotal features from intricate traffic scenarios and formulates initial assessments of accident risks. Subsequently, self-supervised learning is incorporated in this study, augmenting the model's capability to comprehend and categorize accident imagery. The TrafficRiskClassifier model exhibits a generalization ability of 91.82%, 85.16%, and 80.92% on individual classification tasks, respectively, signifying its robust learning capacity and proficiency in managing unseen data. Furthermore, the TrafficRiskClassifier model delineates a functional nexus between accident risk and variables such as weather, road conditions, and personal factors, employing a polynomial regression approach. This methodology not only amplifies the predictive precision of the model but also renders it versatile across diverse scenarios. Through the analysis of various polynomial functions, the model achieves enhanced accuracy in classifying disparate risk levels. The outcomes demonstrate that the TrafficRiskClassifier model can efficaciously amalgamate contextual information within traffic scenarios, thereby achieving more precise classification of traffic accident risks, and consequently serving as an invaluable instrument for urban traffic safety management.

STPA-RL: Integrating Reinforcement Learning into STPA for Loss Scenario Exploration

Experience-based methods like reinforcement learning (RL) are often deemed less suitable for the safety field due to concerns about potential safety issues. To bridge this gap, we introduce STPA-RL, a methodology that integrates RL with System-Theoretic Process Analysis (STPA). STPA is a safety analysis technique that identifies causative factors leading to unsafe control actions and system hazards through loss scenarios. In the context of STPA-RL, we formalize the Markov Decision Process based on STPA analysis results to incorporate control algorithms into the system environment. The agent learns safe actions through reward-based learning, tracking potential hazard paths to validate system safety. Specifically, by analyzing various loss scenarios related to the Platform Screen Door, we assess the applicability of the proposed approach by evaluating hazard trajectory graphs and hazard frequencies in the system. This paper streamlines the RL process for loss scenario identification through STPA, contributing to self-guided loss scenarios and diverse system modeling. Additionally, it offers effective simulations for proactive development to enhance system safety and provide practical assistance in the safety field.

Guidelines for Raman spectroscopy and imaging techniques in food safety analysis

AbstractEnsuring the highest standards of food quality and safety is crucial for maintaining human health. This requires the creation of sophisticated and highly sensitive techniques for detecting and identifying food pollutants. Raman spectroscopy, known for its rapidity, simplicity, sensitivity, and noninvasive characteristics, has become a prominent method in the field of food safety and quality analysis. This review discusses in detail the fundamental principles, instruments, methodology, and data processing techniques of Raman spectroscopy. It specifically emphasizes the practical applications of Raman spectroscopy in assessing foodborne pathogens, toxic gases in spoiled foods, and monitoring the translocation of pesticide in plants. Finally, we discussed the development trend and challenges of Raman spectroscopy in the field of food safety analysis, aiming to provide an accessible and practical guide. This review article equips readers with essential insights into conducting and understanding Raman spectroscopy experiments, thereby contributing to development in the field of food safety analysis.

ADSA – Association-Driven Safety Analysis to Expose Unknown Safety Issues

Autonomous systems are susceptible to unknown safety issues due to overlooked dependencies among components of the system and the entities that are part of its operating environment. The current safety analysis techniques aids in identifying known safety issues but not overlooked/unknown safety issues. To identify unknown safety issues due to problematic interactions between components, in our previous work, we proposed safety assessment for concurrent components (SACC). Despite being more effective than FMEA and goal modeling, SACC suffers from some limitations such as not considering environmental entities and their properties, and a manual process for identifying associated components for the collective analysis. For a complex system with a large number of components, such an analysis can result in overlooking safety issues. To address these limitations, in this paper, we propose an association-driven safety analysis (ADSA) approach, which is extended and built on SACC. The approach uses a property-relation (PR) table and modified association rule mining algorithm to identify components and environmental entities that need to be considered together to detect overlooked or unknown safety issues. We evaluated our approach using four robotic systems and compared with SACC and systems theoretic process analysis (STPA). Our results show that our proposed approach, in particular using behavioral dependencies, is effective at exposing unknown safety issues.

