Process Capability Analysis And Its Application In Manufacturing Of Electronic And Cold Roller Products

As a core content of statistical process control (SPC), process capability analysis is an important tool and method to gurantee quality of products, and process capability analysis is raising more and more attention now, especially under the environment that "Six Sigma" and "Total Quality Management" are popularly used and become common practice. This thesis analyzes the capability of products in different situations, such as the data is non-normal distributed, the sampling size is small, even the stages and characteristics are mutiple, and it also proposes the corresponding methods of process capability analysis for above cases. The methods are helpful to enterprises for quality improving, and they are profound of theoretical and practical significance.Traditionally, there are three basic hypotheses in process capability analysing: the process is in control, the data is normal distributed, the data is independent and with large samples. However, they are not all satisfied in reality, such as the data is non-normal distributed, the samplings are in small sizes or the production is in small batch, even the stages and characteristics are multiple. All these situations bring inconvenience to enterprises and their operators, even cause misunderstanding and misapplication. To solve these problems, this thesis firstly analyses and summarises the recent years development of SPC and process capability analysis, then combined with the actual production situations of enterprises, some researches and application are developed which based on investigations to a mechnical company in Sanxi and an electronic company in Zhejiang. This thesis is a constituent part of "985 project scientific and technological innovation of Integrated Automation of Process Industry platform research project", "Liaoning provincial division of sicence and technology planning project" and "National Natural Science Funds for Distinguished Young Scholar project". It is also a core content of enterprises' technical studing project-"Process data management system of cold roller" and "Quality appriasing and improvming system of cold roller" in Sanxi, and enterprises' consultant and management project-"Quality management and improving consultant project of electronic company of Dafeng".In Chapter 2, basic theories about SPC are firstly introduced, including the concepts of SPC, the classifications of control charts, the meanings of process capability analysis and different definitions of their indices calculating, the literatures of their theroies are also overviewed in detail; and then combined with the real cases of producing, the thesis proposes methods of process capability analysis corresponding to traditional cases, non-normal data cases, small sampling size cases, and the cases of multi-stages and multi-characteristics, it also provides reasonable suggestions and solutions to enterprises based on the practical application; finally, the thesis points out the deficiency of process capability analyzing and decision making, which only based on process capability indices calculating in traditional way. Combined with the practical application, a quality improving flowchart based on process capability plots is constructed. As a whole, this thesis focuses on the following five key problems.As the key problem 1, chapter 3 is an application of process capbility analysis whose model is DMAIC (Define-Measure-Analysis-Improve-Control), and it is a revelation of traditional flow of process capability analysis. Taking the production of some electronic products as an example, and following the flow of DMAIC, this chapter firstlly analyzes the causes and locates the stages of quality defects, and then an analysis of measurement system is developed. Based on reliable and stable measurement system, design of experiment (DOE) is developed for choosing, determining and optimizing the critical factors and their relative settings. This chapter employs SPC to wave solering, and the control chart is used for controlling and diagnosing the stage of wave solering, the further calculation and analysis of process capability are developed after the process is in control.The later chapters are research and application of different and special cases of process capability analysis.As the key problem 2, chapter 4 focuses on the solution of non-normal data in real production. Considering the data is non-normal distributed in some actual production, this chapter firstly analyzes the causes and influences of nonnormality to process capability analysis, and then some simple comparisons and limitation analysis are made according to different methods, which are used for dealing with non-normal data. This thesis firstly adopts Root Transformation method to translate non-normal data into normal, and then makes an application of it to some electronic products. The rationality and validity of this method are vertified after comparing with Box-Cox transformation method.As the key problem 3, chapter 5 focuses on process capability analysis with small samples. After analyzing the influences of sampling size to the point estimations and confidence intervals of C_p and C_pk, a serious of random data that is namely normal distributed, student t distributed, chi-square distributed and lognormal distributed are simulated with different sample sizes. Based on these simulated data and four Bootstrap methods, i.e. Standard Bootstrap (SB), Percentile Bootstrap (PB), Biased-corrected Percentile Bootstrap (BCPB), Percentile-t Bootstrap (PTB), the confidence intervals of C_p and C_pk are simulated and computed, and then some comparisons and analysis of different Bootstrap methods and sample sizes are made through two factors analysis of variance (ANOVA) method. Some valuable conclusions are made at last. Combined with the production of some electronic products, the thrust power of red agglutinant with devastatingly sampling and small samples is taken as the characteristic to be studied, and the PTB method is used for process capability analysis. Analyzing the results, some valuable suggestions are provided to enterprises.As the key problem 4, chapter 6 focuses on the analysis of mutivariable process capability, including the analysis of multi-stages and multi-characteristics. Combined with the actual production of enterprises, and considering the plurality of stages and characteristics, this chapter constructs a model of multivariable quality controlling and improving. In view of the plurality of stages, this chapter takes the production of cold roller as an example, and a simple improvement in Taguchi quality loss function is made to locate the key stages and analyze the process capability of multi-stages. The rationality and validity of this method are vertified through an application in cold roller production. In view of the plurality of characteristic, a flowchart of multi-characteristics process capability analysis is constructed, it is based on the Luceno index. Combined with the actual production of some electronic products, the method and the idea of the model is used for calculating the process capability indices (PCIs) of 5 process characteristics in wave soldering stage. Some suggestions and advicies are provided to enterprise according to the results.As the key problem 5, chapter 7 focuses on the process capability plots and their application. Considering the defects of process capability analyzing only with process capability indices, the hypothesis testing is used for process capability analyzing and decision making based on the critical values of PCIs. An analysis of the influence of sample scale to crtical values of PCIs is made, it is helpful to enterprises for reasonal sampling. The graph forms of process capability plots are proved, and the quality improving flowchart based on process capability plots is constructed. Combined with the actual production of some electronic products, the analysis of process capability based on multi-characteristics process capability analysis (MCPCA) chart is developed. The superiority of process capability plots is finally proved by a practical application.