刘雯街拍2017高清图片:DMAIC

  
什么是DMAIC方法
6西格玛管理不仅是理念，同时也是一套业绩突破的方法。它将理念变为行动，将目标变为现实。这套方法就是6西格玛改进方法DMAIC和6西格玛设计方法DFSS。DMAIC是指定义（Define）、测量（Measure）、分析（Analyze）、改进（Improve）、控制（Control）五个阶段构成的过程改进方法，一般用于对现有流程的改进，包括制造过程、服务过程以及工作过程等等。DFSS是Design for Six Sigma的缩写，是指对新流程、新产品的设计方法。
一个完整的6西格玛改进项目应完成“定义D”、“测量M”、“分析A”、“改进I”和“控制C”5个阶段的工作。每个阶段又由若干个工作步骤构成。虽然，Motorola、GE、6Sigma Plus、Smart Solution等采用的工作步骤不尽相同，有的采用6步法，有的采用12步法或24步法。但每个阶段的主要内容是大致相同的.
每个阶段都由一系列工具方法支持该阶段目标的实现。
参考：http://dmaic.vicp.net
Six Sigma is a business management strategy, originally developed by Motorola, that today enjoys widespread application in many sectors of industry.
Six Sigma seeks to identify and remove the causes of defects and errors in manufacturing and business processes.[1] It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization ("Black Belts" etc.) who are experts in these methods.[1] Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified financial targets (cost reduction or profit increase).[1]
Contents [hide]
1 Historical overview
1.1 Origin and meaning of the term "six sigma process"
1.1.1 The role of the 1.5 sigma shift
1.1.2 Sigma levels
2 Methods
2.1 DMAIC
2.2 DMADV
3 Implementation roles
4 Quality management tools and methodologies used in Six Sigma
5 Software used for Six Sigma
6 List of Six Sigma companies
7 Reception
7.1 Lack of originality
7.2 Role of consultants
7.3 Studies that indicate negative effects caused by Six Sigma
7.4 Based on arbitrary standards
7.5 Criticism of the 1.5 sigma shift
8 See also
9 References
10 Further reading
11 External links
Historical overview
Six Sigma was originally developed as a set of practices designed to improve manufacturing processes and eliminate defects, but its application was subsequently extended to other types of business processes as well.[2] In Six Sigma, a defect is defined as anything that could lead to customer dissatisfaction.[1]
The particulars of the methodology were first formulated by Bill Smith at Motorola in 1986.[3] Six Sigma was heavily inspired by six preceding decades of quality improvement methodologies such as quality control, TQM, and Zero Defects, based on the work of pioneers such as Shewhart, Deming, Juran, Ishikawa,Taguchi and others.
Like its predecessors, Six Sigma asserts that –
Continuous efforts to achieve stable and predictable process results (i.e. reduce process variation) are of vital importance to business success.
Manufacturing and business processes have characteristics that can be measured, analyzed, improved and controlled.
Achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management.
Features that set Six Sigma apart from previous quality improvement initiatives include –
A clear focus on achieving measurable and quantifiable financial returns from any Six Sigma project.[1]
An increased emphasis on strong and passionate management leadership and support.[1]
A special infrastructure of "Champions," "Master Black Belts," "Black Belts," etc. to lead and implement the Six Sigma approach.[1]
A clear commitment to making decisions on the basis of verifiable data, rather than assumptions and guesswork.[1]
The term "Six Sigma" is derived from a field of statistics known as process capability studies. Originally, it referred to the ability of manufacturing processes to produce a very high proportion of output within specification. Processes that operate with "six sigma quality" over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities (DPMO).[4][5] Six Sigma's implicit goal is to improve all processes to that level of quality or better.
Six Sigma is a registered service mark and trademark of Motorola, Inc.[6] Motorola has reported over US$17 billion in savings[7] from Six Sigma as of 2006.
