Lean Six Sigma Concepts

🔍 5 Whys

The 5 Whys technique is a simple yet powerful tool used to uncover the fundamental cause of a problem. By persistently asking “why”—typically five times or more—each response builds on the last, eventually leading to the root cause behind a recurring issue.

🧹 5S

5S is a structured workplace organization system developed in Japan, designed to enhance efficiency and reduce waste. It stands for:

• Seiri (Sort): Remove unnecessary items.
• Seiton (Set in order): Arrange tools and materials for easy access.
• Seiso (Shine): Keep the area clean and tidy.
• Seiketsu (Standardize): Establish consistency through routines.
• Shitsuke (Sustain): Maintain and continuously improve the practice.

🛠️ 6 M’s

The 6 M’s represent six fundamental sources of variation that can affect the outcome of a process. These are:

• Man (or People) – Human error or inconsistency
• Machine – Equipment-related issues
• Material – Quality or availability of inputs
• Method – Procedure or process design flaws
• Measurement – Inaccurate data collection
• Mother Nature (Environment) – Environmental influences such as humidity, temperature, etc.
  This concept is also known as 5M1P when “Man” is replaced by the more inclusive “People.”

🎯 6σ (Six Sigma)

6σ symbolizes Six Sigma, a methodology focused on reducing process variation and defects. In statistics, σ (sigma) stands for standard deviation. A process achieving Six Sigma quality operates with such precision that it produces only 3.4 defects per million opportunities—equivalent to 99.99966% perfection.

🧰 7 QC Tools

Also known as the Seven Basic Tools of Quality, these techniques—popularized by Professor Kaoru Ishikawa—are essential for process improvement and problem-solving:

1. Cause and Effect (Fishbone) Diagram
2. Check Sheet
3. Control Chart
4. Histogram
5. Pareto Chart
6. Scatter Diagram
7. Stratification (or Flow Chart)

🧩 8D Problem Solving

The 8 Disciplines (8D) framework provides a step-by-step method for addressing and resolving complex problems in a team setting:

• D1: Form the team
• D2: Define the problem
• D3: Establish interim containment
• D4: Identify root causes
• D5: Confirm corrective actions
• D6: Implement permanent fixes
• D7: Prevent recurrence
• D8: Celebrate team success

🚫 8 Wastes (DOWNTIME)

Lean thinking identifies eight non-value-added activities—collectively remembered by the acronym DOWNTIME:

• Defects
• Overproduction
• Waiting
• Non-utilized Talent
• Transportation
• Inventory
• Motion
• Excess Processing

🎯 Accuracy

Accuracy describes how closely a measured value aligns with the actual, true value. In quality terms, it’s about hitting the bullseye—not just being consistent, but being correct.

✅ Action Plan

An Action Plan outlines the specific steps, responsibilities, resources, and deadlines needed to carry out a task or project. It’s like a tactical roadmap showing who does what by when.

🧠 Affinity Diagram (Chart)

An Affinity Diagram organizes large sets of ideas or data into logical groups based on natural relationships. It’s especially useful during brainstorming sessions or when sorting complex feedback.

⚡ Agile

Agile is both a mindset and a methodology that prioritizes flexibility, cross-functional collaboration, and quick responses to change. While rooted in software development, its principles apply across projects needing iterative progress and customer feedback loops.

🔁 Alternative Path

The Alternative Path method explores other possible ways to achieve the same outcome—especially when traditional methods aren’t delivering the results you want. It’s about keeping options open and innovative.

🔍 Analyze Phase (DMAIC)

The Analyze Phase is the third step in the DMAIC cycle. This is where root causes are discovered using data analysis, process mapping, and hypothesis testing. It’s about understanding why the problem exists.

🚨 Andon

An Andon is a visual signal or alert mechanism used in manufacturing to indicate a problem. Originating from Japanese production systems, it allows workers to stop the process immediately when an issue arises—triggering fast action and preventing defects.

📊 ANOVA (Analysis of Variance)

ANOVA is a statistical test used to compare the means of multiple groups to see if any of them differ significantly. It helps determine if process changes actually impact performance.

📝 Approval

An Approval is a checkpoint in a process where someone must give formal consent before the work can continue. Too many approvals? That’s a bottleneck waiting to happen.

🎯 Attribute Data

Attribute Data is qualitative, often binary, and represents categories or counts. Examples: Pass/Fail, Yes/No, number of errors. It differs from continuous data, which can take on any value.

