统计过程控制和全面质量管理【外文翻译】
品检质量控制中的统计过程控制方法

品检质量控制中的统计过程控制方法在现代工业生产中,如何保证产品质量的稳定和可靠性是一个重要的问题。
统计过程控制(Statistical Process Control,简称SPC)是一种常用的质量控制方法,通过对生产过程中的数据进行统计和分析,帮助企业实现对质量的持续监控和改进。
本文将介绍品检质量控制中常用的统计过程控制方法,包括控制图、过程能力分析和六西格玛方法。
控制图是一种直观简单且易于理解的统计工具,用于监控生产过程中的关键指标。
控制图一般由上限线、下限线和中心线组成,中心线表示过程的平均水平,上下限线则代表了过程的变异性。
通过收集和记录采样数据,可以绘制出控制图,并根据数据的变化情况来判断过程是否处于控制状态。
常用的控制图包括均值图和极差图。
均值图用于监测过程的平均水平是否稳定。
通过对一系列样本均值的统计,绘制出均值图,可以直观地判断过程是否存在系统性变化。
如果数据点超出了控制限,就说明过程中可能存在特殊原因的影响,需要进行进一步分析和改进。
极差图则用于监控过程的变异性。
极差是指样本中最大值与最小值之间的差异,极差图通过对一系列样本极差的统计,可以判断过程的变异性是否处于控制状态。
同样,如果数据点超出了控制限,就需要进行原因分析和改进措施的制定。
除了控制图之外,过程能力分析也是品检质量控制中的重要工具。
过程能力分析的目的是评估生产过程是否具有满足需求的能力。
常用的过程能力指标包括过程平均值与规格上下限之间的距离、过程的标准偏差以及过程的允许偏差范围。
通过分析过程能力指标,可以得出生产过程是否稳定,并评估其是否满足产品质量要求。
如果过程能力指标超出了规格要求,就需要采取措施来改进过程,以提升产品质量。
六西格玛方法是一种基于统计分析的全面质量管理方法。
它将统计过程控制与过程改进相结合,致力于提高质量、降低成本和增强客户满意度。
六西格玛方法通过收集和分析大量数据来识别生产过程中的关键环节,并采取措施来减少变异性,从而提高产品质量和生产效率。
统计过程控制技术在质量管理中的应用

统计过程控制技术在质量管理中的应用摘要:统计工程控制(SPC)作为先进质量管理和过程控制的重要工具在企业中得到了广泛的引用。
本文就SPC在质量管理中的应用做了一个系统论述,包括SPC的发展历程、SPC在质量管理中的实现方法以及SPC在质量管理中的引用。
关键字:统计过程控制;实现方法;应用引言:质量是企业在激烈的竞争中能否取胜的关键[1]。
为了在全球竞争中获胜,为了给客户提供优质的产品,企业必须确保在产品的生产过程中不断监测并使产品的质量得到不断提高。
统计过程控制(Statistieal Proeess Control,简称SPC)作为先进质量管理和过程控制的重要工具和技术,对预防产品生产过程的质量缺陷,增强企业的竞争力具有举足轻重的作用。
1. 统计过程控制(SPC)的概述SPC是美国贝尔实验室休哈特博士在20世纪二、三十年代所创立的理论[2]。
SPC利用抽样表能科学地区分出生产过程中产品质量的偶然波动与异常波动,从而对生产过程的异常及时告警,以便生产管理人员采取措施,消除异常,使过程处于受控状态。
但是,SPC可以判断过程的异常,及时报警,但不能找出异常是由什么原因引起的。
SPC作为先进的质量管理技术,其理论在不断的发展中,统计过程控制与诊断(SPCD)是其发展的第二阶段,弥补了SPC的不足,它既能及时告警,又能对异常进行诊断;SPCDA,即Statistieal Proeess Control,Diagnosis and Adjustment的简称,为其发展的第三阶段,这一阶段则在SPCD的基础上,对生产过程进行自动的调整,使生产过程处于稳态[3]。
SPCD是SPC发展的第二阶段,它是Statistieal Proeess Control and Diagnosis 的简称,即统计过程控制与诊断[3]。
SPCD弥补了SPC的不足,它既能及时告警,又能对异常进行诊断。
1982年,我国北京科技大学的张公绪教授,打破了SPC 控制理论的局限性,首创两种质量诊断理论,为统计质量诊断开辟了新的方向。
统计过程控制概述

我们必须在失败中寻找胜利,在绝望中寻求希望
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控制图应用
步骤三、计算R图控制线
UCLR R 3 R D4 R CLR R R LCLR R 3 R D3 R
控制图应用
步骤四、计算 图控制线 X
UCLX X 3 X X A2 R CLX X X LCLX X 3 X X A2 R
控制图应用
步骤五、作R图 a、根据控制线作图 b、数据描点,判稳 c、不稳定则控制过程,回步骤二
贯彻预防原则 应用统计技术 保持过程稳定 保证产品质量
SPC的特点
强调全员参与 强调统计方法 强调过程、体系
二、控制图原理
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控制图的结构:
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过程变差 偶然因素
过程固有 波动随机 对质量影响小
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控制图判异准则:
国标GB/T 4091-2001
UCL A B
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统计过程控制(简称SPC)

SPC统计过程控制SPC是Statistical Process Control的简称统计过程控制。
利用统计的方法来监控过程的状态,确定生产过程在管制的状态下,以降低产品品质的变异。
统计过程控制(简称SPC)是一种借助数理统计方法的过程控制工具。
它对生产过程进行分析评价,根据反馈信息及时发现系统性因素出现的征兆,并采取措施消除其影响,使过程维持在仅受随机性因素影响的受控状态,以达到控制质量的目的。
它认为,当过程仅受随机因素影响时,过程处于统计控制状态(简称受控状态);当过程中存在系统因素的影响时,过程处于统计失控状态(简称失控状态)。
由于过程波动具有统计规律性,当过程受控时,过程特性一般服从稳定的随机分布;而失控时,过程分布将发生改变。
SPC正是利用过程波动的统计规律性对过程进行分析控制。
因而,它强调过程在受控和有能力的状态下运行,从而使产品和服务稳定地满足顾客的要求。
实施SPC的过程一般分为两大步骤:首先用SPC工具对过程进行分析,如绘制分析用控制图等;根据分析结果采取必要措施:可能需要消除过程中的系统性因素,也可能需要管理层的介入来减小过程的随机波动以满足过程能力的需求。
第二步则是用控制图对过程进行监控。
控制图是SPC中最重要的工具。
目前在实际中大量运用的是基于Shewhart原理的传统控制图,但控制图不仅限于此。
近年来又逐步发展了一些先进的控制工具,如对小波动进行监控的EWMA和CUSUM控制图,对小批量多品种生产过程进行控制的比例控制图和目标控制图;对多重质量特性进行控制的控制图。
SPC源于上世纪二十年代,以美国Shewhart博士发明控制图为标志。
自创立以来,即在工业和服务等行业得到推广应用,自上世纪五十年代以来SPC在日本工业界的大量推广应用对日本产品质量的崛起起到了至关重要的作用;上世纪八十年代以后,世界许多大公司纷纷在自己内部积极推广应用SPC,而且对供应商也提出了相应要求。
在ISO9000及QS9000中也提出了在生产控制中应用SPC方法的要求。
《SPC—统计过程控制》

实质:以质量管理为灵魂, 以概率与统计为理论工具, 以控制图为应用工具, 对过程进行统计控制。