Other early adopters of Six Sigma who achieved well-publicized success include Honeywell (previously known as AlliedSignal) and General Electric, where the method was introduced by Jack Welch.[8] By the late 1990s, about two-thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of reducing costs and improving quality.[9]
In recent years, Six Sigma has sometimes been combined with lean manufacturing to yield a methodology named Lean Six Sigma.
[edit]Origin and meaning of the term "six sigma process"
Graph of the normal distribution, which underlies the statistical assumptions of the Six Sigma model. The Greek letter σ marks the distance on the horizontal axis between the mean, µ, and the curve's inflection point. The greater this distance is, the greater is the spread of values encountered. For the curve shown in red above, µ = 0 and σ = 1. The other curves illustrate different values of µ and σ.
The following outlines the statistical background of the term Six Sigma: Sigma (the lower-case Greek letter σ) is used to represent the standard deviation (a measure of variation) of a statistical population. The term "six sigma process," comes from the notion that if one has six standard deviations between the mean of a process and the nearest specification limit, there will be practically no items that fail to meet the specifications.[5] This is based on the calculation method employed in a process capability study.
In a capability study, the number of standard deviations between the process mean and the nearest specification limit is given in sigma units. As process standard deviation goes up, or the mean of the process moves away from the center of the tolerance, fewer standard deviations will fit between the mean and the nearest specification limit, decreasing the sigma number.[5]
[edit]The role of the 1.5 sigma shift
Experience has shown that in the long term, processes usually do not perform as well as they do in the short.[5] As a result, the number of sigmas that will fit between the process mean and the nearest specification limit is likely to drop over time, compared to an initial short-term study.[5] To account for this real-life increase in process variation over time, an empirically-based 1.5 sigma shift is introduced into the calculation.[10][5] According to this idea, a process that fits six sigmas between the process mean and the nearest specification limit in a short-term study will in the long term only fit 4.5 sigmas – either because the process mean will move over time, or because the long-term standard deviation of the process will be greater than that observed in the short term, or both.[5]
Hence the widely accepted definition of a six sigma process is one that produces 3.4 defective parts per million opportunities (DPMO). This is based on the fact that a process that is normally distributed will have 3.4 parts per million beyond a point that is 4.5 standard deviations above or below the mean (one-sided capability study).[5] So the 3.4 DPMO of a "Six Sigma" process in fact corresponds to 4.5 sigmas, namely 6 sigmas minus the 1.5 sigma shift introduced to account for long-term variation.[5] This is designed to prevent underestimation of the defect levels likely to be encountered in real-life operation.[5]
[edit]Sigma levels
Taking the 1.5 sigma shift into account, short-term sigma levels correspond to the following long-term DPMO values (one-sided):
One Sigma = 690,000 DPMO = 31% efficiency
Two Sigma = 308,000 DPMO = 69.2% efficiency
Three Sigma = 66,800 DPMO = 93.32% efficiency
Four Sigma = 6,210 DPMO = 99.379% efficiency
Five Sigma = 230 DPMO = 99.977% efficiency
Six Sigma = 3.4 DPMO = 99.9997% efficiency
[edit]Methods
Six Sigma has two key methods: DMAIC and DMADV, both inspired by Deming's Plan-Do-Check-Act Cycle.[9] DMAIC is used to improve an existing business process; DMADV is used to create new product or process designs.[9]
[edit]DMAIC
The basic method consists of the following five steps:
Define process improvement goals that are consistent with customer demands and the enterprise strategy.
Measure key aspects of the current process and collect relevant data.
Analyze the data to verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered.
Improve or optimize the process based upon data analysis using techniques like Design of experiments.
Control to ensure that any deviations from target are corrected before they result in defects. Set up pilot runs to establish process capability, move on to production, set up control mechanisms and continuously monitor the process.
[edit]DMADV
The basic method consists of the following five steps:
Define design goals that are consistent with customer demands and the enterprise strategy.
Measure and identify CTQs (characteristics that are Critical To Quality), product capabilities, production process capability, and risks.
Analyze to develop and design alternatives, create a high-level design and evaluate design capability to select the best design.
Design details, optimize the design, and plan for design verification. This phase may require simulations.
