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Organizations put statistical engineering to the test, see results
组织应用统计工程实例及成果

by Roger W. Hoerl and Ronald D. Snee

A review of past Statistics Roundtable columns reveals that statisticians and quality professionals are always looking for better ways to increase the breadth and effectiveness of the use of statistical thinking and methods.
过往Statistics Roundtable 专栏的许多文字表明,统计和质量专家一直在寻找更广泛,更有效的应用统计理论和方法的途径。

In last month’s column, we introduced statistical engineering as an approach that links statistical thinking with statistical methods and provides a mechanism for improving the effectiveness of statistical thinking and methods.1
上个月的专栏,我们介绍了联结统计原理和应用并提高它们效率的统计工程学。

Statistical engineering works because statistical concepts, methods and tools are linked and sequenced, based on sound science and embedded in work processes with the aid of software. Embedding—including statistical methods in the standard operating procedures for business processes—is a powerful method of institutionalizing the proper use of statistical methods.
统计工程的作用是基于良好的基础科学,辅以辅助制造的软件,实现统计原理,方法和工具的联结和接续。包括业务流程标准化的统计方法在内的辅助措施,构成了统计方法合理应用的强有力的制度。

Statistical engineering is effective in solving problems and improving processes. What follows are several cases illustrating how statistical engineering is used and the breadth of its application.
统计工程精于解决问题,改进制程。下面的例子会说明统计工程是如何被广泛应用的。

Transactional processes
交易流程

The first example of statistical engineering is improving the performance of a transactional process: the process of collecting money from those who are past due on their accounts.
第一个例子,代收逾期货款流程的改进。

Statistical thinking and methods, as well as proper use of data, can be imbedded into the operation of the process to improve performance and to institutionalize this improved approach. Table 1 illustrates some simple ways statistical thinking and methods can be imbedded in such a process. The statistical tools involved include process maps, run charts, control charts, Pareto charts, measurement system analysis using attribute measurement studies, and design of experiments (DoE
统计原理,方法以及数据的有效应用,可以在提高过程绩效中使用并将改进方法制度化。表1表明,基础的统计原理和方法可以在这样的流程内使用,应用的统计工具包括流程图,运行图,控制图,柏拉图,测量系统分析,因果图,实验设计。






用统计工程来改进信息收集过程
方法 目标
培训内容增加流程图 明确流程操作中的文件和交流和关键过程
用运行图和控制图定义并跟踪关键测量 定义工作目标标准,随时确认过程绩效
用柏拉图来管理每月的账户违约的原因 明确执行过程中变异的真因
建立标准程序对不连续的测量值进行分析优于柏拉图 保证违约原因能够被准确侦测,并对不确定的侦测存档
建立标准程序按设计好的方法改进信息收集策略 用科学的方法保证工作人员使用最合适的方法

Perhaps the only method requiring some explanation is the use of DoE to improve collection strategies. In fact, DoE has many potential applications in the service industries.2 This first example is based on actual DoE applications in collections at General Electric (GE3
也许唯一要解释的就是收款计划中使用实验设计方法(DOE),其实DOE在服务业的应用潜力还很大。下面是一个基于GE公司在收款过程中DOE实际应用的例子。

In this case, GE’s credit card division had many collectors attempting to find customers who owed money on their cards, but they could not be found at the address or phone numbers on record. Many of these customers were willing to pay, but GE had no way of getting them their bills.
这个案子中,GE的信用卡部有很多收款人会努力搜寻卡里还欠账的顾客,但是他们在记录上无法获得这些人的电话或地址。很多客人愿意支付,但GE却无法让他们拿到账单。

Unfortunately, each collector had his or her own process, usually involving multiple external data sources, such as external credit agencies, public records or other GE credit-card files.
不幸的是,每个收款人有自己的工作方式,通常涉及多种外部资料,包括外部信用机构、公共记录和其他GE信用卡文件。

By applying DoE to identify the most effective collection strategy, GE was able to standardize the approach taken by collectors, resulting in additional collections of almost $3 million per year.
应用DOE寻找最有效的搜寻策略,GE把收款人所采取的方式标准化,从而实现每年多回收大约300万美元。

