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Methods of Computational Intelligence in the Context of Quality Assurance in Foundry Products

机译:铸造产品质量保证中的计算智能方法

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One way to ensure the required technical characteristics of castings is the strict control of production parameters affecting the quality of the finished products. If the production process is improperly configured, the resulting defects in castings lead to huge losses. Therefore, from the point of view of economics, it is advisable to use the methods of computational intelligence in the field of quality assurance and adjustment of parameters of future production. At the same time, the development of knowledge in the field of metallurgy, aimed to raise the technical level and efficiency of the manufacture of foundry products, should be followed by the development of information systems to support production processes in order to improve their effectiveness and compliance with the increasingly more stringent requirements of ergonomics, occupational safety, environmental protection and quality. This article is a presentation of artificial intelligence methods used in practical applications related to quality assurance. The problem of control of the production process involves the use of tools such as the induction of decision trees, fuzzy logic, rough set theory, artificial neural networks or case-based reasoning.
机译:确保铸件所需技术特征的一种方法是严格控制影响最终产品质量的生产参数。如果生产工艺配置不当,铸件上产生的缺陷将导致巨大的损失。因此,从经济学的角度来看,建议在质量保证和未来生产的参数调整领域中使用计算智能方法。同时,在冶金领域的知识开发(旨在提高铸造产品的制造技术水平和效率)之后,应继之以开发信息系统以支持生产过程,以提高其有效性和可靠性。符合对人体工学,职业安全,环境保护和质量日益严格的要求。本文介绍了与质量保证相关的实际应用中使用的人工智能方法。生产过程的控制问题涉及使用工具,例如决策树的归纳,模糊逻辑,粗糙集理论,人工神经网络或基于案例的推理。

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