Verify the design, set up pilot runs, implement the production process and hand it over to the process owners.
DMADV is also known as DFSS, an abbreviation of "Design For Six Sigma".[9]
[edit]Implementation roles
One of the key innovations of Six Sigma is the professionalizing of quality management functions. Prior to Six Sigma, quality management in practice was largely relegated to the production floor and to statisticians in a separate quality department. Six Sigma borrows martial arts ranking terminology to define a hierarchy (and career path) that cuts across all business functions and a promotion path straight into the executive suite.
Six Sigma identifies several key roles for its successful implementation.[11]
Executive Leadership includes the CEO and other members of top management. They are responsible for setting up a vision for Six Sigma implementation. They also empower the other role holders with the freedom and resources to explore new ideas for breakthrough improvements.
Champions are responsible for Six Sigma implementation across the organization in an integrated manner. The Executive Leadership draws them from upper management. Champions also act as mentors to Black Belts.
Master Black Belts, identified by champions, act as in-house coaches on Six Sigma. They devote 100% of their time to Six Sigma. They assist champions and guide Black Belts and Green Belts. Apart from statistical tasks, their time is spent on ensuring consistent application of Six Sigma across various functions and departments.
Black Belts operate under Master Black Belts to apply Six Sigma methodology to specific projects. They devote 100% of their time to Six Sigma. They primarily focus on Six Sigma project execution, whereas Champions and Master Black Belts focus on identifying projects/functions for Six Sigma.
Green Belts are the employees who take up Six Sigma implementation along with their other job responsibilities. They operate under the guidance of Black Belts.
[edit]Quality management tools and methodologies used in Six Sigma
Six Sigma makes use of a great number of established quality management methods that are also used outside of Six Sigma. The following table shows an overview of the main methods used.
5 Whys
Analysis of variance
ANOVA Gauge R&R
Axiomatic design
Business Process Mapping
Catapult exercise on variability
Cause & effects diagram (also known as fishbone or Ishikawa diagram)
Chi-square test of independence and fits
Control chart
Correlation
Cost-benefit analysis
CTQ tree
Quantitative marketing research through use of Enterprise Feedback Management (EFM) systems
Design of experiments
Failure mode and effects analysis
General linear model
Histograms
Homoscedasticity
Pareto chart
Pick chart
Process capability
Regression analysis
Root cause analysis
Run charts
SIPOC analysis (Suppliers, Inputs, Process, Outputs, Customers)
Stratification
Taguchi methods
Thought process map
TRIZ
[edit]Software used for Six Sigma
Main article: List of Six Sigma software packages
[edit]List of Six Sigma companies
Main article: List of Six Sigma companies
[edit]Reception
Six Sigma has made a huge impact on industry and is widely employed as a business strategy for achieving and sustaining operational and service excellence.[1] However, there have also been various criticisms of Six Sigma.
