LPSCE key terms

Any activity that consumes resources without creating value for the customer. Typical forms include overproduction, waiting, transport, overprocessing, inventory, motion, and defects; Lean targets these for elimination.

Work that physically or informationally transforms a product or service in a way the customer would willingly pay for, done right the first time. Anything else is business-necessary waste or pure waste.

A visual mapping technique that traces material and information flow from customer request to delivery, showing process steps, inventory, lead time, and value-added ratio to expose improvement opportunities.

Continuous, incremental improvement carried out by the people who do the work. Events are typically short, focused, team-based efforts to remove waste and standardize a better method.

The available production time divided by customer demand, expressed as time per unit. It sets the pace a process must meet to satisfy demand without overproducing.

A pull signal, often a card or electronic marker, authorizing upstream work to replenish what downstream has consumed. It limits work-in-process and prevents overproduction.

An error-proofing device or design feature that prevents a mistake from being made or makes it immediately obvious. Examples include fixtures that only accept correct orientation and sensors that stop the line.

A measurable characteristic of a product or service that directly reflects what the customer values. CTQs translate vague customer needs into specifications a process can be measured against.

Structured collection of customer needs, expectations, and complaints through interviews, surveys, complaints, and observation. It is the raw input that gets translated into CTQs and project goals.

A framework classifying features as basic (expected), performance (more is better), or delighter (unexpected). It helps teams prioritize requirements that drive satisfaction versus those that only prevent dissatisfaction.

A formal document authorizing a Six Sigma project. It states the problem, goal, scope, business case, team, milestones, and constraints, and is signed by the project sponsor.

A concise description of the gap between current and desired performance, including magnitude, location, timing, and customer impact, without stating a cause or a solution.

A goal written to be specific, measurable, achievable, relevant, and time-bound. In DMAIC it defines the target metric and date the team commits to achieving.

A high-level map of suppliers, inputs, process, outputs, and customers used to define project scope and boundaries. It shows where the process starts and stops before detailed mapping.

Identifying everyone affected by or able to influence a project, then assessing their interest and influence to plan communication and buy-in. It supports change management throughout DMAIC.

The five-phase Six Sigma improvement cycle: Define, Measure, Analyze, Improve, Control. Each phase has required deliverables and a tollgate review before the next phase begins.

A design-for-Six-Sigma cycle: Define, Measure, Analyze, Design, Verify. It is used to create a new process or product when an existing one cannot meet requirements through improvement alone.

A checkpoint at the end of each DMAIC phase where the team, sponsor, and belt review deliverables and evidence before approving progress or redirecting the project.

A set of studies quantifying how much variation in measured data comes from the measurement system itself, including repeatability, reproducibility, bias, linearity, and stability.

A study separating measurement variation into repeatability (same operator, same part) and reproducibility (different operators). Results are expressed as a percentage of total or tolerance variation.

An MSA method for pass/fail or categorical judgments, measuring agreement within raters, between raters, and against a known standard. Kappa statistics are commonly reported.

A comparison of process spread and centering against specification limits, expressed as Cp, Cpk, Pp, or Ppk. Higher values mean fewer expected defects relative to tolerances.

The upper and lower bounds on a characteristic set by the customer or design, not by the process. They define acceptability and are independent of the process's natural variation.

Breaking a dataset into subgroups by machine, shift, operator, lot, or other factor so patterns hidden in aggregate data become visible. It often reveals the true source of variation.

A bar chart of categories sorted from largest to smallest with a cumulative line, used to focus effort on the few causes producing most of the effect.

A cause-and-effect diagram organizing potential causes into branches such as people, machine, method, material, measurement, and environment. It structures brainstorming before data collection.

An iterative questioning technique that asks why repeatedly to move from a symptom to a root cause. Each answer becomes the subject of the next why, usually stopping at a controllable cause.

The underlying reason a problem occurs that, if removed, prevents recurrence. It is verified with data rather than assumed from opinion or a single observation.

A statistical procedure comparing sample evidence against a null hypothesis, yielding a p-value used to decide whether an observed difference or relationship is likely real rather than chance.

Rejecting a true null hypothesis, also called alpha or the producer's risk. In improvement work it means declaring a factor significant when it is not.

Failing to reject a false null hypothesis, also called beta or the consumer's risk. Its complement, power, is the probability of correctly detecting a real effect.

The number of observations needed to detect an effect of practical size with acceptable alpha and power. It depends on effect size, variability, and the test chosen.

A structured set of runs that varies factors together so their individual and interacting effects on a response can be estimated efficiently, rather than changing one factor at a time.

Failure Mode and Effects Analysis ranks potential failure modes by severity, occurrence, and detection to prioritize preventive action. It is used both to design solutions and to control risk.

A limited trial of a proposed solution under realistic conditions to confirm it works, surface side effects, and build evidence before full-scale rollout.

A time-ordered plot of a process metric with statistically derived control limits. It distinguishes common-cause variation from special-cause signals that require investigation.

A document specifying which metrics are monitored, how and how often they are measured, who responds to out-of-control signals, and what corrective action is taken.

A documented, agreed method for a task that captures the current best sequence, timing, and quality checks. It is the baseline that makes deviations visible and improvement possible.

The structured approach to moving people from current to future ways of working, addressing communication, resistance, training, and reinforcement so improvements persist.

A responsibility chart labeling each task or decision as responsible, accountable, consulted, or informed. It clarifies roles and prevents gaps or duplicated ownership on a project team.