Quality Risk Management Algorithm for Cold Storage Construction Based on Bayesian Networks

Abstract

In the cold storage construction project, only by controlling the quality risk of the project can ensure that the cold storage can meet the expected use function and achieve the expected economic benefits after the completion of the cold storage. In order to effectively ensure the key pivot role of cold storage in cold chain logistics, a cold storage construction quality risk management system is constructed to identify and analyze quality risk factors from three dimensions: construction procedures, participating units, and work processes, construct a cold storage construction quality risk evaluation model based on Bayesian network, and through reverse reasoning analysis and sensitivity analysis, key quality risk factors are derived: inadequate quality assurance system, technical delivery not in place, mismatch of building materials and equipment, inadequate training of skilled workers, completion acceptance not careful or acceptance standards unreasonable, and duration not meeting the requirements. Finally, in view of the above quality risks, suggestions and measures are put forward from five aspects: man, material, machine, method, and environment.