[edit]Lack of originality
Noted quality expert, Joseph M. Juran, has described Six Sigma as "a basic version of quality improvement," stating that "[t]here is nothing new there. It includes what we used to call facilitators. They've adopted more flamboyant terms, like belts with different colors. I think that concept has merit to set apart, to create specialists who can be very helpful. Again, that's not a new idea. The American Society for Quality long ago established certificates, such as for reliability engineers."[12]
[edit]Role of consultants
The use of "Black Belts" as itinerant change agents is controversial as it has created a cottage industry of training and certification. Critics argue there is overselling of Six Sigma by too great a number of consulting firms, many of which claim expertise in Six Sigma when they only have a rudimentary understanding of the tools and techniques involved.[1]
The expansion of the various "Belts" to include "Green Belts," "Master Black Belts" and "Gold Belts" is commonly seen as a parallel to the various "belt factories" that exist in martial arts.[citation needed]
[edit]Studies that indicate negative effects caused by Six Sigma
A Fortune article stated that "of 58 large companies that have announced Six Sigma programs, 91 percent have trailed the S&P 500 since." The statement is attributed to "an analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-improvement process)."[13] The gist of the article is that Six Sigma is effective at what it is intended to do, but that it is "narrowly designed to fix an existing process" and does not help in "coming up with new products or disruptive technologies." Many of these claims have been argued as being in error or ill-informed.[14][15]
A Business Week article says that James McNerney's introduction of Six Sigma at 3M may have had the effect of stifling creativity. It cites two Wharton School professors who say that Six Sigma leads to incremental innovation at the expense of blue-sky work.[16]
[edit]Based on arbitrary standards
While 3.4 defects per million opportunities might work well for certain products/processes, it might not be ideal or cost-effective for others. Apacemaker process might need higher standards, for example, whereas a direct mail advertising campaign might need lower ones. The basis and justification for choosing 6 as the number of standard deviations is not clearly explained. In addition, the Six Sigma model assumes that the process data always conform to the normal distribution. The calculation of defect rates for situations where the normal distribution model does not apply is not properly addressed in the current Six Sigma literature.[1]
[edit]Criticism of the 1.5 sigma shift
Because of its arbitrary nature, the 1.5 sigma shift has been dismissed as "goofy" by the statistician Donald J. Wheeler.[17] Its universal applicability is seen as doubtful.[1]