🤖 Autonomation (Jidoka)

Autonomation (or Jidoka) is smart automation that stops itself when abnormalities occur, allowing human intervention. This principle—pioneered by Sakichi Toyoda—is core to Toyota’s production system and emphasizes quality at every step.

➗ Average (Mean)

Average, or mean, is the result of adding all the values in a dataset and dividing by the number of values. It provides a central value to describe the dataset.

🧪 Bartlett’s Test

Bartlett’s Test checks whether different groups of data have equal variances. This is important for validating assumptions in statistical models—especially before running ANOVA.

🎯 Bias

Bias is the deviation of a measured value from the true value in a specific direction. It can skew results and mislead decision-making unless identified and corrected.

🥋 Black Belt (Six Sigma)

A Black Belt is a trained Six Sigma professional who leads projects full-time. They possess advanced knowledge of statistical tools and DMAIC, and guide teams through improvement efforts.

🧱 Bottleneck

A Bottleneck is a stage in a process where the flow slows down due to capacity limits or high volume, causing delays and inefficiencies downstream.

📈 Box Plot (Whisker Plot)

A Box Plot is a graphical tool that displays the distribution of data based on five summary statistics: minimum, first quartile, median, third quartile, and maximum.

💸 Break-Even Analysis

Break-Even Analysis determines how many units need to be sold or how much revenue must be generated to cover total costs—beyond which profit starts.

📚 Business Case

A Business Case provides the justification for starting a project. It outlines the expected benefits, costs, risks, and alignment with organizational goals.

📊 C-Chart

A C-Chart (Count Chart) is a control chart used to monitor the number of defects per unit in a process where each unit can have multiple defects. Ideal for quality teams tracking error rates over time.

🛠️ CAPA (Corrective and Preventive Action)

CAPA is a structured approach for tackling process issues:

• Corrective actions fix the immediate problem.
• Preventive actions ensure the issue doesn’t happen again.

🐟 Cause-and-Effect Diagram

Also called a Fishbone Diagram or Ishikawa Diagram, this tool visually maps out all potential root causes of a specific issue, categorizing them under common headers like Man, Method, Machine, etc.

🔄 Change Management

Change Management encompasses all methods used to prepare, support, and help individuals, teams, and organizations transition through change—especially during process improvement or transformation projects.

📉 Common Cause Variation

Common Cause Variation refers to the natural, predictable variability that exists in any stable process. It’s not caused by errors or one-time issues—it’s the system’s inherent noise.

📈 Control Chart

A Control Chart helps track process performance over time. It features a center line (average), an upper control limit (UCL), and a lower control limit (LCL). If data points stay within the limits, the process is considered “in control.”

🔢 Continuous Data

Continuous Data includes values that can take on any number within a range—like weight, temperature, or time. It’s different from discrete data, which only includes whole numbers.

🔁 Continuous Improvement

This mindset focuses on ongoing, incremental enhancements to processes, products, or services. It’s a core Lean and Six Sigma principle, often achieved through cycles like DMAIC or PDCA.

🔗 Correlation Coefficient

The Correlation Coefficient measures the strength and direction of the relationship between two variables. Ranges from -1 (perfect negative) to +1 (perfect positive), with 0 meaning no correlation.

💸 Cost of Poor Quality (COPQ)

COPQ includes all the hidden costs incurred due to defects, delays, rework, or lost customers. It’s what happens when quality fails—before, during, or after delivery.

🛡️ Countermeasure

A Countermeasure is any action taken to reduce or eliminate the impact of a known problem—even if temporarily. It’s a quick response that buys time while deeper root cause solutions are explored.

📏 Cp (Process Capability Index)

Cp measures how well a process fits within its specification limits. It’s calculated by comparing the spread of the process (its variability) to the allowable tolerance range.

🌟 CTQ (Critical-to-Quality)

Critical-to-Quality characteristics are the features or attributes most important to the customer. If these fail, customer satisfaction takes a direct hit.

❌ Critical X

A Critical X is a key input or factor in a process that has a significant effect on the output (Y). Identifying these variables helps in pinpointing improvement targets.

🧭 Cross-Functional Map (Swimlane Map)

A Cross-Functional Map visually outlines how a process flows across various departments or stakeholders. Also called a Swimlane Diagram, it’s great for spotting delays and ownership handoffs.

👥 Customer

In Lean Six Sigma, a Customer is any individual or group that receives or uses the output of a process—either internal (like another department) or external (like the end user).