1、 SPC的内容: 一是利用控制图分析过程的稳定性,对过程存 在的异常因素进行预警; 二是计算过程能力指数分析稳定的过程能力满 足技术要求的程度,对过程质量进行评价。
2、SPC所体现的管理思想: 预防为主的思想 全员参与的思想 全过程控制思想 3、 SPC应用范围:生产过程、服务过程、管理过 程 4、SPC的增强功能: 诊断SPCD(statistical process control diagnosis): 利用统计技术对过程中各个阶段进行监控和诊断。 调整SPCDA(statistical process control diagnosis and adjustment):统计过程控制、诊断与调整。
SPC
Analyze Improve Control
SPC
Statistical Process Control
对过程进行统计控制 Process
第一节
SPC概述
一、过程(process): 过程:是将输入转化为输出的一组彼此相关的活动。 (旧:称工序,在6σ管理中称流程) 以x1x2,x3,---xn表示输入,以y表示输出,则一个过程可 以表示为 y=f(x1x2,x3,---xn)
第三节 两类错误和3σ方式 一、两类错误
误判 漏判
β α
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UCL CL LCL LSL
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二、 3σ方式 3σ方式即规定控制限: LCL= µ+3σ CL= µ UCL= µ-3σ 其中µ为总体均值,σ为总体标准差,此时犯 µ σ 一类错误的概率为0.0027。 0.0027 注意:规格限(Standard Limit):显示产品质量 合格与否, 控制限(Control Limit):区分偶然波动与 异常波动。
全面质量管理Total Quality Management

物业管理部企业管理知识培训资料一、TQC管理全面质量管理Total Quality Management(TQM ),是全面质量管理的简称。
它是指在全面社会的推动下,企业中所有部门,所有组织,所有量的因素,以优质的工作最经济的办法提供满足用户需要的产品的全部活动。
该管理模式盛行于上世纪八十年代,但至今开展这项活动仍然有着重要的意义。
二、6S管理整理(SEIRI)——将工作场所的任何物品区分为有必要和没有必要的,除了有必要的留下来,其他的都消除掉。
目的:腾出空间,空间活用,防止误用,塑造清爽的工作场所。
整顿(SEITON)——把留下来的必要用的物品依规定位置摆放,并放置整齐加以标识。
目的:工作场所一目了然,消除寻找物品的时间,整整齐齐的工作环境,消除过多的积压物品。
清扫(SEISO)——将工作场所内看得见与看不见的地方清扫干净,保持工作场所干净、亮丽的环境。
目的:稳定品质,减少工业伤害。
清洁(SEIKETSU)——将整理、整顿、清扫进行到底,并且制度化,经常保持环境处在美观的状态。
目的:创造明朗现场,维持上面3S成果。
素养(SHITSUKE)——每位成员养成良好的习惯,并遵守规则做事,培养积极主动的精神(也称习惯性)。
目的:培养有好习惯、遵守规则的员工,营造团队精神。
安全(SECURITY)——重视成员安全教育,每时每刻都有安全第一观念,防范于未然。
目的:建立起安全生产的环境,所有的工作应建立在安全的前提下。
用以下的简短语句来描述6S,也能方便记忆:整理:要与不要,一留一弃;整顿:科学布局,取用快捷;清扫:清除垃圾,美化环境;清洁:清洁环境,贯彻到底;素养:形成制度,养成习惯;安全:安全操作,以人为本.因前5个内容的日文罗马标注发音和后一项内容(安全)的英文单词都以“S”开头,所以简称6S现场管理。
三、6西格玛管理六西格玛是一套系统的业务改进方法体系,是旨在持续改进企业业务流程,实现客户满意的管理方法。
统计过程控制SPC培训教材ppt课件

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6. 直方图(Histogram;亦称柱状图):将所收集的测定特性值或结果 值,分为几个相等的区间作为横轴,并将各区间内所测定的特性值或 结果值依所出现的次数累积而成的面积,用柱子排起来的图形,称为 直方图。亦即指用来对特征数据进行分级整理,将杂乱无章的资料, 解析出其规律性,以得出其分布特征的统计分析的方法。
与要求相比偏高
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7. 控制图(Control Chart):用来表示一个过程特性的图象,图上标 有根据那个特性收集到的一些统计数据,如一条中心线、一条或两条 控制限,它能减少I类错误和Ⅱ类错误的净经济损失。它有两个基本 的用途:一是用来判定一个过程是否一直受统计控制;二是用来帮助 过程保持受控状态。亦即指附有控制界限的图表,用以描述样本数据 与界限比较。若数据超出界限或出现“链”及非随机图形,表示过程 存在特殊原因变差,则应采用适当的措施加以消除。 7.1 Ⅰ类错误:拒绝一个真实的假设。例如:采取了一个适用于特 殊原因的措施而实际上过程还没有发生变化;即过度控制。 7.2 Ⅱ类错误:没有拒绝一个错误的假设。例如:对实际上受特殊 原因影响的过程没有采取适当的措施;即控制不足。 7.3 计数值控制图与计量值控制图的应用比较:
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铸造车间产品生产废品统计表
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5. 特性要因分析图(Characteristic Diagram ;亦称石川图或鱼骨图/鱼刺图 或因果图):指将造成某项结果的众多原因,以有系统的方式来表达结果 (特性)与原因之间的关系图表。 5.1 因果图(Cause-and-Effect Diagram):一种用于解决单个问题的简 单工具,它对各种过程要素采用图形描述来分析过程可能的变差源, 也被称作鱼刺图(以其形状命名)或石川图(以其发明命名)。 A)、某项结果的形成,必定有其原因,应设法利用图解法找出其原 因来,这个概念是由日本品管大师石川馨博士提出的。 B)、特性要因图是利用5M+1E:人员(Man)、机器(Machine)、材 料(Material)、方法(Method)、测量(Measurement)、环 境(Environment)等五大类加以分析及应用的。
统计过程控制的几种常用方法

统计过程控制1、统计过程控制的基本知识1.1统计过程控制的基本概念统计过程控制(Stastistical Process Control简称SPC)是为了贯彻预防原则,应用统计方法对过程中的各个阶段进行评估和监控,建立并保持过程处于可接受的并且稳定的水平,从而保证产品与服务符合规定要求的一种技术。
SPC中的主要工具是控制图。
因此,要想推行SPC必须对控制图有一定深入的了解,否则就不可能通过SPC取得真正的实效。
对于来自现场的助理质量工程师而言,主要要求他们当好质量工程师的助手:(1)在现场能够较熟练地建立控制图;(2)在生产过程中对于控制图能够初步加以使用和判断;(3)能够针对出现的问题提出初步的解决措施。
大量实践证明,为了达到上述目的,单纯了解控制图理论公式的推导是行不通的,主要是需要掌握控制图的基本思路与基本概念,懂得各项操作的作用及其物理意义,并伴随以必要的练习与实践方能奏效。
1.2统计过程控制的作用(1)要想搞好质量管理首先应该明确下列两点:①贯彻预防原则是现代质量管理的核心与精髓。
②质量管理学科有一个十分重要的特点,即对于质量管理所提出的原则、方针、目标都要科学措施与科学方法来保证他们的实现。
这体现了质量管理学科的科学性。