At GE, the contribution of statistical engineering was to identify how methods effective in one application arena could also be applied in a new arena—collections—and also to ensure the ongoing application of these methods by embedding them into standard work processes.
在GE,统计工程不仅应用于确定各种方式在既有环境下的有效性,同时在新环境下也可以得到令人满意的应用,并通过制度化确保其做出持续贡献。

Managing product quality
产品质量管理

Another tangible example of statistical engineering in the field of quality improvement is the Product Quality Management System (PQM) developed at DuPont in the 1970s. PQM is an overall framework for managing the quality of a product or service. It provides an operational system that enables marketing, R&D, production and support personnel to work together to meet increasingly stringent customer requirements.
另一个明显的例子是1970年代,统计工程在都彭产品品质管理体系(PQM)的质量改进领域的使用。PQM是产品品质或服务的管理的总的框架,它提供了一个使业务,研发,生产和支援部门通过团队合作满足顾客日益严苛要求的系统。

In his 1986 American Statistical Association Invited Presidential Address, DuPont CEO Richard E. Heckert commented:
在1986年美国统计委员会高端邀请会上,DuPont CEO Richard E. Heckert 这样说:

"Within two years, product quality had improved to the point of commanding a marketplace advantage, and more than $30 million had been gained in operating cost improvements. The statistically based PQM system developed for ‘Dacron’ was expanded to other products with further contributions in earnings."4
在过去2年,改善的产品品质,使我们在市场上占据优势,经营成本的精益让每年可以多赚3千万美元。为DACRON开发的以统计为基石的PQM系统将会在其他产品上做出更大的贡献。

The statistical tools embedded in the PQM approach included:
组成PQM方法的统计工具有:

• Product and process sampling schemes.
• 过程和产品的抽样方案
• Product lot release methods.
• 产品转量产管理
• Analysis of variance and variance components.
• 变异及其组成分析
• Cumulative sum control chart process control.
• 制程累积控制图
• Shewhart control.
• 休哈特控制图
• Interlaboratory studies of measurement methods.
• 测试方面的实验室研究
• DoE.
• DOE
• Response surface method.
• 响应面方法
• Data graphics.
• 数据制图

A training system was also in place to provide DuPont staff with the needed knowledge and skills to use PQM.
DUPONT建立了一个培训系统,指导员工掌握使用质量监测(PQM)需要的知识和技能。

Managing product quality was emphasized the tools were not. This was evident in the role definitions of PQM statisticians and quality professionals found in DuPont’s PQM manual in 1988:
产品质量管理被再三强调但是统计工具被忽略了。
这一点从1986年DUPONT PQM手册中关于PQM中统计和质量专家的角色定义能够很明显的体现出来:

• Leaders in developing their organization’s strategy for quality management.
• 负责制定组织关于质量管理的策略
• Leaders in developing technology systems for quality management.
• 负责质量管理的工艺制定
• Participants in the business planning process.
• 业务计划流程参与者
• Participants in problem-solving activities.
• 问题解决参与者
• Leaders in initiating and implementing quality management training systems.
• 负责发起和促进质量管理的培训系统

This manual, which goes back more than 20 years, indicates that the roles of statisticians and quality professionals are different when embedding statistical thinking and methods in the processes used to operate the business. Leadership is required by those using statistical engineering. This example illustrates the leadership role needed to implement statistical engineering by connecting statistical tools with statistical thinking. This was illustrated in Figure 1 in last month’s Statistics Roundtable column.5
这本20多年前的手册,说明在把统计原理和方法嫁接到商务流程中,统计专家和质量专家是不同的角色。使用统计方法的人被强调的却是领导力,也从侧面反应出在实现统计原理,统计方法为基础的统计工程应用时,领导者是必须的。这也是上期图1说明的内容。

The contribution of statistical engineering in this example was to integrate various techniques (statistical and otherwise), software, a training system, a manual and new roles for statisticians and quality professionals into an overall quality management system to improve quality at lower costs.
统计工程在这个例子时整合了多种技术(统计以及其他),软件,培训机制,文件,统计专家的新角色,质量专家,从而形成了一个低成本的质量改进的管理系统。

In essence, the whole was greater than the sum of the parts. This difference was the unique contribution of statistical engineering.
整体功能大于局部之和,这也是他与统计工具简单相加的区别。

