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Can AI Be Used to Replace Six Sigma Statistical Software?

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Key Concepts Six Sigma is a well-established, data-driven methodology designed to improve processes by identifying and eliminating defects in manufacturing and business processes. One of the key components of Six Sigma is statistical analysis, which helps organizations identify problems and implement solutions. To perform this analysis, Six Sigma practitioners traditionally rely on specialized statistical software, […]

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Achieving Process Stability with Common Cause Variation: Strategies for Success

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This article will introduce you to common cause variation, one of the foundational concepts in quality improvement. Weโ€™ll explore guidance for the successful use of common cause variation in process improvement.

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How to Use Entitlement to Drive Process Improvement

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Entitlement is defined as the best performance you can reasonably achieve with the existing process.

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Mean in Lean Six Sigma: How to Interpret Your Data

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Central tendency and mean are two of the more significant statistics that are used in Lean Six Sigma. These two concepts have a large place in the developed world of LSS and are important when it comes to implementing new technologies or measuring processes for improvement.

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Low-Hanging Fruit: Easily Transform Your Organization

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A competitive and successful business needs to critically evaluate all the opportunities for improvement and deploy valuable resources strategically. By identifying low-hanging fruit, high-impact, low-effort activities can be addressed creating a solid foundation for continuous improvement.

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Insights from COPIS for Improved Efficiency

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What does your process look like from 30,000 feet? Your extended process view can be described using COPIS, or customer, output, process, input, and supplier. Letโ€™s get in our balloon and go up.ย 

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Subjective Rating vs. Ranking: Which Is the Better Data Collection Method?

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Subjective ratings and rankings can be used in a variety of applications, such as assessing job performance, gauging customer satisfaction, and monitoring the morale of your workforce.ย Find out more about this Six Sigma term.

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The FabChip Caster Challenge: A Lean Six Sigma Journey To $3,000,000

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Background FabChip (fictitious name) was a leader in the global semiconductor industry, known for its cutting-edge wafer-fabrication equipment. With the semiconductor sector at the core of everything from smartphones to medical devices, FabChipโ€™s role in supplying this vital technology was crucial. The equipment FabChip manufactured, however, was often large and complex. When it arrived at […]

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Best Practices for Managing Rework in Your Business

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Increasing complexity of products and services in combination with the pressure of reduced time to market can increase the probability of non-conformance and the need to perform rework to meet functional requirements. Weโ€™ll explain why avoiding rework activities is an all-round winner with some top tips for you to implement it in your business.

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TEAM: Meeting Your Project Goals

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When you are part of an organization that is working towards goals, you are part of a team. A team moving toward hitting milestones can sometimes need to generate excitement and motivation while inching toward the goal line. This is why we have acronyms like TEAM. An acronym like TEAM can be used […]

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Assessing Process Stability: Techniques and Tools

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Have you ever wondered why your doctor may keep you waiting in the waiting room or why you have to fast before doing a blood test? Letโ€™s see if Lean Six Sigma can give you an answer.

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Process Stability: Minimizing Variation While Increasing Efficiency

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In Six Sigma, process stability is extremely important to efficiency and productivity. With a stable process, you have predictability, and quotas can be met.

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Understanding Process Variation: Increasing Production Quality

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It is well established that there exist eight dimensions of quality: Each dimension can be explicitly defined and is self-exclusive from the other dimensions of quality. A customer may rate your service or product high in conformance, but low in reliability. Or they may view two dimensions to work in conjunction with each […]

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Bimodal Distributions and Why They Matter

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One of the important statistical descriptors of your data is its central tendency. Central tendency can be described using the mean, median and mode of the data. The mean is described as the mathematical center of your data. The median is the physical center of your data, and the mode is the most frequently occurring value in your data.

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PDCA vs. OODA: What’s the Difference?

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What Is PDCA? The Plan-Do-Check-Act (PDCA) method is a framework used to achieve continuous improvement in a particular organization or process. Itโ€™s also known by several other names, including the Deming wheel, the Shewhart cycle, and the control circle. Even though the method was originally rooted in quality control, it has since been […]

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Tips for Recognizing and Transforming Non-Normal Data

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Six Sigma professionals should be familiar with normally distributed processes: the characteristic bell-shaped curve that is symmetrical about the mean, with tails approaching plus and minus infinity (Figure 1). When data fits a normal distribution, practitioners can make statements about the population using common analytical techniques, including control charts and capability indices (such […]

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ARMI (Approver, Resource, Member, Interested Party): Mastering Lean Six Sigma

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ARMI stands for Approver, Resource, Member, and Interested Party (IP). Find out more about these Lean Six Sigma expertise classifications.