⏱️ Cycle Time

Cycle Time measures how long it takes to complete one full process cycle—from the beginning of a task to its final delivery. It’s a key performance metric in both Lean and Agile.

❌ Defect

A Defect is any instance where a process output fails to meet its required specification—be it a product flaw, a service error, or any deviation from standard.

📍 Defect Opportunity

A Defect Opportunity is any chance for something to go wrong during a process. Identifying these points helps calculate DPMO (Defects Per Million Opportunities).

📝 Define Phase (DMAIC)

The Define Phase sets the stage for a Six Sigma project. It includes clarifying the problem, setting project goals, defining scope, and identifying stakeholders and Voice of the Customer (VOC).

🧪 DFSS (Design for Six Sigma)

Design for Six Sigma applies Six Sigma principles to the creation of new products or services. Instead of fixing problems later, DFSS helps “design in” quality right from the start.

🔢 Discrete Data

Discrete Data represents countable values—like number of defects, number of users, or times an event occurred. It’s made up of whole numbers only.

🚀 DMADV

The DMADV methodology (Define, Measure, Analyze, Design, Verify) is used for creating new processes or products, especially when the existing system isn’t adequate or can’t be improved further.

🔁 DMAIC

DMAIC stands for Define, Measure, Analyze, Improve, and Control. It’s the classic Six Sigma problem-solving cycle used to improve existing processes.

🚫 DOWNTIME (8 Wastes)

The acronym DOWNTIME summarizes the eight primary wastes identified in Lean:

• Defects
• Overproduction
• Waiting
• Non-Utilized Talent
• Transportation
• Inventory
• Motion
• Excess Processing

📉 DPMO (Defects Per Million Opportunities)

DPMO is a key Six Sigma metric that quantifies process performance by measuring how many defects occur per one million opportunities. The lower the DPMO, the more capable and reliable the process.

🔢 DPU (Defects Per Unit)

DPU measures the average number of defects found in a single unit of output. Unlike DPMO, it doesn’t consider the number of possible defect opportunities—just actual observed defects.

🛡️ Error Proofing (Poka-Yoke)

Error Proofing refers to any strategy or device that prevents errors from occurring in a process—or detects them before they cause harm. In Lean, this is known as Poka-Yoke, a concept introduced by Shigeo Shingo.

⚠️ Error-Proofing Methods

According to Shingo, error-proofing can be achieved through four main tactics:

1. Elimination – Remove the source of error completely.
2. Flagging – Use visual indicators to detect problems.
3. Facilitation – Make the correct action easier than the wrong one.
4. Mitigation – Lessen the impact of an error if it occurs.

✅ Effectiveness

Effectiveness is about doing the right things. It measures how well an output meets customer expectations or fulfills its intended purpose.

🔄 Extra Processing

Extra Processing is a type of waste that occurs when a process adds features, steps, or effort that the customer didn’t ask for or doesn’t benefit from. It’s effort without value.

❌ External Failure

External Failure happens when a defect escapes the process and reaches the customer. These failures can damage reputation, increase costs, and often result in returns or complaints.

👥 Facilitator

A Facilitator is a neutral party who leads improvement sessions or projects, helping teams collaborate, problem-solve, and maintain momentum.

🧨 FMEA (Failure Modes and Effects Analysis)

FMEA is a proactive risk management tool that identifies potential failure points in a process, evaluates their severity, likelihood, and detectability, and prioritizes action using a Risk Priority Number (RPN).

⚖️ Force Field Analysis

Force Field Analysis is a decision-making tool that weighs the “driving forces” for change against the “restraining forces” resisting it. It’s used to evaluate change initiatives and build support.

🔒 Four Absolutes of Quality (Crosby)

Outlined by Philip Crosby, these principles form the backbone of quality management:

1. Quality is conformance to requirements
2. Quality is achieved through prevention
3. The performance standard is zero defects
4. The measurement of quality is the cost of nonconformance

🗺️ Future State Map

A Future State Map visualizes what the ideal process should look like after improvements—focusing on value creation, flow efficiency, and waste elimination.

🎯 Gage R&R (Repeatability and Reproducibility)

Gage R&R is a test used during Measurement System Analysis (MSA) to evaluate whether measurement tools and operators provide consistent and accurate results.

🖼️ Gallery Walk

A Gallery Walk is a structured display of completed Lean Six Sigma projects or improvement ideas. It’s used to showcase successes, share learning, and engage others across the organization.

