Sentence examples for risk analysis principles from inspiring English sources

The framework is designed in accordance with the generic risk analysis principles used in food safety and can be used by regulators to decide whether or not a specific allergenic food or ingredient is of sufficient public health importance that it warrants regulation (i.e. mandatory labelling) when used in the production of food products.

Quantitative risk analysis is in principle an ideal method to map one's risks, but it has limitations due to the complexity of models, scarcity of data, remaining uncertainties, and above all because effort, cost, and time requirements are heavy.

The control measures at these critical stages or points could be identified through a risk analysis approach using HACCP principles to quantify and rank the risk.

The company has applied big data principles for risk analysis of business loans.

The principles of risk analysis were conceptually applied to surveillance in order to further develop approaches and tools (scenario tree modelling) to design risk-based surveillance (RBS) programmes.

The term 'risk-based surveillance' could be reserved for the context of strategic decision making that employs principles of risk analysis in relation to surveillance of animal disease.

Principles of quantitative risk analysis together with economic objectives are used for the design of two types of distillation arrangements, namely conventional distillation and multi-effect distillation.

The issue of time is also critical for risk analysis and application of the precautionary principle.

As part of credit risk analysis and credit engineering, the general underlying principles of risk analysis remain the same as in general business risk.

The Codex Alimentarius Commission (2011) described eight principles that are specific to risk analysis for foodborne antimicrobial resistance, several of which are generally applicable to a HHRA of environmental ARB.

This is achieved by redefining how to estimate risk and by applying the principles of mathematical optimization to quantitative risk analysis.