为了保证预防原则的实现,20世纪20年代美国贝尔电话实验室成立了两个研究质量的课题组,一为过程控制组,学术领导人为休哈特;另一为产品控制组,学术领导人为道奇。
其后,休哈特提出了过程控制理论以及控制过程的具体工具——控制图。
道奇与罗米格则提出了抽样检验理论和抽样检验表。
这两个研究组的研究成果影响深远,在他们之后,虽然有数以千记的论文出现,但至今仍未能脱其左右。
休哈特与道奇是统计质量控制(SQC)奠基人。
1931年休哈特出版了他的代表作《加工产品质量的经济控制》这标志着统计过程控制时代的开始。
(2)“21世纪是质量的世纪”。
美国著名质量管理专家朱兰早在1994年的美国质量管理年会上即提出此论断,若干年来得到越来越多的人的认同。
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本科毕业设计(论文)外文翻译原文:SPC and Total Quality ManagementAbstract The seven basic tools of Statistical Process Control (SPC) are articulated, together with an understanding of how SPC is an essential element of Total Quality Management. The criteria to establish a Total Quality Operation are also discussed and the presentation will include case histories of problems examined and benefits realized.The creation of a Total Quality operationIt must be recognized that improvements in any aspects of a business operation may possibly lead to a state of continuous quality improvement, but Total Quality will only be achieved by a radical, co-ordinated approach throughout the entire operation, and that demands leadership.The creation of a Total Quality operation demands a balanced amount of attitudinal change, use of a management control system, together with application of appropriate tools and techniques. The common thread is management leadership and a dedicated passion to improve. A system without passion will not succeed, neither will passion without a system. However, improvement in general cannot be achieved without specific improvements being identified and realized. It is this focus on many specific improvement opportunities which produces a radical improvement in quality levels to break through existing barriers. Such intensive focus on specific improvement opportunities (sometimes called problems) demands the creation of teams with membership specific to the improvement action; the detailed knowledge and use of process improvement tools and techniques; together with dedicated management leadership. The creation of a Total Quality operation is the result of the optimal use of total human resourcesin the pursuit of excellent performance. It is an evolutionary process that comes about primarily by a change in traditional management style and behaviour. Since only management can decide on how the human resource is used within an organization, then the rate at which improvement progresses towards Total Quality is dependent solely on management skills, energy and knowledge of the improvement process.Leadership styleThe directive leadership style is essential in bringing about change, in particular when introducing quality improvement actions through projects and SPC.At Avon Rubber plc, 600 managers went through a 6-month Total Quality Management modular training programme, one element of which was that each manager (commencing with the Group Chief Executive and then cascading down), had to take on board a personally owned improvement project. One of the modules was called ‘Putting TQM into Practice’ and had an additional two and a half-day session entitled ‘Statistical Thinking’.All that I have related to in terms of commitment, dedication, passion, leadership styles and projects, is meaningless if none of it is used. Hence the importance to me of the statistical thinking session, which basically tells us ‘how’to improve, by demanding its use in a real work situation.I prefer ‘statistical thinking’ rather than just SPC—my rationale is that ‘I am giving skills such that others may be capable of understanding their management processes to enable them to improve them in a systematic manner’. This ‘statistical thinking’ description is generally acceptable in the non-manufacturing support areas, whereas SPC has (unfortunately) overtones of ‘analysis-paralysis’.Recipe for successThis section concentrates on how to achieve quality improvement successes (having gained top level commitment, senior personnel are involved inproviding leadership to transform their operation), and how everybody's commitment within the operation can be harnessed towards achieving Total Quality. It is no secret that this transaction demands three things:(a) leadership to ensure the required attitudinal culture (the management attitude);(b) a well defined management process which indicates how to achieve what at every stage in the internal customer/supplier chain (the management system);(c) an ability to define and quantify a problem, an ability to solve problems utilizing well established techniques, and harness the inputs of all team members (tools and techniques of process management—SPC). The tools and techniques of process managementA process is the transformation of a set of inputs, which can include actions, methods and operations, into desired outputs, in the form of products, information, services or, generally, results. In each area of an organization there are many processes taking place. For example, the finance department may be involved in budgeting processes, accounting processes, salary and wage processes, costing processes, etc. Each process in every department or functional area can be analysed by an examination of the inputs and outputs. This will determine the action necessary to improve quality.The tools and techniques used to improve process management activities have generally been the tool-kit used by specialist quality practitioners. All managers must have access to this tool-kit and have an understanding of how the tools may be used to best advantage within their area of activity, to assist with continuous improvement.The use of factual information, collected and presented using statistical techniques, opens a channel of communication not available through other problem solving methods. Continuous improvement in thequality of products and services can be obtained without major capital investments if all levels of an organization are part of the problem solving team.By using reliable methods, creating a favourable environment for problem solving, and continuing to improve by using SPC techniques, a spiral of never-ending improvement can be attained in any organization, which is the theme of Total Quality Management.Process control requires us to manage real-time data, acting on information from the process, not the product. It requires an ability to speak in the language not of percentage rejects but process capability. Special cause variation must be identified such that it is killed off for ever, and common cause variation must have a management plan to reduce the extent of its effect.The management climate must be such that there is a dismissal of the quality tradition which says that if it meets the specification that's OK—no further improvement need be made.The seven basic tools of SPCIt needs to be stressed that SPC is not all about Shewhart control charts. Understanding a process such that it can be improved in a systematic way demands knowledge of the following seven basic tools, sometimes called ‘The Seven Ishikawa Tools’.