Search Results (2)

Conventional unconditional random field (URF) models were shown to neglect in-situ monitoring data and thus misrepresent real slope stability. To address this, a conditional random field (CRF) generator was proposed, in which Fast Fourier Transform (FFT) filtering was coupled with co-Kriging to assimilate site observations. A representative three-bench slope was adopted, and the failure-mode distribution and the statistics of the factor of safety (FoS) produced by the URF, the independent random field (IRF), and the CRF were examined across bedding-dip angles of 15–75° and two cross-correlation states ($\rho$ = −0.2, 0). It was found that eliminating cross-correlation decreased the mean FoS by 0.006, increased its standard deviation by 10.26%, and raised the frequency of low-FoS events from 7.49% to 12.30%. When field constraints were imposed through the CRF, the probability of through-going failure was reduced by 12%, the mean FoS was increased by 0.01, the standard deviation was reduced by 15.38%, and low-FoS events were suppressed to 2.30%. The CRF framework was thus demonstrated to integrate stochastic analysis with field measurements, enabling more realistic reliability assessment and proactive risk management of slopes. Full article

This paper presents a new risk assessment methodology called the Integrated Risk Framework (IRF) through the application of Ishikawa diagrams combined with the enhanced Hazard Analysis and Critical Control Point (HACCP) system. This risk investigation technique aims to ensure a significantly higher level of quality, safety, and sustainability in food products by using improved classical methods with strong intercorrelation capabilities. The methodology proposes expanding the typology of basic physical, chemical, and biological risks outlined by the ISO 22000 Food Safety Management System standard, adding other auxiliary risks such as allergens, fraud/sabotage, Kosher/Halal compliance, Rapid Alert System for Food and Feed notification, or additional specific risks such as irradiation, radioactivity, genetically modified organisms, polycyclic aromatic hydrocarbons, African swine fever, peste of small ruminants, etc. depending on the specific technological process or ingredients. Simultaneously, it identifies causes for each operation in the technological flow based on the 5M diagram: Man, Method, Material, Machine, and Environment. For each identified risk and cause, its impact was determined according to its severity and likelihood of occurrence. The final effect is defined as the risk class, calculated as the arithmetic mean of the impact derived at each process stage based on the identified risks and causes. Within the study, the methodology was applied to the spring water bottling process. This provided a new perspective on analyzing the risk factors during the bottling operations by concurrently using Ishikawa diagrams and HACCP principles throughout the product’s technological flow. The results of the study can form new methodologies aimed at enhancing sustainable food safety management strategy. In risk assessment using these two tools, the possibility of cumulative or synergistic effects is considered, resulting in better control of all factors that may affect the manufacturing process. This new perspective on studying the dynamics of risk factor analysis through the simultaneous use of the fishbone diagram and the classical HACCP system can be extrapolated and applied to any manufacturing process in the food industry and beyond. Full article