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

机译:基于贝叶斯网络的冷库建设质量风险管理算法

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摘要

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 is not in place, mismatch of building materials and equipment, inadequate training of skilled workers, completion acceptance is not careful or acceptance standards are unreasonable, and duration does not meet 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.
机译:在冷库建设项目中,只有控制好工程的质量风险,才能保证冷库在冷库建成后能够满足预期的使用功能,达到预期的经济效益。为有效保障冷库在冷链物流中的关键枢纽作用,构建冷库建设质量风险管理体系,从施工程序、参与单位、工作流程三个维度识别和分析质量风险因素,构建基于贝叶斯网络的冷库建设质量风险评估模型, 并通过逆向推理分析和敏感性分析,推导出关键质量风险因素:质量保证体系不健全、技术交付不到位、建筑材料与设备不匹配、熟练工人培训不足、竣工验收不仔细或验收标准不合理、工期不符合要求等。最后,针对上述质量风险,从人、物、机、法、环境五个方面提出建议和措施。

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