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15 Criteria for Selecting a Viable DMAIC Project

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As anyone involved in Six Sigma knows, selecting the right project is a critical component of project success. If practitioners do not put enough effort into selecting the right opportunity for improvement, a project can end in disaster, or create unnecessary work and complexity for the project team. Selecting projects with just a […]

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Understanding the Uses for Mood’s Median Test

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When comparing the average of two or more groups with the help of hypothesis tests, the assumption is that the data is a sample from a normally distributed population. That is why hypothesis tests such as the t-test, paired t-test, and analysis of variance (ANOVA) are also called parametric tests. Nonparametric tests do […]

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The Benefits of Using Flowcharts in Six Sigma Projects

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A flowchart is a diagram of a process, using standard symbols to represent a variety of process activities over a specified timeline.

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Continuous vs. Attribute Data: Whatโ€™s the Difference?

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What is Continuous? Continuous data refers to numerical data with any value within a certain range. The values have infinite possibilities, but they all fall within a range. These can be whole numbers or decimals measured using data analysis like skews and line graphs. This kind of data can change over time and […]

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A Practical Approach to the Successful Practice of 5S

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While some Lean Six Sigma (LSS) practitioners consider 5S a tool, it is more than that. 5S, abbreviated from the Japanese words seiri, seito, seiso, seiketsu, shitsuke, is not just a methodology, it is a culture that has to be built into any organization that aims for spontaneous and continuous improvement of working […]

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Steps in Constructing an X-Bar and R-Control Chart

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Steps in Constructing an X-Bar and R Control Chart: This document contains the step-by-step instructions to construct an X-bar and R control chart. First the R chart is constructed. If the R chart validates that the process variation is in statistical control, the XBAR chart is constructed.

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Process Entitlement: Unlocking Top Process Performance

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Understanding process entitlement is essential to Lean Six Sigma practitioners and organization leaders because process entitlement quantifies the best case or optimum process performance without changes to the process.

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Thought Process Map for Six Sigma: What, Why and How

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A thought process map, sometimes referred to as a TMAP or TPM, not only helps you begin an improvement project with a comprehensive view, but ensures you stay on track all the way through completion. Learn how to use this powerful visual tool.

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Multi-Vari Chart: Visualizing Variation in Your Processes

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As the Chinese proverb says, โ€œa picture is worth a thousand words.โ€ The multi-vari chart is such a picture. In a single graph, you will be able to understand the variation of your process. Letโ€™s learn more.ย 

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Gemba: The Key to Engaging Employees and Improving Performance

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Does Going to Gemba sound like a nice trip to an exotic locale? While not a fancy foreign destination, Gemba is going to where the work is done to learn more about the process. Letโ€™s take a deeper look into what Gemba is about.ย 

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The Harada Method: Reduce the Eighth Waste โ€“ Part 1 of 2

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The Harada method helps individuals achieve self-reliance, which in turn facilitates a company’s process improvement journey. This week’s article provides an overview of the method and its genesis. Partย Two of this article presents five templates to use to plan a goal, measure the goal’s progress, and assess success. No matter its size, an organization is driven by […]

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Comparing and Contrasting AI, CI and Big Data

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AI (Artificial Intelligence) involves creating systems and algorithms capable of mimicking human intelligence to perform tasks like decision-making, problem-solving, and pattern recognition. It leverages techniques such as machine learning and neural networks to improve through experience. Continuous improvement focuses on systematically enhancing processes, products, or services through incremental changes, using methods like Lean […]

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Real Life Examples of Quality Management That Worked

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Quality management is the process of ensuring that products and services meet consistent standards of excellence. It encompasses various strategies, tools, and techniques that aim to enhance organizational performance, improve customer satisfaction, and reduce waste. Many businesses around the world have effectively utilized quality management principles to drive significant improvements. Over the years there have […]

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Effective Project Management with SMART Goals

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You need to be SMART when writing the goals for your project charter: specific, measurable, achievable, relevant, and time-bound. Here’s how the SMART framework can help you write better goal statements.