Streamlining experimentation
精益案例

Another example involves streamlining experimentation. This application of statistical engineering was developed at DuPont in the 1960s and was offered in public workshops beginning in the 1970s.6
这个例子是关于精益的。是DUPONT在1960年代发展起来的并在1970年代被大量使用的统计工程应用。

The strategy identifies three experimental environments: screening, characterization and optimization. The strategy sequences and links a variety of experimental designs that are used depending on the experimental environment.
策略是三个过程:筛选,鉴定和优化,他们是一系列依赖环境的过程设计的接续和联结

The screening phase explores the effects of a large number of variables with the objective of identifying a smaller number of variables to study further in characterization or optimization experiments. Screening studies typically use fractional-factorial and Plackett-Burman designs to collect data. Additional screening experiments involving additional factors may be needed when results of the initial screening experiments aren’t promising. On several occasions, we’ve seen the screening experiment solve the problem.
筛选阶段探讨了大量的变量(其中较少的已被识别)对筛选和优化的影响。筛选研究通常使用分数因子和Plackett-Burman设计收集数据。初步筛选实验的结果并不乐观时,可能需要另外设计分数因子,进行额外的筛选实验。有那么几次,在筛选阶段就解决了问题。

In the characterization phase, we try to better understand the system by estimating interactions and linear (main) effects. Here, full-factorial and fractional-factorial designs are used.
在鉴定阶段,我们试图通过估计其相互作用和线性相关(主要的)来更好地理解系统。在这里,将使用全因子和分数因子设计。

In the optimization phase, we develop a predictive model for the system to find useful operating conditions through response surface contour plots and perhaps mathematical optimization. Response surface designs are used to collect data in these studies.
在优化阶段,我们开发了一个系统的预测模型,通过响应面的等高线图或者数学优化,去寻找合适的操作条件。响应面设计用来在这些研究中收集数据。

This screening, characterization and optimization (SCO) strategy actually embodies several substrategies that are a subset of the overall SCO strategy, namely:
这种筛选,鉴定和优化(SCO)的战略包括了多个子战略,每个子战略又是SCO战略的一子集,即:


• Screening-characterization-optimization.
筛选 鉴定 优化
• Screening-optimization.
筛选 优化
• Characterization-optimization.
鉴定 优化
• Screening-characterization.
筛选 鉴定
• Screening.
筛选
• Characterization.
鉴定
• Optimization.
优化


The end result of each of these sequences is a completed project. There is no guarantee of success in a given instance, only that SCO strategy will increase your chances of succeeding.
每个序列的最终结果是一个项目的完成。SCO战略并不是成功的保证,它只会增加成功的机会。


The strategy used depends on the experimental environment. These characteristics involve program objectives, the nature of the factors (Xs) and responses (Ys), resources available, quality of the information to be developed and the theory available to guide the experiment design and analysis. A careful diagnosis of the experimental environment along these lines can have a major effect on the success of the experimental program.7
采用的策略取决于实验环境。这些特性,涉及到计划目标,因素的本质
(XS)和反应(YS),可用资源,信息质量,指导实验设计和分析的理论。从这些角度出发,对实验环境的仔细分析,对实验program.7的成功有重大影响


Statistical engineering contributes by taking proven DoE techniques, which are often researched and taught in isolation from one another, and integrating them into an overall experimentation strategy. This strategy allows practitioners to achieve greater results than they could achieve using the same DoE techniques in isolation.
在这个案例中,统计工程通过DOE技术达成目标。DOE往往是研究和讲授单独的技术,并集成一个整体实验策略。这一策略使从业人员在取得比简单相加的使用DOE技术更好的成果。

Improving sales and operations
改善销售和运营

James L. Hess, vice president of operations services at Leggett and Platt, described another use of statistical engineering that helped the the company improve its sales and operational planning process, which of course is a critical business process.8
Leggett and Platt运营服务副总裁James L. Hess描述了另一个统计工程的应用实例:帮助公司改进销售和运营规划过程。这当然是一个重要的业务过程。

This example involved embedding statistical modeling and forecasting methods within the demand planning part of the process. Using data and applying proven statistical methods are integral to the business process, as is the commercial software used to support the workflows.
这个例子涉及在过程需求规划中使用统计建模和预测方法的。使用数据和应用成熟的统计方法是业务流程的必要组成部分,就像用商业软件来支持工作流程。