(1)Process sequence flow charts.(2)Tally chart, check sheet or other simple data collection method.(3)Histogram.(4)Pareto chart.(5)Cause and effect diagram.(6)Scatter diagram.(7)Control charts.The above order is not a random allocation, but indicates how the toolsmay be used, namely:(a) What is the process? (not what we think or what somebody tells us—but fact); if we don't know all the stages of a process, how can we begin to improve it?(b) How are we doing at each of the stages of the process? Use a simple data collection technique to tell us how often what goes wrong—again we need the facts.(c) How can we get a meaningful picture of all this data? Numerical data alone does not highlight important aspects of the data. A histogram displays the spread of the data.(d) Which problem should we work on first? The Pareto chart allows us to separate the ‘the vital few from the trivial many’, sometimes called the 80/20 rule.(e) Using the brainstorming principle and teamwork approach let's ask what factors may possibly be causing the problem? The brainstorm output can then be displayed in a structured way under such headings as men, machines, materials, methods, maintenance and environment. The chart takes the shape of a fishbone (sometimes called an Ishikawa [1974] chart after its founder). The solution effect diagram (sometimes called a reverse fishbone diagram) can be used to determine what effect a proposed solution could have on such things as men, machines, method, materials, maintenance and the environment. In this way a proposed solution may be verified to have positive benefits.(f) The scatter diagram may be used to verify suspected relationships, that is confirm whether there is or is not any relationship.(g) Control charts may be used to monitor the output from a process. Using the above techniques the capability of the process may be increased as special cause disturbance factors disappear and random cause variability is reduced.The affinity of SPC, Problem Solving Process, Quality Improvement Process and TQMIn order to use SPC techniques effectively, a sequence of problem solving steps must be used to find the shortest reliable path that leads to the true cause of the problem. Management must take actions to make permanent improvements to the process that will prevent recurrence of the same problems in the future. The eight-step Problem Solving Process clearly assists with this process.The eight-step Problem Solving ProcessSTEP 1. Identify and select the problem. Ask—what do we want to change? We should consider which problems present the greatest opportunity for improvement. The problem should be initially stated in terms of ‘should vs actual’ so that the level of improvement desired can be clearly understood by all. Big problems should be broken into smaller problems. Statistical tools to use here: flow charts, check sheets, Pareto analysis, brainstorming.STEP 2. Define the problem clearly. Ask—what's preventing us from achievement? We should collect and analyse data to define the problem in a quantitative manner and review the problem statement, if