Aligning Stakeholders and Actors: A New Safety and Security-Based Design Approach for Major National Infrastructures

This study introduces a systems-theoretic methodology to meet the requirements of a major national infrastructure for safety and security-based design by enhancing the alignment of stakeholders and actors in the project. Safe-by-Design (SbD) is an engineering concept for risk management that considers safety as much as possible in the design phase. The article presents the results of a case study conducted to investigate the efficacy of recent system safety models and analysis techniques in the major national infrastructure of a Waste-to-Energy (WtE) project under consideration in Iceland. The structures and roles within the system responsible for constructing the WtE plant, given the sustainability and circular economy restrictions, are addressed in the study. Stakeholders’ roles and responsibilities are analyzed, yielding their feedback on potential risks and creating a positive image of the project. Also, suitable ways to enter the project and finance it are devised. In essence, this enables the creation of a safety and security-based design approach. Furthermore, detailed documentation of the system model development is presented. The novelty of the study lies in the application of STAM, STPA, and STECA as an SbD approach for a major infrastructure project. Also, the methods discussed here have not been used in a WtE project as far as we know.

A systematic co-engineering of safety and security analysis in requirements engineering process

Co-engineering safety and security is increasingly important in safety-critical systems as more diverse interacting functions are implemented in software. Many studies have tried to perform safety and security analyses in unified or in parallel. While the unified approach requires more complex analysis with new delicate methods, the parallel needs further improvement on additional integration activity for harmonizing safety and security analyses results. This paper tries to improve the harmonization activity seamlessly and systematically in typical requirements engineering process for safety-critical systems. It encompasses both requirements elicitation and analysis as well as safety and security analyses, regardless of which analysis techniques are used. The paper suggests performing an appropriate safety analysis first to derive safety requirements as summary information. It then performs goal-tree analysis to refine the high-level safety requirements into lower-level ones, from which any security analysis can work on to derive security requirements. Another goal-tree analysis then tries to refine the high-level security requirements into specific functional ones too, and it ends the analysis activity in a cycle of requirements engineering process. The sequence of safety analysis, goal-tree refinement, security analysis and another goal-tree refinement is seamlessly iterated in the process of requirements engineering, where any conflict of requirements will have an opportunity to be resolved. Our case study of a simplified UAV example uses STPA and STRIDE techniques for safety and security analysis respectively, and shows that the proposed approach is fully applicable up to industrial cases.

Structured Description of Autonomous Inland Waterway Barge Operations

Autonomous and unmanned shipping is revolutionizing the maritime industry by introducing a paradigm shift on how to design the vessels and supporting land-side infrastructure. Currently, there is a lack of formalisms on how to plan for such operations, determining the varying degrees of autonomy and human responsibility, whilst ensuring safety and security. This paper describes fundamental concepts of autonomy in the context of ships. These are then applied in a methodology used to create systematic and structured descriptions for the operation of autonomous ship systems. The examples we use are based on ongoing efforts related to a planned autonomous inland waterway (IWW) barge operation. Finally, we show how the descriptions can be used in conjunction with existing safety and security analysis techniques. Our experience with this methodology is that it allows for a smooth transition from the autonomous ship system design phase to the assessment of the same system using UML notations. We believe that the same methodology can be easily applied to the other use cases and similar systems elsewhere.

Road Accident Severity Prediction using Machine Learning

Road accidents have become a major concern globally, causing a significant number of fatalities and injuries every year. The aim of this project is to predict road accidents severity using machine learning techniques, in order to reduce their occurrence and mitigate the associated risks. The project uses data collected from various sources such as accident reports, weather conditions, and road infrastructure to train and evaluate various supervised learning algorithms and predict the accident severity. Four algorithms were compared, including Decision Tree, Naive Bayes, Random forest . Most probably occurring road accident locations are identified and that particular region is indicated as black pot. The proposed method can be used to provide real-time risk information to road users, helping them to make informed decisions and avoid potential accidents. The project highlights the importance of using machine learning techniques in road safety analysis, providing a foundation for further research in this field

Progressive system safety and reliability analysis: A sustainable game theory approach

AbstractThis research aims to study the applicability of game theory to system safety and reliability decision‐making problems and corresponding objective conflicts using non‐cooperative games. The non‐cooperative games would solve the games considering non‐cooperative cognitive decision‐makers behaviors, which are commonly ignored by other system safety and reliability analysis (SSRA) techniques, assuming that there would be perfect cooperation between the players (decision‐makers). Game theory can also recognize and understand the decision‐makers' behaviors and provide a “win‐win” situation for all players and the best broader system outcomes. The paper also shows the use of dynamic game theory in system safety and reliability decision‐making problems over time. The results indicate the effectiveness and efficiency of game theory and show how this can better reflect decision‐makers’ opinions in system safety and reliability decision‐making problems.

