發(fā)布時(shí)間：2018-05-12 17:02

  本文選題：質(zhì)量控制 + 過(guò)程能力指數(shù)��； 參考：《天津科技大學(xué)》2017年碩士論文

【摘要】：當(dāng)下,隨著實(shí)體經(jīng)濟(jì)的繁榮發(fā)展,客戶對(duì)于產(chǎn)品的要求日趨嚴(yán)格,如何在激烈的市場(chǎng)競(jìng)爭(zhēng)中站穩(wěn)腳跟一直是企業(yè)所思考的問(wèn)題。本文圍繞QS公司焊機(jī)生產(chǎn)的質(zhì)量控制方面進(jìn)行深入研究。在對(duì)生產(chǎn)進(jìn)行質(zhì)量控制時(shí),計(jì)算過(guò)程能力指數(shù)(PCI)進(jìn)而分析生產(chǎn)系統(tǒng)的生產(chǎn)過(guò)程能力十分重要。傳統(tǒng)情況下都視過(guò)程輸出數(shù)據(jù)服從正態(tài)分布這一理想狀態(tài),且進(jìn)行過(guò)程能力分析時(shí),不考慮生產(chǎn)模式,皆采用相同的分析方法。針對(duì)以上問(wèn)題,本文以統(tǒng)計(jì)過(guò)程控制理論為基礎(chǔ),依托QS公司焊機(jī)生產(chǎn),在計(jì)算過(guò)程能力指數(shù)時(shí),充分考慮數(shù)據(jù)非正態(tài)性與QS公司多品種小批量生產(chǎn)模式,建立多品種小批量模式下非正態(tài)過(guò)程能力指數(shù)的計(jì)算方法,并應(yīng)用于QS公司焊機(jī)生產(chǎn)以驗(yàn)證其有效性和可行性。首先,分析非正態(tài)過(guò)程能力指數(shù)的優(yōu)劣。通過(guò)充分了解過(guò)程能力相關(guān)理論的基礎(chǔ)上,建立常用的五類非正態(tài)過(guò)程能力指數(shù)計(jì)算的數(shù)學(xué)模型。利用蒙特卡洛方法,選取對(duì)數(shù)正態(tài)分布、威布爾分布數(shù)據(jù)帶入各數(shù)學(xué)模型,并對(duì)各參數(shù)進(jìn)行賦值。借助Matlab仿真輸出模擬結(jié)果Cpu,對(duì)比分析得到結(jié)果:在實(shí)際的應(yīng)用過(guò)程中由于會(huì)受到諸多因素的限制,故采用偏態(tài)過(guò)程能力指數(shù)Cs方法更為理想。其次,建立多品種小批量生產(chǎn)模式下的過(guò)程能力指數(shù)計(jì)算方法。針對(duì)傳統(tǒng)統(tǒng)計(jì)過(guò)程控制的局限性,提出Bootstrap相關(guān)理論與計(jì)算方法,同時(shí)重點(diǎn)研究了基于Bootstrap相關(guān)方法的過(guò)程能力指數(shù)及其置信區(qū)間的計(jì)算。建立數(shù)學(xué)模型并編寫(xiě)Matlab程序。通過(guò)上下控制限、樣本容量、抽取Bootstrap隨機(jī)替換樣本的樣本容量、抽取個(gè)數(shù)等參數(shù)的設(shè)定,進(jìn)行仿真,并將得到的估計(jì)值、置信區(qū)間以及區(qū)間寬度進(jìn)行對(duì)比,得到結(jié)論:t百分位數(shù)Bootstrap(Percentile-t Bootstrap,PTB)方法較另外兩種方法在處理多品種小批量問(wèn)題上更具優(yōu)勢(shì),得到的過(guò)程能力指數(shù)估計(jì)值與置信區(qū)間更加精確。最后,進(jìn)行QS公司焊機(jī)生產(chǎn)的過(guò)程能力指數(shù)分析。選取DNT3-160通體懸掛點(diǎn)焊機(jī)的C型點(diǎn)焊鉗為研究對(duì)象,建立QFD質(zhì)量屋確定關(guān)鍵質(zhì)量特性。通過(guò)正態(tài)性檢驗(yàn)、結(jié)合偏態(tài)過(guò)程能力指數(shù)Cs與t百分位數(shù)Bootstrap方法,得到質(zhì)量特性值的過(guò)程能力指數(shù)。最終提出針對(duì)于QS公司過(guò)程能力分析的一般流程,依據(jù)此流程改善QS公司過(guò)程能力分析的手段,實(shí)現(xiàn)該企業(yè)焊機(jī)生產(chǎn)的質(zhì)量控制水平。
[Abstract]:At present, with the prosperity of the real economy, the requirements of customers for products become increasingly strict, how to stand firm in the fierce market competition has been considered by enterprises. This paper focuses on the quality control of QS welder production. In the process of quality control, it is very important to calculate the process capability index (PCI) and then analyze the production process capability of the production system. Under the traditional condition, the process output data is normally distributed from the ideal state, and the same analysis method is adopted in the process capability analysis, regardless of the production mode. In order to solve the above problems, based on the statistical process control theory, this paper relies on the production of welding machines in QS Company. When calculating the process capability index, we fully consider the non-normality of data and the multi-variety and small-batch production mode of QS Company. The calculation method of non-normal process capability index in multi-variety and small-batch mode was established and applied to the production of QS welder to verify its validity and feasibility. Firstly, the advantages and disadvantages of the capability index of non-normal process are analyzed. On the basis of fully understanding the relevant theory of process capability, the mathematical models of five kinds of non-normal process capability exponents are established. Using the Monte Carlo method, the logarithmic normal distribution is selected, and the Weibull distribution data are brought into each mathematical model, and the parameters are assigned. By using Matlab simulation to output the simulation results, the results are compared and analyzed. The results are as follows: in the practical application process, due to the limitation of many factors, it is more ideal to use the skewness process capability index Cs method. Secondly, the calculation method of process capability index in multi-variety and small-batch production mode is established. In view of the limitation of traditional statistical process control, Bootstrap correlation theory and calculation method are put forward, and the calculation of process capability index and its confidence interval based on Bootstrap correlation method is studied emphatically. Build mathematical model and write Matlab program. By setting up and down control limit, sample size, sample size of Bootstrap random replacement sample, extracting number and so on, the simulation is carried out, and the estimated value, confidence interval and interval width are compared. It is concluded that the ratio t percentile Bootstrap(Percentile-t Bootstrapper PTB method is superior to the other two methods in dealing with multi-variety and small-batch problems, and the estimation of process capability index and confidence interval are more accurate. Finally, the process capability index analysis of QS welder production is carried out. The C type spot welding clamp of DNT3-160 universal suspension spot welder was selected as the research object, and the QFD quality house was established to determine the key quality characteristics. The process capability index of mass characteristic value is obtained by normal test combined with skew process capability index Cs and t percentile Bootstrap method. Finally, the general process of process capability analysis in QS company is put forward. According to the process capability analysis method, the quality control level of welding machine in QS company is realized.
【學(xué)位授予單位】：天津科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F426.4;F273

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本文編號(hào)：1879418