EXIN LSSA Six Sigma Black Belt key terms

A measurable customer requirement translated from a vague voice-of-customer statement into a specific, verifiable characteristic that a process output must satisfy.

The structured collection of customer needs, expectations, and complaints gathered through interviews, surveys, and field data, used as input for defining project requirements.

A classification scheme that sorts product or service features into must-be, performance, and attractive categories according to how their presence or absence affects customer satisfaction.

A high-level process map showing Suppliers, Inputs, Process steps, Outputs, and Customers, used at project scoping to define boundaries and reveal where measurement should begin.

A formal document authorizing a Six Sigma project that states the business case, problem statement, goal, scope, team, milestones, and expected financial benefit.

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

The process of identifying everyone affected by or able to influence a project, then assessing their interest, influence, and likely support to plan communication and engagement.

A project objective written to be Specific, Measurable, Achievable, Relevant, and Time-bound, so that success can be judged objectively at project closure.

The core Six Sigma model expressing that a measured output Y is a function of controllable input variables x; improvement work identifies and adjusts the influential x's.

The five-phase improvement cycle of Define, Measure, Analyze, Improve, and Control, applied to existing processes whose performance must be raised to customer requirements.

The design-for-Six Sigma cycle of Define, Measure, Analyze, Design, and Verify, used when creating a new process or product rather than repairing an existing one.

Defects per million opportunities, calculated as defects divided by the product of units and defect opportunities per unit, then multiplied by one million.

A capability index expressing process performance as the number of standard deviations between the process mean and the nearest specification limit, with a 1.5-sigma shift convention for long-term data.

The probability that a unit passes every step of a multi-step process without a single defect, computed as the product of the first-pass yields of all steps.

Indices comparing specification width to process spread (Cp) and additionally accounting for centering of the mean within the limits (Cpk); higher values mean fewer defects.

A set of studies, chiefly Gage R&R, that quantifies how much observed variation comes from the measurement system rather than from the parts or process being measured.

A repeatability and reproducibility study that separates variation caused by the gauge itself, by operators, and by interaction between them, usually expressed as a percentage of total variation.

A study for pass/fail or categorical inspection data that measures how consistently appraisers agree with themselves, with each other, and with a known reference standard.

The documented performance of a process before improvement, including its sigma level or capability indices, used later to prove that changes produced a real gain.

A document specifying which variables to measure, operational definitions, sampling method, sample size, frequency, location, and who records the data, written before data are gathered.

A precise, unambiguous description of how a characteristic is measured and judged, so that different people classify the same item identically.

The documented approach for selecting a subset of units for measurement, covering sample size rationale, random or rational subgroup selection, and sampling frequency over time.

Grouping measured units so that variation within a subgroup reflects only common causes, while shifts between subgroups reveal special causes; the basis of control chart sensitivity.

A time-ordered plot of a statistic with center line and statistically derived limits, used to separate common-cause variation from special-cause signals.

The routine, inherent variation produced by the design of a stable process; reducing it requires changing the system rather than reacting to individual points.

Variation arising from an identifiable, non-routine event or assignable source, signaled by out-of-control patterns on a control chart and addressed by finding that source.

A visual representation of the sequence of steps, decisions, and handoffs in a process, used to expose non-value-adding activity, rework loops, and measurement points.

A lean tool that charts material and information flow across a whole value stream, including lead time and queue data, to locate waste and design a future-state flow.

Any activity consuming resources without creating value for the customer; commonly classified as overproduction, waiting, transport, overprocessing, inventory, motion, and defects.

Continuous, incremental improvement carried out by the people who do the work, often through short focused events that implement small changes quickly.

A workplace organization method whose five steps sort, set in order, shine, standardize, and sustain, reducing motion waste and making abnormal conditions immediately visible.

An error-proofing device or design feature that prevents a mistake from being made or makes an error immediately detectable before it reaches the customer.

A written, controlled instruction describing the approved method for performing a task, forming part of the control phase's effort to lock in improved performance.

A document listing each process characteristic, its specification, the measurement method, sample size and frequency, control method, and the reaction plan when a signal occurs.

A structured investigation using tools such as the fishbone diagram or 5 Whys to trace an observed effect back to the underlying system cause that, if removed, prevents recurrence.

A branching diagram that organizes candidate causes of a problem into categories such as people, machine, method, material, measurement, and environment to guide verification.

An iterative questioning technique that asks why a problem occurred repeatedly, each answer becoming the next question, until the actionable root cause is reached.

A statistical procedure that compares sample evidence against a stated null hypothesis, yielding a p-value used to decide whether an observed difference is likely real.

Type I error rejects a true null hypothesis (false alarm, probability alpha); Type II error fails to reject a false null hypothesis (missed effect, probability beta).

The probability of detecting a real effect of a given size, equal to one minus beta; it rises with larger samples, larger effects, and lower noise.

A test comparing means of three or more groups by partitioning total variation into between-group and within-group components and forming an F ratio.

A planned set of runs in which factors are deliberately varied together so that their individual and interaction effects on a response can be estimated efficiently.

A modeling technique that fits an equation relating one or more predictor variables to a continuous response, quantifying both the strength and form of the relationship.

Calculating the number of observations needed to detect a specified effect size with chosen alpha and power, given the process standard deviation.

A team-based risk assessment that scores each potential failure by severity, occurrence, and detection, producing a priority number that directs preventive action.