Method, Computer Apparatus, And Storage Medium For Evaluating Product Reliability

A computer apparatus comprising a processor;

• and a memory storing instructions, which, when executed by the processor, cause the processor to perform steps comprising:
• acquiring a first fault simulation result data of each preset component;
• obtaining a second fault simulation result data of each of the preset components according to an identification of each fault simulation result data in the first fault simulation result data;
• performing distribution fitting to the second fault simulation result data to determine the fault distribution function of each of the preset components;
• performing data sampling according to a first preset random number set and the fault distribution function of each of the preset components, and performing distribution fitting to the PCBA-level fault simulation result data obtained after sampling to obtain the fault distribution function and the fault distribution parameter value set of each PCBA, the fault distribution parameter value set comprising a fault distribution parameter, a point estimation value, and upper and lower limit interval values of a failure time;
• performing data sampling according to a second preset random number set and the fault distribution function of each PCBA, and performing distribution fitting to a product-level fault simulation result data to obtain a fault distribution function and a fault distribution parameter value set of the product;
• and
• obtaining a product reliability evaluation result according to the fault distribution function and the fault distribution parameter value set of each PCBA, and the fault distribution function and the fault distribution parameter value set of the product.

At least one non-transitory computer-readable storage medium storing computer-readable instructions that, when executed by at least one processors, cause the at least one processor to perform steps comprising:

• acquiring a first fault simulation result data of each preset component;
• obtaining a second fault simulation result data of each of the preset components according to an identification of each fault simulation result data in the first fault simulation result data;
• performing distribution fitting to the second fault simulation result data to determine the fault distribution function of each of the preset components;
• performing data sampling according to a first preset random number set and the fault distribution function of each of the preset components, and performing distribution fitting to the PCBA-level fault simulation result data obtained after sampling to obtain the fault distribution function and the fault distribution parameter value set of each PCBA, the fault distribution parameter value set comprising a fault distribution parameter, a point estimation value, and upper and lower limit interval values of a failure time;
• performing data sampling according to a second preset random number set and the fault distribution function of each PCBA, and performing distribution fitting to a product-level fault simulation result data to obtain a fault distribution function and a fault distribution parameter value set of the product;
• and
• obtaining a product reliability evaluation result according to the fault distribution function and the fault distribution parameter value set of each PCBA, and the fault distribution function and the fault distribution parameter value set of the product.