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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.ย 

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Suppliers, Inputs, Process, Output, Customers (SIPOC): Powerful Visualization

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What does your process look like from 25,000 feet up in the air? Your extended process view can be described using SIPOC, or supplier, input, process, output, and customer. Letโ€™s get in our plane and go up.ย 

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Three Steps for Aligning Projects to Business Priorities

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A company with a Six Sigma deployment identifies a process improvement area within the business. It is easy to figure out what comes nextย โ€“ just define the problem, set the goal, select the project team, pick the team leader, and get out of the way, right? Well, sort of…but before deployment leaders get […]

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Center Points: Finding the Mathematical Center of Your Data

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The use of center points in your designed experiments can be valuable in determining the actual relationship between your input factors and your response variable. Letโ€™s explain this in a little more detail.ย 

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Understanding the Purpose and Use of Benchmarking:

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Benchmarking is a way of discovering what is the best performance being achievedย โ€“ whether in a particular company, by a competitor, or by an entirely different industry. This information can then be used to identify gaps in an organization’s processes to achieve a competitive advantage. Thus it is important for Six Sigma practitioners […]

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What is the Bartlett Test and How is it Used in Statistical Analysis

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The Bartlett Test is named after the English statistician, Maurice Stevenson Bartlett. The test is also known as the Bartlettโ€™s test for homogeneity of variances. It is most used in doing a 1-way Analysis of Variance (ANOVA). ANOVA is used to determine whether there is any statistical difference between the means of three […]

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Understanding Customer Needs: The Importance of Quality Targets

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Understanding what quality targets are and how to center product uniformity around them is a helpful step in overall process improvement, ultimately leading to increased profits and customer satisfaction rates.

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Containment Best Practices: Ensuring Product Integrity

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If you have a non-conforming or defective product coming off your production line, what do you do with it? Utilizing a strategy of containment might be the way to go. Letโ€™s learn more about this. Containment of non-conforming products refers to the actions you take to prevent the distribution or use of products […]

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Tolerance Range: Expecting Variation in Your Data

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Understanding and determining the upper and lower statistical limits are the key to determining tolerance range (TR). Find out more about this LSS concept.

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Corrective Action: Eliminating Nonconformity Permanently

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Corrective action is the process, known as a corrective action plan (CAP), of taking the appropriate steps to identify the root cause of a problem and implementing a solution that corrects the root cause to prevent its recurrence. The aim is to improve the processes in place within an organization so that problems […]

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Radar Charts: The Visual Tool for Multi-Dimensional Data Comparison

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A radar chart, also known as a spider chart, is a great tool to graphically compare multiple outcomes for specific characteristics and criteria.ย 

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Cause-and-Effect Diagrams: A Visual Tool for Root Cause Analysis

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Getting to grips with the many different causes of defects and quality issues is key to ensuring business success and avoiding customer dissatisfaction. The cause and effect diagram is a clear, visual representation of all possible causes and keeps the team focused upon quality improvement.

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Monitoring Process Performance with X-Bar and R Charts

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Is the variation in your process data to be expected, or has something special occurred? A control chart will give you the answer. The X-bar and R chart will give you the details.

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The Importance of Fisher’s (1-way ANOVA) in Statistical Analysis

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Fisher’s 1-way ANOVA is a classic analysis of variance utilized in statistics to determine if there are statistical differences between the means of two or more unrelated groups.

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Subject Matter Expert vs. Consultant: Whatโ€™s the Difference?

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What is a Subject Matter Expert? Subject matter experts (SMEs) are people who have a significant amount of knowledge or experience regarding a specific subject. They can specialize in any kind of academic discipline, profession, or practice. Even though their area of expertise is relatively narrow compared to general consultants, there is still […]

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Homogeneity of Variance and Statistical Inference: What You Need to Know

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There are several statistical tests which assume that independent data sets have equal, similar or equivalent variances. Violating this assumption could render any statistical conclusions invalid.ย 

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How Six Sigma Improves Customer Satisfaction

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With Six Sigma, customer satisfaction comes first. We’ve talked at length in the past about the various nomenclature, techniques, and so forth that drive Six Sigma. As a comprehensive discipline, it is a transformative means of making your organization the best it can be. However, it is a methodology and approach that takes […]

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Hard and Soft Savings: What Counts Can Be Counted

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Six Sigma is all about what can be quantified and measured. So it is not surprising that organizations that utilize Six Sigma often prefer to measure success in terms of hard savings or dollars to the bottom line now. They are subsequently less impressed with soft savings, or the possibility of dollars to […]

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Key Tools for Defect Reduction in Lean Six Sigma Processes

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Lean Six Sigma is a system that measures how well a process operates, with โ€œsix sigmaโ€ being the level of perfection in which processes operate at or below 3.4 defects per million units produced. In order to achieve this, companies must eliminate all but the most critical process steps and then re-engineer those remaining steps to be more efficient and effective.

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