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Since the last century since the eighties , as market competition intensifies, the market in which modern business environment has undergone profound changes , business competition increasing emphasis on time-based competition and customer demand . The focus of competition between enterprises gradually from the price factor to quality , flexibility, fast delivery and other non- price factors change , small way to start mass production plays an increasingly important role. Based on this the less variety and large quantities of the traditional production process quality control technology challenges. With the growing popularity of small batch production , including control charts , including how to apply statistical process control methods to make this classic essence of quality control techniques can also be used in the production of personalized , has important application value. Small batch production is characterized by insufficient data , product quality is not enough information using commonly used control method , it is necessary for small batch production process quality control research, the control chart more effective than traditional methods , and can achieve a computer , which It is the content of this thesis . This thesis mainly done the following aspects of work : ( 1 ) study the statistical process control technology, the basic principles and ideas , focusing on the control chart techniques, including the design principle of control charts , control charts category , in a controlled state and runaway state control charts criterion as well as in quality control management in how to use the maps. ( 2 ) the traditional Shewhart control chart used in small batch production conditions, the problems were analyzed , obtained under the conditions of the direct application of small batch traditional Shewhart control charts feasible conclusions. Based on this , the small quantities of statistical process control methods were studied . ( 3 ) In theory , based on the research and development of a prototype system for statistical process control . The system implements different production conditions, quality analysis and real-time control, data analysis , alarms, report output and other functions, and examples are verified . Finally, the full text papers summarized, and the need for further research and exploration of the issues suggested.
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