iSixSigma

Resource Page: A Primer on Non-normal Data

The distribution of data can be categorized in two ways: normal and non-normal. If data is normally distributed, it can be expected to follow a certain pattern in which the data tend to be around a central value with no bias left or right (Figure 1). Non-normal data, on the other hand, does not tend…

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Measurement System Redesign and Innovative Data Management

A multinational paper company wanted to reduce its cost of poor quality. The company recognized an opportunity to use Six Sigma concepts to minimize variability in its processes. Senior management was excited about the idea of applying design of experiments (DOE) to uncover the mathematical relationships among the input and output variables. For them, the…

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Real-time Feedback Changes the Game

Efficiency is in everyone’s interest. However, achieving it is heavily dependent on the quality and timeliness of crucial performance data. Live, real-time information is crucial for any manufacturing business. Waste benefits nobody, whether it is a waste of materials, time or energy. … One of the things that I have learned in manufacturing is that the…

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Help with a Future iSixSigma Article on Gage R&R

Hello iSixSigma readers! We are working on an article about gage R&R and need your help with data collection for analysis. What we need: Raw data itself (either 5-part or 10-part analyses including operators, parts, trials and measurements) The tolerance spread Is this one- or two-sided tolerance What we would like: Gage family information (e.g.,…

The Path of Least Resistance: Is There a Better Route?

Driven by nationwide technologist shortages, an industry-wide focus on quality and rising consumer demand, healthcare is feeling the pressure to deliver more with less. Given this challenging environment, some organizations have come to the conclusion that taking the path of least resistance may not be the best approach. For many, delivering quality patient care is…

Rounding and Round-off Rules

When performing statistical data analyses, quality professionals are always challenged to maintain data integrity. When should you round up the answer; when should you round down? How many significant figures are appropriate for the data set that has been taken? Below are a set of simple rules that should help you traverse the perils of…

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Actionable Information from Soft Data

Engineers, Six Sigma practitioners and other researchers often work with “hard” data – discrete data that can be counted and legitimately expressed as ratios. But what of “soft” data, things like opinions, attitudes and satisfaction? Can statistical process controls (SPC) be applied here? Can process variation in customer satisfaction, for example, be measured and then reported to…

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How To Turn Process Data Into Information

A repeated series of actions and variables is a process. A collection of processes is a system. Virtually perfect Six Sigma quality results from an optimal interaction of all the variables in a given system. Process and system questions we all face at work include: Which variables are the most important to the customer? Am…

Activities vs. Performance: Improvement, Common Sense

Most organizations have a strong bias toward planning, managing and executing a multitude of supposedly value-added activities hoping that these (often isolated) activities will yield significant results. In rare cases, activities are spawned by careful strategic planning, tracked regularly by performance data, reviewed for adjustments and improvements and integrated across functions, divisions and geographies. However,…

Six Sigma in Data Warehousing Domain – IT Case Study

Most quality professionals recognize that Six Sigma is a breakthrough strategy. They understand that the methodology uses data to measure current process effectiveness and to validate improvement; uses proven statistical and quality tools to identify process gaps and improvement solutions; and uses change management processes for institutionalizing and integrating improvements in an organizations’ operational and…

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Renew the Commitment to Data-Based Decision Making

A large corporation recently conducted a competition to identify the organization’s best Six Sigma projects of the previous year. Out of more than a hundred submissions, only one actually validated its improvements with a comparative experiment (z, t, Chi-sq, etc.). What did the rest do? The same thing they did before Six Sigma. The mean…

Attribute Data: Making the Most of What’’s Available

Six Sigma practitioners are aware of the range of numeric data types, from attribute data counts and tallies to continuous data measures on a scale. As the information strength in an element of data depends on the number of potential values it might take on, attribute yes/no data has to be considered the weakest. Many…

Six Sigma Tools Still Fit in Projects Lacking Data

In organizations struggling through the early phases of Six Sigma implementation, practitioners often find themselves doing projects with little or no data. Sometimes they can begin collecting the needed data, which causes delays in the project. In other situations, where past information is critical to understanding the evolution of the project, but the data is…

Analytical Treatment of Discrete Ordered Category Data

Ordered category data is discrete data representing appraiser or client perception against a rating scale such as a survey or questionnaire. Black Belts learning to apply the Six Sigma methodology to ordered category data are traditionally taught analytical methods that include normal and Poisson distributions. This is probably due to Six Sigma’s beginnings in manufacturing….

Benefits of Connecting RFID and Lean and Six Sigma

A growing number of organizations are studying the commercial use of radio frequency identification (RFID). Several large companies have invested large sums in RFID development, and companies such as Wal-Mart plan to require RFID compliance from their suppliers. Nonetheless, many companies do not yet have a full grasp of what this technology may mean to…

Creating a Fresh View of Six Sigma Data and Tools

Six Sigma DMAIC and DFSS roadmaps provide the guidance needed for using facts and data to understand problems, opportunities and solutions to get results in a wide variety of project settings. For the routine cases, they give practitioners what they need. There are some situations, though, that can benefit from a broader view of Six…

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Data Management Plans Can Reduce Project Cycle Times

Companion Article This is one of two articles by David Wetzel that explore the value of developing a data management plan as the intial step in the Measure phase of the Six Sigma DMAIC methodology. The other article is “Data Management Plans Can Improve Collection/Validation.” Long project cycle times, frequently cited as an impediment to…

Measure the Immeasurable: The World of Smell and Taste

In many industries, improvement projects quickly face an obstacle: The lack of easy to get and reliable data. This is especially true when the critical-to-quality elements (CTQs) of the project are “soft attributes” such as taste, smell or texture. Facing such a problem in the food and drink industries is obvious. While in a Kano…

Start Software Testing With All Five Essentials in Place

Five essential elements are required for successful software testing. If any one of the five is missing or inadequate, the test effort will most likely fall far short of what could otherwise be achieved. Exploring these five essentials can help improve the effectiveness and efficiency of any software testing program. Here are the five essential…

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Software and Systems: The Disciplines of CRM

  The total customer relationship management (CRM) market will reach $12.1 billion by 2004, representing an annual growth rate of 29.9 percent, according to the 2000 CRM Market Forecast and Analysis prepared by IDC, the world’s leading provider of information technology data and analysis. It is highly unlikely, however, that the CRM market will reach…

Automating Input Data to Improve On-Time DeliveriesAn iSixSigma Case Study

Liquid Controls, a manufacturer of high-quality flow meters and accessories for accurate liquid measurement, is a well-practiced user of Six Sigma methodologies. Having adopted Six Sigma in 1999 and made significant strides in improving manufacturing processes, the company more recently began to turn attention to transactional processes for serving customers. Liquid Controls identified several processes…