本文關(guān)鍵詞： 過(guò)程方差 合成S~2圖 已知參數(shù) 未知參數(shù)　出處：《浙江工商大學(xué)》2015年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：在生產(chǎn)過(guò)程中,有些生產(chǎn)因素如劣質(zhì)的原材料或者工人操作不熟練并不會(huì)引起過(guò)程均值發(fā)生變化,但卻會(huì)引起過(guò)程方差的變化,過(guò)程方差變大說(shuō)明產(chǎn)品的質(zhì)量不穩(wěn)定,過(guò)程方差減小說(shuō)明產(chǎn)品的質(zhì)量提高。另外過(guò)程方差失控會(huì)使均值控制圖的表現(xiàn)不同于預(yù)期,因此監(jiān)測(cè)過(guò)程方差的變化是十分重要的。傳統(tǒng)的休哈特S2圖常被用于過(guò)程方差的監(jiān)控,但存在一定缺陷,具體表現(xiàn)為對(duì)過(guò)程方差大漂移比較敏感,而對(duì)過(guò)程方差中小漂移不敏感。本文引入合成圖的方法,將休哈特S2圖與合格品鏈長(zhǎng)圖結(jié)合組成合成S2圖來(lái)對(duì)方差進(jìn)行監(jiān)控,以改進(jìn)休哈特s2圖的表現(xiàn),提高控制圖監(jiān)測(cè)過(guò)程方差變化的能力。本文主要研究?jī)?nèi)容如下：(1)本文將合成圖的方法分別應(yīng)用于對(duì)過(guò)程方差單、雙側(cè)漂移的監(jiān)測(cè)。基于參數(shù)已知情況,設(shè)計(jì)了上單側(cè)合成S2圖、下單側(cè)合成s2圖以及雙側(cè)合成s2圖分別應(yīng)用于監(jiān)測(cè)正態(tài)總體假定下過(guò)程方差變大、過(guò)程方差變小以及過(guò)程方差漂移方向不確定等三種情況,并與相應(yīng)的休哈特s2圖比較。結(jié)果顯示本文設(shè)計(jì)的單、雙側(cè)合成s2圖的監(jiān)測(cè)效果均優(yōu)于休哈特S2圖。(2)控制圖的設(shè)計(jì)通常假設(shè)受控參數(shù)己知,而實(shí)際應(yīng)用中受控參數(shù)常常未知并需要由已獲受控樣本進(jìn)行估計(jì)。本文分析了參數(shù)估計(jì)對(duì)三種合成s2圖的影響,發(fā)現(xiàn)參數(shù)估計(jì)會(huì)增加偽警概率,大大降低合成s2圖的監(jiān)控能力,特別是在過(guò)程方差漂移量較小和用于估計(jì)受控參數(shù)的第1階段樣本組數(shù)較小之時(shí)。(3)因?yàn)閰?shù)估計(jì)大大影響三種合成S2圖的表現(xiàn),所以基于己知參數(shù)的控制圖不再合適,因此本文基于估計(jì)參數(shù)設(shè)計(jì)了新的單、雙側(cè)合成s2圖對(duì)過(guò)程方差進(jìn)行監(jiān)控,并與相應(yīng)的的休哈特s2圖比較,結(jié)果顯示在參數(shù)未知時(shí),新設(shè)計(jì)的單、雙側(cè)合成s2圖的監(jiān)測(cè)效果優(yōu)于相應(yīng)的單、雙側(cè)休哈特s2圖。
[Abstract]:In the process of production, some production factors, such as inferior raw materials or unskilled operation of workers, will not cause changes in the mean value of the process, but will cause changes in the variance of the process. The increase of process variance indicates that the quality of the product is unstable, and the decrease of the process variance indicates the improvement of the quality of the product. In addition, the runaway process variance will make the performance of the mean control chart different from the expected. Therefore, it is very important to monitor the variation of process variance. The traditional Shewhart S2 diagram is often used to monitor the process variance, but it has some defects, which shows that it is sensitive to the large drift of process variance. However, it is not sensitive to the small drift of process variance. In this paper, the method of composite graph is introduced, which combines Shewhart S2 diagram with qualified product chain length graph to monitor the variance to improve the performance of Heinhart S2 diagram. The main contents of this paper are as follows: 1) in this paper, the method of composite graph is applied to the monitoring of single and bilateral drift of process variance, based on the known parameters. The S 2 map of upper side synthesis, the second side S 2 and the double side S 2 are designed to monitor the normal population under the assumption that the process variance becomes larger. The process variance becomes smaller and the direction of process variance drift is uncertain. The results are compared with the corresponding Hewhart S2 diagram. The results show that the design of this paper is single. The monitoring effect of bilateral s2 diagram is better than that of Hewhart S2 chart. 2) the design of the control chart usually assumes that the controlled parameters are known. In practical application, the controlled parameters are often unknown and need to be estimated by controlled samples. In this paper, the effect of parameter estimation on three kinds of composite S2 graphs is analyzed, and it is found that parameter estimation will increase false alarm probability. Greatly reduces the monitoring ability of the composite S2 graph. Especially when the variance drift of the process is small and the number of samples used in the first stage to estimate controlled parameters is small) the parameter estimation greatly affects the performance of the three kinds of composite S2 graphs. Therefore, the control chart based on known parameters is no longer suitable, so this paper designs a new single- and double-side composite S2 graph to monitor the process variance based on the estimated parameters, and compares it with the corresponding Shewhart S2 graph. The results show that when the parameters are unknown, the monitoring effect of the newly designed single and bilateral composite S2 charts is better than that of the corresponding single and bilateral Heinhart S2 diagrams.
【學(xué)位授予單位】：浙江工商大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：F273.2;F224

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本文編號(hào)：1442329