To address the challenges in traditional Failure Mode and Effects Analysis (FMEA) related to determining factor weights, identifying risk priority of failure modes, and managing uncertainties in the risk assessment process, this paper proposes an enhanced FMEA risk factor evaluation method. This method integrates incomplete and imprecise expert assessments using a fuzzy multi-criteria compromise ranking technique called the “V1seKriterijumska Optimizacija I Kompromisno Resenje” (VIKOR). By employing Fuzzy Evidence Reasoning (FER), the risk factor ratings are represented using fuzzy belief structures to capture their diversity and uncertainty. Objective weights are adjusted using Shannon entropy to correct subjective weights, and the VIKOR technique is applied to prioritize failure modes based on the principles of minimizing individual regret and maximizing group utility. The improved model is applied to identify key equipment associated with oil and gas leakage risk in the Floating Production Storage and Offloading (FPSO) system. Validity and sensitivity analysis confirm the robustness and reliability of the method, enhancing the accuracy and credibility of the evaluation results.
The selection of appropriate anti-drone systems is critical for enhancing a military's defensive capabilities. With a range of non-kinetic anti-drone guns available, it is essential to identify the optimal system that meets specific military requirements. This study presents a comprehensive approach, combining Multiple Criteria Decision Making (MCDM) techniques to facilitate this selection process. The Defining Interrelationships Between Ranked Criteria II (DIBR II) method has been employed to determine and calculate the criteria weighting coefficients, while the Grey Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method, modified to utilize interval grey numbers, has been applied to rank the alternatives. The criteria weighting coefficients, defined by expert input, are aggregated using the Bonferroni mean. The proposed DIBR II-Grey MARCOS model is then subjected to a sensitivity analysis, which further validates the robustness of the selection process. A comparative analysis of results, based on the applied MCDM methods, underscores the efficacy of the proposed model. The findings demonstrate that this integrated model not only provides a reliable framework for selecting anti-drone guns but also offers a versatile tool for resolving other MCDM challenges across various domains. The study highlights the potential of this model for broader application in diverse operational environments, where complex decision-making is required. The combination of MCDM techniques and sensitivity analysis offers valuable insights into optimizing resource allocation, thereby enhancing strategic decision-making processes. The proposed model's adaptability and effectiveness suggest its significant potential for adoption beyond the military sector.
This study evaluates the safety management system at Xuefu Gas Station in Xiangtan City of China through a combination of Preliminary Hazard Analysis (PHA) and Fault Tree Analysis (FTA). Initially, PHA was employed to identify potential hazards and assess the probability of associated accidents. This analysis led to the formulation of preventive measures aimed at mitigating identified risks. Subsequently, FTA was utilized to construct a logical framework for analyzing the various causes of system failures and their interdependencies. The analysis revealed deficiencies in the management system, equipment, ignition sources, and human factors. An approximate calculation method was applied to rank the structural importance of these factors, thereby highlighting key areas of impact. Based on these findings, targeted recommendations were proposed to enhance the safety management practices at the gas station, thereby reducing accident likelihood and safeguarding personnel and property. The results underscore the necessity of improving management practices, upgrading equipment, controlling ignition sources, and bolstering human factors to achieve a comprehensive safety management system.
The current research is to profit from the science of enterprise architecture (Enterprise Architecture) and its application in building the structure of government sector institutions in the Kingdom of Saudi Arabia, in accordance with the Kingdom of Saudi Arabia 2030 vision. while emphasizing the value of enterprise architecture (EA) and the need for knowledge to apply its models and procedures while creating its structures. The research study's scope is determined by how well the descriptive and analytical approaches function together, and this is achieved by choosing a few government sector organizations to focus on. Throughout exploring the possibility of applying the Enterprise Architecture model, as an application case based on the extent of knowledge of the cadres of those entities with the organizations' enterprise architecture, and the presence of supervisory expertise. By relying on the quantitative method of studying and analyzing the situation by conducting a questionnaire on some workers in those bodies under consideration (Research Sample), studying the possibility and feasibility of applying enterprise architecture for organizations and generalizing this in the restructuring of government sector’s institutions in general.
A detailed investigation into the axial bearing load of the revolving platform in a hydraulic excavator equipped with a shovel attachment was presented in this study. A mathematical model was formulated to assess the forces acting on the bearing under various operational conditions. The analysis focuses on a 100,000 kg excavator with a 6.5 m³ bucket, examining the contributions of kinematic chains and drive mechanisms to axial loads. Simulations of multiple positions within the working range were carried out, calculating the load spectrum, including boundary resistance, to ensure machine stability. An optimization program was developed to refine the bearing selection process by identifying equivalent loads and moments. These calculations were benchmarked against manufacturer capacity diagrams, allowing for precise selection of appropriate bearing sizes. The findings underscore the critical role of accurate load calculations in enhancing the performance, reliability, and design optimization of hydraulic excavators. This approach provides engineers with a framework for selecting bearings that can withstand complex operational stresses, thereby improving the efficiency and longevity of hydraulic machinery.
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