JOB SAFETY ANALYSIS ON MANUFACTURING PROCESS OF HOUSE WIRES

The objective of this project is to analysis of hazards in the process of house wire manufacturing in VGuard industries limited Coimbatore for the purpose of improving safety in the workplace and promoting safety culture among the workers. Manufacturing process involves cold wire drawing process, copper cable bunching process, Insulation process, testing and material handling process all of this process having its own significant hazards. By using the Job safety analysis technique, the analysis was carriedout and the study is submitted as a report to V-Guard industries limited Coimbatore. Here the proposed practical solution in the sequence of Elimination, Substitution, Engineering control, Administrative control, and Personal Protective Equipment using the observation form Job Safety Analysis worksheet

Bayesian Networks based approach to enhance GO methodology for reliability modeling of multi-state consecutive-k-out-of-n: F system

As a success-oriented system reliability and safety analysis technique, GO methodology is widely used in the modeling and analysis scenarios of critical safety engineering systems with signal flow, such as nuclear, chemical industry, electric power transportation, wireless network and microwave communication network. Consecutive-k-out-of-n systems are also widely applied in these fields, but due to their relatively complex logic, there are no corresponding graphical modeling and calculation methods. In this paper, the basic GO methodology is extended to support the modeling and analysis of multi-state linear and circular consecutive-k-out-of-n: F system (MLC(k,n) &MCC(k,n)) models. Two new operators are defined in graphical modeling to represent the two types of complex system logic. The multi-state logic semantics of the new operators and mapping rules to Bayesian networks (BN) are given. And the programmable process is presented to transform the extended GO model into BN, and the reliability of the MLC(k,n)/MCC(k,n) is calculated. Finally, three cases are used to verify i) the correctness of the method supporting multi-state model, ii) the efficiency and ability of the algorithm, and iii) the forward calculation and reverse diagnosis of the MLC(k,n) and MCC(k,n) systems with external shared components.

Piloted Online Training Module to Teach On-Site Safety in Engineering


 
 
 Change in Australian engineering industry has caused difficulty for engineering students to secure placements and engage with engineering practice. Consequently, universities are developing learning modules using digital simulations to expose engineering students to authentic engineering practice as part of their curricula. Many simulations use technology such as virtual reality that is not accessible to students off campus without significant resource investment. One of the important elements of engagement with practice is learning about safety in engineering. With the use of work integrated learning and distance education frameworks, this study developed and evaluated the effectiveness of an online desktop-based learning environment that students could access off-campus, in delivering safety education and awareness, and the benefits of online learning. Fifteen engineering university students (6 female) participated in an optional module using a desktop-based industrial site simulation. Pre and post testing were used to evaluate effectiveness of the module. Results indicated that the module significantly improved understanding and application of the job safety analysis technique and improved on-site safety awareness. The use of flexible online education is versatile and effective. Students benefitted from desktop-based simulation experiences incorporating authentic engineering scenarios and tasks that could be accessed online.
 
 

Hazard Identification and Job Safety Analysis for Improving Occupational Health and Safety in Fishing Net Sinking Process in Southern Thailand

The fishing net sinker workers are exposed to numerous workplace hazards that can endanger their health and safety. We utilized a walk-through survey and Job Safety Analysis (JSA) technique to assess each step of the work process, identify potential hazards on each job and suggest the safest approach to fishing net sinker workers in southern Thailand. A JSA is a useful tool for mitigating risk in the workplace. It emphasizes the interaction between workers, tools or equipment, the working environment, and the tasks. The results show thata total of 52potential hazards occur with varying severity and likelihood, 20% of which are categorized at the highest level. The mesh and lead ball making activities carry an extreme risk rating (RR=12). This work has possible hazards, namely occupational lung and asthma disorders. 40% are categorized at the high-risk level, namely fingers cut by tools (RR=8), and repetitive strain disorder (RR=8). Workers can be more proactive in implementing health and safety measures through appropriate risk control. The result of the paired-sample’s t-test showed that the average risk scorediffers before taking control measures (M= 7.54, SD = 2.62)and after taking control measure(M= 4.31, SD = 1.55)at the 0.0001 level of significance (t= 7.6513, df = 51, n=52, P< 0.0001, 95% confidence interval of this difference 2.39 to 4.07). On an average, risk reduction was about 3.23 point lower after taking control measures.Ensuring that workers use tools and equipment safely and also that they maintain this equipment properly. Thus, it was suggested that the government agencies concerned should carry out regular surveillance and further develop the learning process and solutions to work safety procedures as guidelines to improve their safety, wellbeing, and working conditions. These enhancements will also contribute to the higher efficiency and effectiveness of their work and advance the dynamic interest and participation of the fishing net sinker workers in other areas, including careers for the informal workers of similar work characteristics.