necessary. We can also define the benefits of improvement. Statistical tools to use here: check sheets, Pareto analysis, pie charts, run diagrams, histograms, concentration diagrams, line graphs.STEP 3. Plan to take action. Ask—how do we plan to make improvements? Who will participate? How do we allocate tasks? What timescales are involved? What means of communicating/reporting progress will be used? Have we the necessary skills to go to the next stage?STEP 4. Find the root cause. Ask—how could we make the change? From this we will generate many possible solutions. Statistical tools to use here: brainstorming, cause and effect diagrams, check sheets, scatter diagrams,solution effect diagrams.Ask—are we able to turn the problem on/off at will? For this we may need to collect more data, verify by experimentation and testing relationships. Statistical tools to use here: check sheets, Pareto analysis, scatter diagrams, solution effect diagrams.STEP 5. Select the solution. Ask—what's the best way to do it? We may have to divide the solution into sequential, easily manageable steps. We should ensure that everyone knows what they have to do. A commitment strategy for solution ownership should be developed. A control system should be established to ensure that the specific tasks are being performed. The implementation of the solution will generate change, data on this will need to be collected. A contingency plan should be established to consider potential problems. Statistical tools to use here: flow charts, check sheets, Pareto analysis, run diagrams, histograms, concentration diagrams, scatter diagrams, brainstorming, control charts.STEP 6. Implement agreed solution. Ask—are we following the plan? Be prepared to modify plans as expected—or unexpected—events occur. Use a control system to monitor progress. Statistical tools to use here: Pareto analysis, histograms, control charts.STEP 7. Ensure a permanent fix. Ask—has the problem recurred? Continue to use the control system and monitor. Recognize the ‘spotlight’ effect. Recognize the success and the input of team members; such recognition can spread the enthusiasm to others. Statistical tool: control chart. STEP 8. Continue to improve. Ask—how can we do it better (more cost effectively)? Consider mistake-proofing, increase the process capability, use cost of quality analysis. Statistical tools: all of those previously named that is start at beginning again!ConclusionThe theme (and driving force) of Total Quality Management is continuousimprovement. If we are to improve all (or any) of our management processes, it is essential to know what the process is, what we expect the process to give us and what it is actually giving us. For this we need a structured Problem Solving Process used in conjunction with a Quality Improvement Process. The basic seven tools of SPC, utilized in Japan by Quality Circles under the guidance of the late Dr Kaoru Ishikawa, are an essential element of the continuous improvement activity. Total Quality Management is by definition a management led process, harnessing the resource available to it. Hence the degree of utilization of SPC is dependent upon the degree of management knowledge and understanding of its benefits.Source: TOTAL QUALITY MANAGEMENT,VOL.1,NO.2,1990译文:统计过程控制和全面质量管理摘要统计过程控制(SPC)的七个基本工具是相互连接的,使我们理解统计过程控制如何成为全面质量管理的一个基本要素。