🏭 Gemba

Gemba is a Japanese word meaning “the real place.” In Lean, it refers to the actual site where value is created—whether it’s the shop floor, service desk, or operations room. Gemba Walks are when leaders visit these locations to observe and support improvements directly.

🎯 Goal Statement

A Goal Statement clearly outlines the intended result of a process improvement effort. It’s specific, measurable, and tied to customer or business needs—answering the question: What are we trying to achieve?

🟢 Green Belt

A Green Belt is a Six Sigma practitioner who has completed formal training (usually around two weeks) in the DMAIC methodology. They lead smaller-scale improvement projects and support Black Belts on larger ones—typically while maintaining their regular job role.

🤝 Handoff

A Handoff refers to the point where ownership of a task, product, or information is transferred between individuals or departments. Poorly managed handoffs are common sources of delay and error.

🔍 Help-Hinder Analysis

The Help-Hinder method is a team reflection exercise where members identify their own actions that either support (help) or disrupt (hinder) process efficiency. It helps improve collaboration and accountability.

🏭 Hidden Factory

The Hidden Factory (also called Hidden Plant or Hidden Operations) refers to all the unseen effort spent fixing mistakes, redoing work, or making up for inefficiencies. These are costs that don’t appear in reports—but quietly drain productivity.

📊 Histogram

A Histogram is a bar graph showing the frequency distribution of a dataset. It helps visualize how data is spread—whether it’s skewed, centered, or contains outliers.

📏 Historical Parameters

Historical Parameters are the baseline values used to measure change or progress. They’re the “before” snapshot that’s compared to the “after” once improvements are implemented.

⏱️ Huddle Meetings

Huddles are quick (usually daily) stand-up meetings where team members share key updates, blockers, and priorities. They’re designed to keep everyone aligned and promote fast decision-making.

🧠 Hypothesis Statement

A Hypothesis Statement is a formal assumption about the root cause of a problem. It’s crafted during the Analyze Phase and tested with data to validate whether the suspected cause holds true.

🧪 Hypothesis Testing

Hypothesis Testing is the process of using statistical analysis to validate or disprove a theory about a data set—often involving p-values and confidence intervals to make decisions.

📉 I-MR Chart (Individuals and Moving Range)

The I-MR Chart is used to monitor variation in processes with small sample sizes:

• I Chart tracks individual values.
• MR Chart tracks short-term variability between them.
  It’s ideal for low-volume or high-mix environments.

👥 Implementation Team

The Implementation Team consists of cross-functional members responsible for deploying process improvements. They turn strategy into action—defining tasks, assigning responsibilities, and ensuring follow-through.

🚀 Improve Phase (DMAIC)

The Improve Phase is where solutions are developed and tested based on insights from earlier stages. Ideas become pilots, and pilots evolve into scalable improvements.

🧠 Improvement Kata

Improvement Kata is a structured habit that encourages continuous learning and behavior change. It’s built around scientific thinking and small experiments to move from a current state toward a target condition.

🔁 Input

In process terms, an Input is any resource—like materials, data, or energy—that feeds into a system to produce an output.

🔍 Inspection

Inspections are checks conducted to find defects in products or services. While helpful, Lean aims to make inspections unnecessary by building quality into the process itself.

🏛️ Institutionalization

Institutionalization means embedding improvements into the culture and systems of an organization so that gains are sustained over the long term—through SOPs, training, habits, and leadership support.

🔧 Internal Failure

An Internal Failure occurs when a defect is caught within the organization—before reaching the customer. These still incur costs (rework, scrap), but less damage than external failures.

📦 Inventory

Inventory refers to items (raw materials, WIP, or finished goods) that sit idle in the process. Excess inventory is a major form of waste in Lean, tying up capital and space.

🤖 Jidoka (Autonomation)

Jidoka is a Lean concept meaning “automation with a human touch.” It empowers machines—or operators—to halt the process when abnormalities occur, ensuring defects don’t continue unchecked.

⏲️ Just-In-Time (JIT)

Just-In-Time is a production strategy that delivers exactly what’s needed, exactly when it’s needed, in exactly the right amount. It reduces inventory waste and boosts responsiveness.

🔄 Kaizen

Kaizen is the philosophy of continuous, incremental improvement. Derived from the Japanese words “kai” (change) and “zen” (good), Kaizen is often driven by frontline employees who identify and fix inefficiencies daily.

📋 Kanban Board

A Kanban Board is a visual tool for tracking work items as they move through stages like “To Do,” “In Progress,” and “Done.” It’s a staple in Lean and Agile environments for limiting work-in-progress and improving flow.

