Karmaşık bir sistemin belirsizlik ve hataların bağımlılığı altında güvenilirlik analizi

Reliability is the fundamental element of safety operation of all systems. The aim of reliability analysis is to quantify the failure probability and its protective barriers. These barriers are intended to protect the system from failures. Along with the emerging world economy, the growing complexity of systems and the advantage of increasing computational power, system reliability concept expanded to involve service availability, organizational and human reliability, uncertainty of complex systems, network system reliability. Human performance plays a significant role in developing and operating complex systems. Hence it is obvious that human errors have serious effects on complex systems' performance. All engineering systems are created by human endeavor, so it is actually suitable to claim that most of the system failures are due to human causes as ignorance, negligence or ineptitude. Human Reliability Analysis (HRA) techniques are used in different fields such as manufacturing, transportation, military or medicine. Human Reliability (HR) is a highly important notion as human errors may cause serious adverse consequences. Healthcare services sector is one of the major fields that require human reliability assessment as most of the applications involve human handling, decisions and processing. This study aims to draw a complete representation of doctors' behavior leading to clinical error by acquiring a complete causal relation model between all possible performance- influencing factors (PIFs) in healthcare operations which have been determined and analyzed for various healthcare operations. A major problem of HR studies is the lack of numerical measures of the likelihood of an erroneous event and its consequences. In these conditions, many methods have been developed to provide a quantitative risk assessment for HR concept. On the other hand, the nature of human error differs from the nature of component failure with the uncertainties involved. It is requisite to develop a clear understanding of human performance or behavior and their dependence on dynamic context and socio-technical environment. Human behavior can be affected by many different factors; furthermore these factors can be the connection between different stages of human behavior. Therefore a good mapping of PIFs is one of the essential concerns of understanding human behavior. In this context, Fuzzy Cognitive Maps (FCM) have been used to procure an explicit understanding of human behavior and all of the reasons relying under that behavior. In this respect, four doctors working in different high-risk healthcare fields evaluated all PIFs. The causal relationships are obtained and evaluated through a sensitivity analysis using different α-cuts. In real-life decisions, decision-makers / experts may have different confidence levels on their judgments. Sensitivity analysis procures decision-makers, a perspective that explains how the fuzziness in judgment may affect the solution robustness.