The 1.5 sigma shift has also been contentious because it results in stated "sigma levels" that reflect short-term rather than long-term performance: a process that has long-term defect levels corresponding to 4.5 sigma performance is, by Six Sigma convention, described as a "6 sigma process."[5][18] The accepted Six Sigma scoring system thus cannot be equated to actual normal distribution probabilities for the stated number of standard deviations, and this has been a key bone of contention about how Six Sigma measures are defined.[18] The fact that it is rarely explained that a "6 sigma" process will have long-term defect rates corresponding to 4.5 sigma performance rather than actual 6 sigma performance has led several commentators to express the opinion that Six Sigma is a confidence trick.[5]
DMAIC模型在人力资源培训的应用
进入新经济时代，市场环境变得更加复杂与多变，企业员工的知识、技能、素质等方面都受到不断冲击!许多企业由于人力资源的培训与开发难以抵挡这些冲击而最终走向衰退。 培训与开发是人力资源管理的重点和难点，很多企业为此采取了大量的改革措施，但是却效果很差。以六西格玛管理的DMAIC模型对人力资源培训与开发管理进行分析。
根据DMAIC模型及其原理,人力资源管理应采取以下步骤：
（1）定义阶段（D阶段）。 确定员工的知识、技能和素质等方面的关键需求，并识别需求改进的培训项目或培训管理流程，并将改进的内容界定在合理的范围内。主要方法有：胜任力模型、行为事件访谈（BEIs）、专家小组法、问卷调查法、全方位评价法、专家系统数据库和观察法等。
（2）测量阶段（M阶段）。通过对现有培训流程的测量，辨别核心流程和辅助流程；识别影响培训流程输出的输入要素，并对测量系统的有效性作出评价。 主要方法有：AFP法、模糊综合评判法、直方图、矩阵数据分析图等。
（3）分析阶段（A阶段）。通过数据分析，确定影响培训流程输出的关键因素，即确定培训过程的关键影响因素。主要方法有：鱼骨图、帕拉图、回归分析、因子分析等。
（4）改进阶段（I 阶段）。寻找优化培训流程并消除或减少关键输入因素影响的方案，使流程的缺陷或变异降低到最小程度。 主要方法有：流程再造等。
（5）控制阶段(C阶段）。使改进后的流程程序化，并通过有效的监测手段，确保流程改进的成果。 主要方法有：标准化、程序化、制度化等。
DMAIC模型在人力资源培训的应用分析
1.定义顾客需求(define)
六西格玛管理是以顾客为中心,强调关注顾客的需求。它的出发点就是研究客户最需要的是什么?最关心的是什么？那么，培训开发的顾客是谁呢？是企业的人才需求，准确地说就是培训需求。培训需求分析是整个培训开发工作的出发点，其准确与否直接决定了整个培训开发过程的有效性大小。令人遗憾的是，很多企业对培训需求重视不够，或想重视但无能为力。传统的培训需求分析主要基于绩效要求与现有绩效之间的“绩效差距”，并以此来制定员工的培训计划。有些甚至只是在每年年底向各部门发一份培训需求申请表，由部门自主申请培训项目，然后人力资源部再根据公司每年的培训经费做个“平衡”，再依平衡的结果做培训计划。
如何全面、准确地确定培训需求呢？首先是确定员工要掌握什么样的知识、技能和素质，然后分析测量员工目前所具有的水平，两者之“差距”，便是培训需求。当然，员工的要求不能只看考核指标，而应在公司方针、战略框架下进行职位分析，分析企业所有职位特别是关键职位，明确这些职位的工作内容、任职资格等相关内容。关于职位分析，目前有一种新方法，就是胜任力模型(competency)，它是美国著名的心理学家、哈佛大学教授麦克里兰(McClelland)博士的研究成果。岗位胜任特征，是指根据岗位的工作要求，确保该岗位的人员能够顺利完成该岗位工作的个人特征结构，它可以是动机、特质、自我形象、态度或价值观、某领域知识、认知或行为技能，且能显著区分优秀与一般绩效的个体特征的综合表现。
在科学、准确地进行职位分析之后，还要测量员工目前的真实水平，以便确定培训需求。企业一般都是通过绩效考核的结果来判断员工的能力，但目前大部分企业的绩效考核在科学、合理、客观等方面还存在很多不足，直接以绩效考核结果来决定培训项目，显然是不科学的。在不断完善绩效考核体系的同时，还应分析以下几个问题:(1)还有哪些知识不足?(2)还有哪些技能欠缺?(3)素质有没有达到要求?
2.评估当前绩效(Measure)
评估当前绩效阶段，并不是指员工的绩效考核，而是评估公司当前培训管理流程的绩效，即测量公司的培训管理流程，看其是否能够满足以上确定的培训需求。
评估培训流程的当前绩效，工作量和难度都很大，它不但要测量整个培训流程的绩效，而且要测量培训需求分析、制定培训计划、培训计划实施以及效果评估等各个环节的绩效。需要统计、分析近三年流程相关的各方面数据，通过比较才有可能准确反映流程各环节的当前绩效。
3.原因分析(Analyze)
原因分析阶段，主要是根据统计分析问题。通过评估当前绩效阶段取得必要的数据后，在分析阶段需要我们寻找问题的原因，找出影响目前绩效的潜在问题及其影响因素。原因分析的方法有很多，最简单的是利用鱼骨图找出影响当前绩效的所有相关原因，再用帕拉图确定关键因素，也可以利用流程分析、图形分析、假设检定、相关分析、回归分析、因子分析等统计方法。不管用哪种方法，都离不开数据统计，一切以数据和事实说话，而且往往需要多次分析才能找出真正影响当前绩效的关键因素。
4.改进措施(Improve)
本阶段的任务是，通过以上的原因分析，找出影响流程输出变化的关键因素，针对关键因素采取改进措施。六西格玛管理与其他管理的最大区别之一就是关注流程，所以改进方法主要是流程再造，而且要首先考虑核心流程，其次才考虑辅助流程。改进措施是否有效，与以上的M阶段和A阶段的工作结果有密切联系，即如果测量当前绩效不准，分析原因有误，改进措施当然就不会产生良好的效果。因此，如果改进措施没有效果，必须重新进行绩效评估和原因分析，经过多次循环，一直到改进措施产生积极效果，才能进入下一个阶段。
5.控制实施(Control)
控制是为了稳固以上改进的效果。如果通过改进措施之后，培训效果得到良好的改进，就可能通过制定相关制度进行程序化、标准化，同时可使用SPC、FMEA、错误证实等工具来发展与施行流程控制计划。改革总是难以毕其功于一役，旧的问题解决了，可能仍有遗留问题或产生新的矛盾，只有多次按照DMAIC模型进行改进，才能达到持续改进的效果。