😊 Kano Model

The Kano Model helps organizations categorize customer requirements into:

• Basic needs (expected features)
• Performance needs (more = better)
• Delighters (unexpected features that surprise and excite customers)

📦 Lead Time

Lead Time is the total time from when an order is placed to when it is delivered. It includes waiting, processing, transportation, and any delay in between.

⚙️ Lean

Lean is a business philosophy focused on maximizing customer value while minimizing waste. Rooted in the Toyota Production System, it encourages continuous improvement, respect for people, and total system efficiency.

📈 Lean Six Sigma

Lean Six Sigma combines Lean’s waste elimination mindset with Six Sigma’s focus on reducing variation. It uses the structured DMAIC framework to solve complex problems, improve quality, and streamline processes.

📏 Linearity

Linearity measures the consistency of measurement system bias across a range of values. If bias remains steady throughout, the system is said to be linear—an important component in Gage R&R.

🔻 Lower Control Limit (LCL)

The LCL is the lowest value a process can statistically reach without being considered “out of control.” It’s typically three standard deviations below the process mean on a control chart.

🔽 Lower Specification Limit (LSL)

The LSL is the minimum acceptable value for a product or process output, based on customer or engineering specifications. Anything below this is considered non-conforming.

🧠 Master Black Belt (MBB)

A Master Black Belt is the highest level of Six Sigma certification. MBBs train and mentor other belts, lead enterprise-wide initiatives, and act as strategic change agents within organizations.

📏 Measurement System Analysis (MSA)

MSA is a comprehensive evaluation of a measurement process, checking for both accuracy and consistency. It includes tests for repeatability, reproducibility, linearity, bias, and stability.

➗ Median

The Median is the middle value in an ordered data set. Unlike the mean, it’s not skewed by extreme values and is a reliable measure of central tendency in uneven distributions.

💥 Moment of Truth

A Moment of Truth is the point in the customer journey where a person forms an opinion about the service or product. These critical touchpoints can make or break customer satisfaction.

📝 MoSCoW Method

MoSCoW is a prioritization technique for project management:

• Must have – Essential requirements
• Should have – Important but not critical
• Could have – Nice to include if possible
• Won’t have – Agreed to exclude (for now)

🕺 Motion Waste

Motion Waste refers to unnecessary physical movement by people or equipment. This type of waste doesn’t add value and can be reduced through better layout, tools, and task design.

🗑️ Muda

Muda is Japanese for “waste.” In Lean, it describes any activity that consumes resources but doesn’t add value to the customer.

🔢 n (lowercase)

n usually represents the number of data points in a sample during statistical analysis.

🧮 N (uppercase)

N typically represents the total number of items in a population, as opposed to a sample.

👤 Non-Utilized Talent

This waste refers to underusing people’s skills, ideas, or abilities. It’s one of the 8 Lean Wastes and occurs when employees are assigned tasks that don’t leverage their full potential.

🚫 Non-Value Adding Activities

These are steps in a process that do not directly contribute to delivering the final product or service. Examples include rework, waiting, or excessive motion—costing time and money without benefit to the customer.

🔔 Normal Distribution

Also known as the bell curve, Normal Distribution is a symmetric distribution of data where most values cluster around the mean, and fewer appear as you move away in either direction.

✅ Normality Test

A Normality Test checks whether a data set follows a normal distribution. This is critical before using certain statistical methods like t-tests or ANOVA.

📈 nP Chart

An nP Chart is a type of control chart used to monitor the number of defective items in samples of consistent size. It’s great for visualizing pass/fail data trends.

📖 Operational Definition

An Operational Definition clearly defines a variable or term so it can be consistently measured or assessed. It answers: What exactly are we measuring? How will it be measured?

🏁 Output

Output is the end product or result generated by a process. It can be a physical item, service, document, or decision—anything produced for a customer or next process step.

🧱 Overproduction

Overproduction happens when more is made than needed or too early—resulting in excess inventory, wasted time, and storage issues. It’s considered the worst type of waste in Lean.

📊 P Chart

A P Chart is a control chart that monitors the proportion (percentage) of defective units in a sample. It’s ideal for tracking quality in binary outcomes like pass/fail or yes/no.

📉 Pareto Chart

A Pareto Chart is a combo bar-line graph that shows the frequency of defects (bars) alongside their cumulative impact (line). It visually emphasizes the vital few issues that cause the majority of problems.

