Data is the lifeblood of Lean Six Sigma. But that data must be measured reliably. Be sure to choose the right method to validate your data.
Measurement system analysis (MSA) determines whether the measurement system is adequate and confirms that significant error is not introduced to the true value of a process characteristic. MSA is the one of the most misunderstood and underused concepts in Six Sigma. This article highlights two of the common mistakes made during the study and explains…
The precision of a measurement system is commonly assessed using a gage repeatability and reproducibility (GR&R) study. Part 1 of this article discussed metrics used in measurement system analysis. Here, Part 2 compares commonly used GR&R metrics with probabilities of misclassification. Comparison of GR&R Metrics with Probability of Misclassification Using Numeric Simulation A simulation study…
The precision of a measurement system is commonly assessed using a gage repeatability and reproducibility (GR&R) study. In Part 1, this article describes available GR&R metrics. Part 2 covers their applicability to two broad cases of comparative study. Measurement system analysis has been a major part of process characterizations and improvements, with key guidance…
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…
Manufacturing processes vary over time. Occasional large, special-cause events that are sprinkled against a background of lesser variation are natural to the process. Most processes, as a result, use a control strategy, at the heart of which is a measurement system designed to manage the product properties that are critical to customers. To maintain accuracy,…
A number of improvement projects are hampered because of lack of quality data. Engineers tend to overlook the importance of validating the measurement system, and even more importantly often times don’t select the right measurement instrument. During one such project, a company team was measuring the tube width with a vernier caliper. The specification width…
Measurement system analysis (MSA) can be fun, always impresses the customer, and can often result in an important surprise or two. Learn why gage R&R is only one part of the equation for achieving near risk free measurements of all types. Characterizing measurement error is one of the most important yet overlooked and misunderstood aspects of…
Quality improvement methodologies and the analyses that are performed within your organization are only as good as the data on which they are based. That is why it is essential to make sure that your measurement system – your gages, personnel, methods and procedures – is stable and capable of measuring your data before continuing with…
Measurement error is unavoidable. There will always be some measurement variation that is due to the measurement system itself. Most problematic measurement system issues come from measuring attribute data in terms that rely on human judgment such as good/bad, pass/fail, etc. This is because it is very difficult for all testers to apply the same…
A defect database that tracks errors in processes (or even products) – a database that is so sophisticated that it actually tracks where the defect occurred in addition to the type of defect – can provide powerful information. It can be quite helpful in scoping and prioritizing potential improvement opportunities. But is the data trustworthy?…
“You don’t know what you don’t know.” That phrase has been taught in Black Belt training for many years, and it continues to be relevant today. When combined with a related phrase, “What you don’t know can hurt you,” these words illustrate a common challenge: Sometimes, the events that hurt us are unknown and unexpected….
The gage R&R study is the standard tool in the Six Sigma process improvement methodology to evaluate the adequacy of a measurement system with regard to measurement variability. While it is well established and widely used in the discrete manufacturing industry, it is less useful in process industries where the nature of measurements is different,…
A common service level agreement (SLA) measurement among Information Technology Infrastructure Library (ITIL) practitioners is project completion time, in one form or another. Many use a percent difference measurement between actual and forecasted, others simply subtract the actual completion time from the forecasted completion time. Whatever the final calculation, using the elapsed time between when…
Effort accounting is needed in software and IT for the simple reason that labor is generally the most important controllable element of cost. Labor cost (effort hours times prevailing labor rate) is an essential and fundamental element of efficiency measurement. Six Sigma projects in software and IT (especially DMAICs) are often focused on driving down…
There is usually a strong belief that a validated analytical method, either partly automated or fully manual is simply perfect and cannot generate any defect since it complies with highly demanding regulations. Thus, any apparent variation in a production process is automatically attributed to the manufacturing process or raw material suppliers. The latter being also…
Can we trust the data? This is the fundamental question behind measurement system analysis (MSA). The question can come up in any data-based project. Shortcomings in a measurement system’s accuracy (bias, linearity, stability or correlation) and precision (resolution, repeatability or reproducibility) can obstruct analysis purposes. One often-overlooked aspect of resolution is data granularity, or the…
Successful corporate initiatives such as Lean Six Sigma require proper planning, prioritization, resource allocation, budgeting, training, and proper review and reward mechanics. These initiatives also must consider the stability, accuracy and maturity of the core processes, measurement systems and the people they will affect. In most organizations there is a wide range of both experience…
At a high level, there is usually agreement on the big issues in any healthcare organization. Through observation and feedback alone, key stakeholders may realize there are problems with excessive wait time in the emergency department, or that the first surgical case of the day rarely starts on time, or that it is taking too…
As the industrial world continues to become more competitive, measurement tolerances will become tighter. At the same time, customers insist that products be produced at a lower cost. In this environment, the production floor of Six Sigma companies must continually improve the certainty of measurements without increasing costs. Most companies are at the early stages…
In Six Sigma work, practitioners normally are expected to conduct a gage R&R study to verify that that the measurement systems being used are providing measurements free from variations due to repeatability and reproducibility problems. This is usually done in the Measure phase of DMAIC (Define, Measure, Analyze, Improve, Control) prior to data analysis so…
An essential component of any Six Sigma project is the gage R&R step conducted during the Measure phase. Traditional training will cover the full analysis of variance (ANOVA) of a set of continuous data, an attribute gage R&R for discrete data and the destructive gage R&R. Since it is sometimes difficult to apply these tools…
More than ever, companies today realize the importance of measurement – everything from measuring performance to measuring gap closure – in order to achieve goals. Measurement is the process of estimating the ratio of the magnitude of a quantity to a unit of the same type. A measurement is the result of such a process, normally expressed…
One of the biggest challenges in making improvements in transactional processes is getting data which can be relied upon. There is an abundance of categorical data in transactional areas – situations where a judgment call is required: Is something right or wrong? Is the application complete? What type of error was made on the request…
This combination “case study and tutorial” tracks the inception of a Six Sigma DMAIC project by an IT support business. The project is aimed at helping the company become more competitive and profitable. Each part follows the project team as it works through another stage of the DMAIC methodology. Click to read the rest of…
Alexander Silantyev
Rohin Raina
Nick Finstrom
Eric Maass
Brad Craver
Richard Miller
Hemanth Subramanya
Kim Niles
iSixSigma-Editorial
Chew Jian Chieh
Robert Tripp
SiewMun Ha
Scott D. Adams
Gary A. Gack
Jean-François Guilland
Michael Ohler
Bruce J. Hayes
Carolyn Pexton
Richard Clark
Alastair Muir
J. DeLayne Stroud
Michael Mueller
David L. Hallowell