The Study Of Using SPC Technique In Cards Production

With the high speed development of 21st century information technology, rapid grown of economy, the entry level of manufacturing is getting lower and lower in today's competitive market. Every company need to seek every means to increase their own competitiveness. As the fundamental of survival, robust and effective quality management is the topic which is worthy for every company to research.Quality assurance is a mainly carried on by quality control, which occupies very important position in the whole process. With the emerging of many different quality control methods, statistic process control (SPC) is adopted in a wide range of companies, especially in electronic products and highly precision companies. SPC can make great contribution in the improvement of product yield rate because it can monitor the overall production process, spot the abnormal quickly, prevent the defect or scrap from happening.SPC is 1^st presented in 1924 by Shewhart W.A. from Bell Telephone Laboratories, it can timely alarm the quality issues, so that the management can have promote reaction. But traditional SPC is more suitable for high volume production, not good for small volume but multiple models, the characteristic for which is in-sufficient quality information and limited sample size.However, with the development of people's consumer attitudes, they are seeking for more and more personality in the consumptions, which has been proved by the rising of Apple. The pursue of personality will not allow high volume copy and production, but will result in small volume multiple models. That's why SPC study of small volume multiple models is becoming more and more important and the major topic of this thesis.This thesis will compare the current control methods for small volume, and then propose the subject content: The study of using SPC in cards production. It contains the following area: first, find out the primary process parameters of quality index after analysis for card production in M factory. Second, analyze the limitation of current quality control method and propos the proper method. Last, verify the effectiveness by the quality data from certain batch of production.