📈 Pareto Principle (80/20 Rule)

Named after economist Vilfredo Pareto, this principle suggests that 80% of problems come from 20% of causes. It’s a key concept in prioritizing efforts for maximum impact.

🔁 PDCA (Plan-Do-Check-Act)

Also known as the Deming Cycle, PDCA is a four-step method for continuous improvement:

• Plan the change
• Do the implementation
• Check the results
• Act based on findings
  It’s also rendered as PDSA (Plan-Do-Study-Act).

🏁 Perfection

In Lean Six Sigma, Perfection isn’t about flawlessness—it’s about the pursuit of continuous, incremental improvement until zero waste and full customer satisfaction are achieved.

🧪 Pilot

A Pilot is a controlled, small-scale implementation of a solution to validate its effectiveness before rolling it out fully. It reduces risk and provides real-world feedback for refinement.

🧯 Poka-Yoke (Error Proofing)

Poka-Yoke is a Japanese term meaning “mistake-proofing.” It refers to any mechanism or approach that prevents errors from occurring—or catches them early—often through simple, clever design.

📊 Process Cycle Efficiency (PCE)

PCE is a Lean metric that compares the time spent on value-added work to the total lead time of a process. It’s calculated as:
PCE = (Value-Added Time ÷ Total Lead Time) × 100%
Higher PCE = leaner process.

🔧 Process Improvement

This refers to any effort to make a process better—whether by eliminating waste, reducing variation, speeding up delivery, or improving quality. It’s the central aim of Lean Six Sigma.

📜 Project Charter

A Project Charter is a formal document that outlines the purpose, scope, team, timelines, goals, and success criteria of a project. It acts like a contract between the project team and its sponsor.

🧬 Project Y

Project Y represents the primary output or key metric of interest in a Lean Six Sigma project—often expressed as Y = f(x), where Y is the output and x are the inputs affecting it.

📉 Proportion Defective

This is the ratio of defective units to total units, often expressed as a percentage. It’s used in control charts and quality metrics to track process performance over time.

📦 QDIP (Quality, Delivery, Inventory, Productivity)

QDIP is a visual performance tracking system that scores processes daily across four key areas:

• Quality
• Delivery
• Inventory
• Productivity
  It’s a simple, effective way to maintain discipline and spot issues early.

🏷️ Quality

In Lean Six Sigma, Quality means conformance to requirements and the ability to meet or exceed customer expectations. It’s not just about durability—it’s about value from the customer’s point of view.

🧩 QFD (Quality Function Deployment)

QFD is a structured approach to translating customer needs into technical specifications and design features. Often represented by the “House of Quality” diagram, it bridges the gap between VOC (Voice of the Customer) and engineering.

📊 Quartile

A Quartile is one-fourth (25%) of an ordered data set. Quartiles help analyze variability and distribution trends—especially when comparing different process performances.

🔁 R&R (Repeatability & Reproducibility)

These are the two components of measurement system variation:

• Repeatability: Same operator, same tool, same conditions
• Reproducibility: Different operators, same tool, same conditions
  Used in Gage R&R to evaluate consistency in measurements.

📋 RACI Matrix

A RACI matrix defines who is:

• Responsible (does the work)
• Accountable (owns the outcome)
• Consulted (provides input)
• Informed (kept in the loop)
  It clarifies roles in projects and prevents ambiguity.

📏 Range

Range is the difference between the highest and lowest values in a dataset. It gives a quick view of data spread or variability.

🔁 Repeatability

This refers to a situation where the same person, using the same equipment under the same conditions, consistently gets the same measurement.

👥 Reproducibility

This happens when different people measuring the same item get consistent results—crucial for ensuring reliable and unbiased data collection.

🔧 Rework

Rework is the time, effort, and materials spent fixing a defective product or correcting a process error. It’s a form of waste and a hidden cost that Lean aims to eliminate.

🧮 Rolled Throughput Yield (RTY)

RTY calculates the probability of a unit passing through all process steps defect-free. It helps measure end-to-end process efficiency in multi-step operations.

🌱 Root Cause Analysis (RCA)

RCA is a systematic method for uncovering the underlying causes of a problem—not just its symptoms. Tools include 5 Whys, Fishbone Diagrams, and Pareto Analysis.

💡 Root Cause Hypothesis

This is an educated assumption about what’s causing a process issue. It’s tested with data in the Analyze Phase to validate or eliminate it as the true cause.

