## Meeting Customer Expectations with Kano Analysis

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What do your customers really want? You are taking a risk by blindly fulfilling your customers’ needs without understanding how they classify them. Kano analysis will allow you to properly classify those customer needs and lower your risk.

## How House of Quality Shapes Product Excellence

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House of Quality? No, this is often referred to as a House of Pain because of the effort needed to complete one. Let’s see if we are just being overly pessimistic.

## Identify, Design, Optimize, Validate: A Proven Approach to Designing High-Quality Products

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Incremental and continuous improvements are great. When appropriate, breakthrough improvement is even better. IDOV (identify, design, optimize, validate) is one tool for accomplishing this. Let’s see how.

## A Comprehensive Guide to Input-Process-Output Models

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Creating and mapping business process models can sound like a daunting task with little tangible value. With input-process-output models, we debunk these myths and introduce a versatile, straightforward methodology that can be used to transform your business.

## Kappa

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Kappa is the common measurement for judging how your measurement system works for attribute data. It is also described as the primary output from an Attribute Agreement Analysis.

## How to Optimize the Value of Hypothesis Testing

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Hypothesis testing is a branch of statistics in which, using data from a sample, an inference is made about a population parameter or a population probability distribution.

## Streamlining Production with Just-In-Time Manufacturing

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Have you ever had to shut down your manufacturing line because major components haven’t arrived from your supplier? Have you ever had to rent extra warehouses for your finished goods? Just-in-time (JIT) manufacturing would prevent that from happening. Let’s see how that works.

## Interquartile Range

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In a box plot, it is easy to see the range of where 50% of your data lies. Let’s examine this a little further by describing the interquartile range. Quartiles can be defined as dividing your data into 4 parts or quarters of approximately equal size. You can define the 4 parts in terms of […]

## Maximizing the Benefits of In-Control: Tips for Process Improvement

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In-control is not referring to the behavior of your children. It’s about whether your process is exhibiting common or special cause variation. Let’s explore how this works.

## The Concept of Kaizen: The Key to Continuous Improvement

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If your organization is too impatient to use a formal DMAIC approach to continuous improvement then Kaizen may be the tool for you.

## KJ

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Now that you have brainstormed and gathered a list of random ideas, how do you make sense of them? KJ is a tool for helping you establish the themes and relationships between your ideas.

## Hoshin Kanri

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Does your organization just focus on today’s operational and tactical issues, or is there a process for developing a strategic plan for the future? Hoshin Kanri is a method for ensuring an organization’s strategic goals drive progress and action at every level within that organization.

## Track Organizational Progress with the Help of Key Performance Indicators

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How does your organization track and monitor organizational performance? Do you have key metrics that you frequently look at to make decisions? Using Key Performance Indicators (KPIs) is a common method for tracking your most important metrics. Let’s see how. A Key Performance Indicator (KPI) is a measurable value that demonstrates how effectively a company […]

## What Every SS Practitioner Should Know About Factors

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The word factor, in the context of Design of Experiments (DOE), has several other names. Let’s learn more about what a factor is and how it is used in DOE. One of the most common formulas in statistics is Y = f(X) which states that Y is a function of X. If you define Y […]

## The Evolution and Impact of Jidoka

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STOP THE PRESSES! Jidoka will immediately stop equipment upon discovering an abnormality in the process. Let’s explore this a little deeper.

## Mastering Gage R&R: Key Steps for a Successful Study

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You want to make good data-driven decisions, but can you trust your data? Is the measurement system you used to gather the data giving you precise and consistent measurements? A Gage R&R study will answer your questions.

## The Impact of Key Business Issues: Understanding and Addressing Critical Challenges

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Are all your organization’s problems and issues of equal importance? Probably not. How should you handle those that are the most critical and important? Let’s find out. A Key Business Issue (KBI) refers to a critical problem or challenge that your organization faces, which can significantly impact your performance, growth, or competitiveness. KBIs are specific […]

## Kirkpatrick Model of Evaluation

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Is your Lean Six Sigma training accomplishing what you want it to do? How do you know? Those questions can be answered by using the Kirkpatrick Model of Evaluation. Let’s see how.

## The Competitive Advantage of Being a Certified Green Belt

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Will having a Lean Six Sigma Green Belt help you break boards? No. But a trained and experienced Green Belt will help improve what your organization does so you can defeat waste, process defects, and much more. Let’s see how.

## Exploring the Benefits of Fractional Factorial DOE

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Fractional factorial DOE is a cost- and time-effective designed experimentation statistical tool for understanding the impact of your process inputs on your process outputs.

## Engineering Change Request (ECR)

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While you hope everything goes smoothly and as planned, sometimes you have to make a change in your existing product or product design. The engineering change request is the form you use to initiate the changes.

## Empirical Rule

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The empirical rule is a simple way to understand the distribution of your data values if they come from a normal distribution.

## F-value (ANOVA)

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Whether you are talking about the F-value, F-test, F-statistic or F distribution they all revolve around the same concept of using variances to make statistical decisions about your data.