Abstract
AbstractThe internal audits carried out in the first half of 2019 in water laboratories as part of quality accreditation in accordance with ISO/IEC 17025:2017 showed a high frequency of adverse events in connection with sampling. These faults can be a consequence of a wide range of causes, and in some cases, the information about them can be insufficient or unclear. Considering that sampling has a major influence on the quality of the analytical results provided by water laboratories, this work presents a system for reporting and learning adverse events. Its aim is to record nonconformities, errors, and adverse events, making possible automatic data analysis aiming to ensure continuous improvement in operational sampling. The system is based on the Eindhoven Classification Model and enables automatic data analysis and reporting to identify the main causes of failure. Logic programming is used to represent knowledge and support the reasoning mechanisms to model the universe of discourse in scenarios of incomplete, contradicting, or even unknown information. In addition to suggesting solutions to the problem, the system provides formal evidence of the solutions presented, which will help to continuously improve drinking water quality and promote public health.
Highlights
Securing water quality for human consumption through a public supply system is an essential element of health policy
To achieve accurate results in water analysis, it is essential that sampling is carried out correctly. To help fulfill this objective, this work presents an adverse event reporting and learning system, developed for the sampling phase, that aims to improve the quality of drinking water and, contributes to the promotion of public health
The key contribution of this work is related to the quantification of the QoI imbedded in Causal Trees (CTs) and to address the issues pertaining to incomplete information using the logic programming (LP) paradigm
Summary
Securing water quality for human consumption through a public supply system is an essential element of health policy. By the end of the 19th century, an assessment and control of risks to human health from transmission of diseases caused by water consumption had been carried out empirically on the basis of the physical appearance of water (Bagchi 2013). Until the middle of the 20th century, the quality of water for human consumption had been largely assessed based on its organoleptic characteristics, i.e., its colorless, tasteless, and odorless features (Eaton et al 2017). This type of assessment does not guarantee the protection of public health
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