SafeSoCPS: A Composite Safety Analysis Approach for System of Cyber-Physical Systems.

The System of Cyber-Physical Systems (SoCPS) comprises several independent Cyber-Physical Systems (CPSs) that interact with each other to achieve a common mission that the individual systems cannot achieve on their own. SoCPS are rapidly gaining attention in various domains, e.g., manufacturing, automotive, avionics, healthcare, transportation, and more. SoCPS are extremely large, complex, and safety-critical. As these systems are safety-critical in nature, it is necessary to provide an adequate safety analysis mechanism for these collaborative SoCPS so that the whole network of these CPSs work safely. This safety mechanism must include composite safety analysis for a network of collaborative CPS as a whole. However, existing safety analysis techniques are not built for analyzing safety for dynamically forming networks of CPS. This paper introduces a composite safety analysis approach called SafeSoCPS to analyze hazards for a network of SoCPS. In SafeSoCPS, we analyze potential hazards for the whole network of CPS and trace the faults among participating systems through a fault propagation graph. We developed a tool called SoCPSTracer to support the SafeSoCPS approach. Human Rescue Robot System—a collaborative system—is taken as a case study to validate our proposed approach. The result shows that the SafeSoCPS approach enables us to identify 18 percent more general faults and 63 percent more interaction-related faults in a network of a SoCPS.

A formal approach to support the identification of unsafe control actions of STPA for nuclear protection systems

STPA (System-Theoretic Process Analysis) is a widely used safety analysis technique to identify UCAs (Unsafe Control Actions) resulting in potential losses. It is totally dependent on the experience and ability of analysts to construct an information model called Control Structures, upon which analysts try to identify unsafe controls between system components. This paper proposes a formal approach to support the manual identification of UCAs, effectively and systematically. It allows analysts to mechanically extract Process Model, an important element that makes up the Control Structures, from a formal requirements specification for a software controller. It then concisely constructs the contents of Context Tables, from which analysts can identify all relevant UCAs effectively, using a software fault tree analysis technique. The case study with a preliminary version of a Korean nuclear reactor protections system shows the proposed approach's effectiveness and applicability.

Addressing process safety challenges in downstream industries in Brunei Darussalam

International oil and gas corporations operating in Brunei may apply process safety management (PSM) and analysis techniques, resulting in varying approaches and measures to address process safety issues. Global corporations may have developed their own process safety standards while smaller firms employ established ones. This research compares the local PSM systems and standards with international ones to determine which employers face the most difficulties in implementing or increasing process safety inside their organizations. This study found that Occupational Safety and Health Administration (OSHA) regulations are used by 30% of local users in downstream operations. Common challenges encountered by local users are management/leadership commitment to process safety (11.9%), mechanical integrity and management of safety critical devices (5.3%), management review and intervention for continuous improvement (4.9%), communication amongst workers (3.8%), management of change (3.8%), operational control, permit to work and risk management (3.8%) and incident reporting (3.8%).

Assessment of Job Risks in the Chemical Laboratory of the Pharmacy Study Program with Job Safety Analysis (JSA) Techniques

