多品种小批量生产模式下工序质量控制方法研究

发布时间：2018-05-26 14:05

本文选题：多品种小批量 + 成组技术　；参考：《北京交通大学》2017年硕士论文

【摘要】：当今社会经济飞速发展促使消费者追求多样化、个性化产品需求不断提升,企业为快速响应市场,赢取用户越来越倾向于向多品种、小批量的短周期、柔性生产模式转变,但由于多品种、小批量生产模式产品品种多、规格复杂多样、每种产品数量少,生产过程不稳定等特点给质量管理带来很大困难,因此探索一种适合该模式的质量控制方法尤为重要。质量是制造出来的,而不是检验出来的,因此对过程控制显得尤为重要。传统SPC休哈特控制图对大批量生产的过程监控产生巨大经济效益,因此本文充分研究SPC方法,取其精华,去其糟粕,提出一种多品种小批量生产模式下的成组工序统计过程控制方法。针对使用传统SPC样本量不足问题,本文提出成组技术思想,研究其应用可行性,并给出一种基于直觉模糊集的工序相似性判定方法;接下来对成组工序内数据进行了标准化处理;盲目使用传统休哈特特控制图容易造成虚发警报,本文提出多变异分析方法,对不同变异来源采用不同过程质量控制方法;最后以M公司分条实例验证了上述理论方法的可行性与有效性,为多品种小批量生产模式下工序质量控制提供一种有效的解决办法。
[Abstract]:With the rapid development of society and economy, consumers are seeking diversification and the demand for individualized products is increasing. In order to quickly respond to the market and win customers, enterprises are more and more inclined to change to multi-variety, small-batch short cycle and flexible production mode. However, because of the characteristics of multi-variety, small-batch production mode, variety of products, complicated specifications, small quantity of each product, unstable production process and so on, it brings great difficulties to quality management. Therefore, it is very important to explore a quality control method suitable for this model. Quality is manufactured, not tested, so it is particularly important to process control. The traditional SPC Shewhart control chart has great economic benefits on the process monitoring of mass production. Therefore, this paper fully studies the SPC method, takes the essence of it, and loses its dross. This paper presents a statistical process control method for group processes in multi-variety and small-batch production mode. In order to solve the problem of insufficient sample size using traditional SPC, this paper puts forward the idea of group technology, studies the feasibility of its application, and gives a method of judging process similarity based on intuitionistic fuzzy set. Then the data in the group process are standardized. Blind use of the traditional Huhaltte control chart can easily lead to false alarm. This paper proposes a multi-variation analysis method and uses different process quality control methods for different sources of variation. Finally, the feasibility and effectiveness of the above theoretical methods are verified by the example of M Company, which provides an effective solution for the process quality control under the multi-variety and small-batch production mode.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F273.2

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