The statistical tools used included Bayesian time series techniques for modeling data. These techniques were tailored to the application.
所使用的统计工具包括用贝叶斯时间序列技术对模型数据进行处理,以及其他适用的技术

For example, if adequate data were available, seasonality was incorporated into the models. Rather than relying solely on statistical methods, the models were constructed and used to make forecasts that can be revised based on outside information, integrating statistical and knowledge-based approaches.
比如,数据足够充分,季节性因素也可以纳入模型。依靠统计方法,模型被构造并用来根据外界的信息结合统计和知识为基础的方法做出预测,这些预测是可以修改的 。

The main benefits came from reduced inventories for the same customer service level and production efficiency. This freed cash and reduced expenses associated with carrying inventory. One of the most significant benefits was the reduced opportunity for slow-moving and obsolete inventory.
主要优点是在同一的服务水平和生产效率下减少库存。释放库存带来流动资金和减少开支。其中一个最显着的好处是减少滞销及存货过期的机会。

A smaller part of the business case is improved labor efficiency. While the financial impact of this approach is company confidential, Hess reported that this business process approach contributed significantly to the company’s bottom line.
本案例的一部分是提高劳动效率。虽然这种方法的财务影响是公司的机密,Hess在不触及公司底线的情况下,报告了此业务流程改进的方法。

In this case, the contribution of statistical engineering was embedding the methods to ensure institutionalization, integration of statistical and knowledge-based approaches, and tailoring the Bayesian time series approach so it could differentiate between cases with enough data for seasonality estimation and cases that didn’t have enough data.
在这种案例中下,统计工程的作用是嵌入,制度化的方法,整合了统计和知识为基础的的方法,合适的贝叶斯时间序列的方法,所以它可以区分季节性估计是否有足够的数据支持

Underlying theory
理论构成

The reasons for the effectiveness of statistical engineering can be seen when you consider the theory underlying its use. We believe there are at least five aspects of this theory:
从统计工程理念的应用,我们不难发现它高效的原因,至少有5点:

  1. A system or strategy to guide the use of statistical tools is needed to effectively use the tools.
识别统计工具应用并确保其有效性的策略或系统

  1. The impact of statistical thinking and methods can be increased by integrating several statistical tools, enabling practitioners to deal with highly complex issues that cannot be addressed with any one method.
因统计原理和方法的结合 ,使用者能整合多少统计工具,以处理单一工具无法处理的复杂问题

  1. Linking and sequencing the use of statistical tools speeds the learning of the approach, thereby increasing the impact of the method.
统计工具的关联和排序能够促进统计工具的学习,因此能够增加这些方法的影响

  1. Embedding statistical thinking and tools into daily work institutionalizes their application.
将统计原理和方法嵌入日常工作中使其应用标准化

  1. Viewing statistical thinking and methods from an engineering context provides a clear focus on problem solving to the benefit of humankind.
从工程学角度看待统计原理和方法使处理问题时能更加清晰的聚焦于人类的利益

Over time, as statistical engineering is used, this theory will be challenged and revised as more is discovered. As a result, the breadth, depth and effectiveness of statistical thinking and methods in practice will increase—an objective on which the vast majority of statisticians and quality professionals can agree.
统计工程应用到现在,其理论在质疑和修正的过程中不断增加。这也促进了统计原理和方法在实际运用中的广度,深度和效力,这也是大多数统计和质量专家愿意看到的。

Realizing the promise
展望未来

Statistical engineering provides a thought process that enables you to integrate, link and sequence statistical tools in a way that facilitates embedding the tools in processes and systems used to run the business. As a result, the sustainability of the benefits on the problem solution or process improvement is increased.
统计工程提供了一个思维,让你能以将内嵌在商业过程和系统的方式来完成统计工具的集成,联结和接续。从而增加问题处理和过程改进的持续性。

Broad use of statistical engineering will move us closer to realizing the promise of statistical thinking and methods. Leadership by statisticians and quality professionals is required to effectively apply statistical engineering. Assuming leadership will result in impactful roles for those who accept the challenge.
统计工程的广泛应用将使我们离统计原理和方法的初衷更近。统计工程的有效应用需要质量和统计专家的领导。接受这项挑战将会使他们更有影响力。
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