Chemistry laboratory organizes practicum, one of them quantitative pharmaceutical chemistry which uses a variety of chemicals and tools where if not careful, not following instructions or procedures even underestimate will cause work accidents and/ or occupational illness. Is observational descriptive research on the job risk assessments in chemical laboratories prodi pharmacy with JSA techniques aimed at finding out the risk of work performed. Population is type practicum work in chemistry laboratory and the sample is quantitative pharmaceutical chemistry practicum. Data collection techniques i.e. the work that has been selected is further determined with the working procedure and the working steps and then determines the findings of errors from each step of the work then further identify the potential hazards of each step of the work. Data analysis techniques is data from each finding of errors determined potential injury / danger / loss and its impact is then calculated risk value (risk matrix) i.e. the value of consequences multiplied by opportunity value where the results are could grouped into risk extreme, high, medium or low that continued with to determine safeguards measures that can be done to control the such danger. The results showed that performs the titration step has high very risk level value compared to another work step other of pharmaceutical chemical practicum quantitative. Titration activities carry an extreme or significant risk of harm when performed incompatible with working measures and unsafe with potential danger (disadvantage) is liquid evaporates (inhaled), disturbances The End Point of the Titration: change in color and determination of concentration, and perform movements manual repetitive continuously namely mixing the liquid or rotating the container (erlenmeyer) contains a chemical liquid by hand continuously. Chemistry laboratory organizes practicum, one of them quantitative pharmaceutical chemistry which uses a variety of chemicals and tools where if not careful, not following instructions or procedures even underestimate will cause work accidents and/ or occupational illness. Is observational descriptive research on the job risk assessments in chemical laboratories prodi pharmacy with JSA techniques aimed at finding out the risk of work performed. Population is type practicum work in chemistry laboratory and the sample is quantitative pharmaceutical chemistry practicum. Data collection techniques i.e. the work that has been selected is further determined with the working procedure and the working steps and then determines the findings of errors from each step of the work then further identify the potential hazards of each step of the work. Data analysis techniques is data from each finding of errors determined potential injury / danger / loss and its impact is then calculated risk value (risk matrix) i.e. the value of consequences multiplied by opportunity value where the results are could grouped into risk extreme, high, medium or low that continued with to determine safeguards measures that can be done to control the such danger. The results showed that performs the titration step has high very risk level value compared to another work step other of pharmaceutical chemical practicum quantitative. Titration activities carry an extreme or significant risk of harm when performed incompatible with working measures and unsafe with potential danger (disadvantage) is liquid evaporates (inhaled), disturbances The End Point of the Titration: change in color and determination of concentration, and perform movements manual repetitive continuously namely mixing the liquid or rotating the container (erlenmeyer) contains a chemical liquid by hand continuously.

Safety Assessment Review of a Dressing Assistance Robot.

Hazard analysis methods such as HAZOP and STPA have proven to be effective methods for assurance of system safety for years. However, the dimensionality and human factors uncertainty of many assistive robotic applications challenges the capability of these methods to provide comprehensive coverage of safety issues from interdisciplinary perspectives in a timely and cost-effective manner. Physically assistive tasks in which a range of dynamic contexts require continuous human–robot physical interaction such as e.g., robot-assisted dressing or sit-to-stand pose a new paradigm for safe design and safety analysis methodology. For these types of tasks, considerations have to be made for a range of dynamic contexts where the robot-assistance requires close and continuous physical contact with users. Current regulations mainly cover industrial collaborative robotics regarding physical human–robot interaction (pHRI) but largely neglects direct and continuous physical human contact. In this paper, we explore limitations of commonly used safety analysis techniques when applied to robot-assisted dressing scenarios. We provide a detailed analysis of the system requirements from the user perspective and consider user-bounded hazards that can compromise safety of this complex pHRI.

Toward Formal Safety and Performance Evaluation of GNSS-based Railway Localisation Function

European Train Control System (ETCS) is the signalling and control component of the European Rail Traffic Management System (ERTMS). This system is essential to guarantee the safe and interoperable operation of trains. To enhance the competitiveness of rail transport services, the introduction of innovative solutions are under study in view of the evolution of ETCS. In this context, the adoption of Global Navigation Satellite System (GNSS) for train localization is investigated as a technology which can ensure an undeniable added value for railways. Yet, a main challenge is to provide safety evidence permitting the certification of these new systems. In particular, the classical safety analysis approaches show limitations in dealing with the complexity of such systems. Therefore, more adapted safety and performance analysis techniques have to be elaborated. In this paper, a model-based approach, adapted for the evaluation of GNSS-based localisation systems in railway, is presented. Considering the safety-critical aspect of the localisation function in railways, formal methods which are based on rigorous mathematical foundations are adopted in the present work. Concretely, a set of formal models are elaborated to ensure a modular representation of trains dynamics in the context of GNSS-based localization. Namely, probabilistic timed automata formalisms are adopted to this aim. Such notations allow for considering stochastic and dynamic aspects, so as to reflect reality in a trustworthy way. The safety and performance properties to be checked can then be formulated by means of temporal logics. Finally, the analysis of such features can be achieved by means of model-checking and simulation techniques. This evaluation phase yields both qualitative and quantitative results and allows for assessing the impact of various parameters and functional choices on both safety and performance. UPPAAL-SMC engine was used to set the tooling chain of our approach, and an illustration considering specific operational test cases is provided.