🧮 RPN (Risk Priority Number)

Used in FMEA, RPN is a score that ranks risks based on:

• Severity
• Occurrence
• Detection
  Higher RPN = higher priority for corrective action.

🎯 RUMBA

RUMBA is a quality checklist for evaluating requirements. It stands for:

• Reasonable
• Understandable
• Measurable
• Believable
• Achievable

✍️ s or sd (Standard Deviation)

s (or sd) represents the standard deviation of a sample. It measures how much individual data points differ from the mean, helping to gauge process variation and stability.

🛠️ Seven Basic Tools of Quality (7 QC Tools)

These foundational tools—endorsed by Kaoru Ishikawa—are simple, effective, and essential for solving most quality problems:

1. Cause-and-Effect Diagram
2. Check Sheet
3. Control Chart
4. Histogram
5. Pareto Chart
6. Scatter Diagram
7. Stratification (or Flow Chart)

🎯 Sigma Score (Z-Score)

The Sigma Score indicates how many standard deviations fit between a process mean and its closest specification limit. The higher the score, the better the process performance. A 6σ score means near-perfect quality.

🔄 SIPOC Diagram

SIPOC stands for:

• Suppliers
• Inputs
• Process
• Outputs
• Customers
  It provides a high-level map of a process and is typically used during the Define Phase of DMAIC to clarify boundaries and stakeholders.

💡 Six Sigma

Six Sigma is a data-driven methodology that aims to eliminate defects and reduce variation. It relies on the DMAIC framework to improve process performance and customer satisfaction—targeting no more than 3.4 defects per million opportunities.

👔 Six Sigma Implementation Roles

The Six Sigma structure includes a tiered set of belt-based roles:

• Deployment Leader
• Champion
• Master Black Belt
• Black Belt
• Green Belt
• Yellow Belt
• White Belt
  Each role contributes differently to project execution, training, and leadership.

📌 Solution Parking Lot (Gallery Walk)

This is a dedicated space for displaying project improvements, ideas, or solutions—especially those not immediately implemented. It encourages innovation while keeping focus on scope.

⚠️ Special Cause Variation

Unlike common variation, Special Cause Variation is unpredictable and irregular—often tied to external or assignable factors. It signals that something unusual is happening and may need immediate attention.

📊 SQDC Board

SQDC stands for:

• Safety
• Quality
• Delivery
• Cost
  Used as a visual management board, it helps track daily process performance across critical areas.

📉 Stability (Process)

Stability refers to whether a process remains consistent over time without unexpected shifts or trends. A stable process exhibits only common cause variation.

📏 Standard Deviation (σ)

Standard Deviation quantifies how spread out data points are around the mean. A small standard deviation = consistent performance. A large one = lots of variability.

🧱 Stratification

Stratification is a method of separating data into meaningful layers or categories—such as by time, team, region, or machine—so patterns and problems can be more easily analyzed.

💥 Taguchi Loss Function

Introduced by Genichi Taguchi, this function shows that quality loss occurs gradually, not just outside specs. The further a product deviates from target—even if within limits—the more it diminishes customer satisfaction.

🔧 Taguchi Methods

Taguchi Methods are a set of statistical techniques that aim to improve product design and reduce variation. They include robust design, tolerance analysis, and control factors to optimize performance.

⏱️ Takt Time

Takt Time is the rate at which a product needs to be produced to meet customer demand. It’s calculated as:
Takt Time = Available Time ÷ Customer Demand

🔗 TOC (Theory of Constraints)

TOC is a process improvement strategy based on the idea that every system has one key constraint that limits performance. By identifying and addressing the constraint, you unlock flow and boost results.

🚗 Toyota Production System (TPS)

The Toyota Production System is the origin of many Lean principles. It emphasizes continuous improvement (Kaizen), waste elimination, respect for people, and building quality into the process (Jidoka & Just-in-Time).

🏢 TQM (Total Quality Management)

TQM is an older but foundational approach that involves everyone in an organization—from executives to frontline workers—in a shared effort to improve quality, processes, and culture.

🚚 Transportation (Waste)

In Lean, Transportation is considered one of the 8 wastes. It refers to unnecessary movement of materials, parts, or products during a process. More movement = more risk and no added value.

📈 Trend

A Trend is a pattern of movement over time—whether upward, downward, or fluctuating. Trends are often revealed in control charts and help in predicting future performance.

🧮 Trimmed Mean

The Trimmed Mean is the average of a dataset after removing a specified percentage of the highest and lowest values. It’s useful when dealing with outliers that distort the true central tendency.

