A Bayesian Framework for Parameters Estimation in Complex System

摘要

The real-life complex development situations express that the methods applied to new product development process content reliability risks which require assessment and quantification at the earliest stage, extracting relevant information from the process. Reliability targets have to be realistic and systematically defined, in a meaningful way for marketing, engineering, testing, and production. Potential problems proactively identified and solved during design phase and products launched at or near planned reliability targets eliminate extensive and prolonged improvement efforts after start on. Once in the market, products standard procedures require monitoring of early signs of issues, allowing corrective action to be quickly taken. Reliability validation before a product goes to market by the means of Bayesian statistical method because the model has shorter confidence intervals than the classical statistical inference models, allowing a more accurate decision-making process. The paper proposes the estimation of the shape parameters in a complex data structures approached with exponential gamma distribution as model of life time, reliability and failure rate functions The numerical simulation performed in the case study validates the correctness of the proposed methodology.