💭 TSSW (Thinking the Six Sigma Way)

TSSW is a mindset that embodies continuous improvement, data-driven decisions, and structured problem-solving. It means applying Six Sigma principles beyond projects—into daily work thinking.

🔧 u-chart

A u-chart is a control chart used to monitor the number of defects per unit when sample sizes vary. It’s commonly used in service industries or low-volume production.

🔼 Upper Control Limit (UCL)

The UCL is the upper boundary (typically 3 standard deviations above the mean) on a control chart. If a data point goes above it, the process may be experiencing special cause variation.

🔺 Upper Specification Limit (USL)

The USL is the maximum acceptable value for a process or product attribute. Anything above this threshold is considered a defect.

⬆️ Upstream

Upstream refers to earlier steps in a process—before the current operation. Understanding upstream causes helps resolve downstream problems.

💎 Value-Adding Activities

These are process steps that directly contribute to meeting customer needs. They change the product or service, are done right the first time, and are valued by the customer.

🧠 Value Analysis

This is a method of classifying all process activities as:

• Value-Adding
• Non-Value Adding
• Value-Enabling (necessary but not directly valued, like compliance)

⚙️ Value-Enabling Activities

These steps don’t directly add value from the customer’s viewpoint but are required to run the business—like safety checks or legal compliance.

🔀 Variability

Variability refers to the tendency of a process or output to differ from one instance to another. Reducing variability is central to improving quality and predictability.

📏 Variance

Variance is the square of standard deviation and reflects how much data points diverge from the mean. It’s used in statistical calculations like ANOVA.

🔁 Variation

Variation is the extent to which a process output deviates from the expected or desired result. Lean Six Sigma targets minimizing this to create consistent, high-quality outcomes.

🧭 Voice of the Business (VOB)

VOB captures the organization’s goals—like profitability, growth, and compliance. It must be balanced with customer needs to ensure sustainable improvements.

📣 Voice of the Customer (VOC)

VOC represents customer expectations, preferences, and requirements. It’s gathered via surveys, interviews, or direct feedback to guide improvement efforts.

🔊 Voice of the Process (VOP)

VOP reflects what the process can actually deliver—based on performance data and capability analysis. It must align with VOC and VOB for harmony across the system.

⏳ Waiting (Waste)

Waiting is a Lean waste where people, materials, or information are idle—often due to poor scheduling, approvals, or bottlenecks. It slows flow without adding value.

⚪ White Belt

A White Belt is the entry-level Six Sigma role. These individuals have basic awareness of Lean Six Sigma principles and support improvement efforts in a limited capacity.

🛠️ Work in Process (WIP)

WIP includes items that are in progress but not yet complete. Too much WIP leads to inefficiencies, delays, and hidden costs—so Lean aims to reduce it.

📉 x (input variable)

In the function Y = f(x), x represents the input(s) that affect the output Y. Understanding and controlling x’s is the key to improving process performance.

✖️ X-Bar (x̄)

X̄ (pronounced “x-bar”) is the symbol for the sample mean. It’s often used in control charts to represent average process performance over time.

📊 X-Bar & R Charts

These control charts are used together to monitor process averages (X-bar) and ranges (R) over time—ideal for tracking process stability in manufacturing or service delivery.

📉 X-Bar & S Charts

Similar to X-bar & R Charts, but the S chart tracks standard deviation rather than range. Best for larger sample sizes and more precise variability tracking.

🎯 Y (output variable)

In Y = f(x), Y is the outcome or result of the process. Lean Six Sigma aims to control the x’s (inputs) to deliver the best possible Y (output).

💛 Yellow Belt

A Yellow Belt has foundational knowledge of Lean Six Sigma and supports projects led by Green or Black Belts. They help with data collection, analysis, and local process improvements.

🎯 Yield

Yield measures the percentage of outputs that meet quality standards the first time, without rework. Higher yield = less waste, less cost, more customer satisfaction.

🔠 Z (Sigma Score)

Z-score represents the number of standard deviations a data point is from the mean—or how far a process is from its specification limits. It’s the numerical value behind the Sigma level.

🧼 Zero Defects

Coined by Philip Crosby, Zero Defects is the goal of doing things right the first time—fostering a mindset of precision and accountability across the organization.

🚫 Zero Quality Control (ZQC)

ZQC aims to eliminate the need for inspection by preventing errors before they occur—often through poka-yoke and smart design. It treats inspection as a form of waste, not assurance.

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