F Distribution

The F distribution is a probability distribution that arises from the ratio of two independent chi-squared variables divided by their respective degrees of freedom. It is commonly used in variance-based tests, such as ANOVA, to compare statistical models and assess group differences.
See also: Analysis of Variance (ANOVA), F-test

F-test

An F-test is any statistical test that uses the F distribution as its sampling distribution under the null hypothesis. It is typically employed to compare two variances or to assess the overall significance in models (such as in regression or ANOVA).
See also: Variance Analysis, Statistical Significance

F-test (ANOVA)

In ANOVA (Analysis of Variance), the F-test is used to determine whether there are significant differences among group means by comparing the between-group variance to the within-group variance. A large F statistic suggests that not all group means are equal.
See also: F Distribution, Analysis of Variance

FMEA (Failure Mode and Effects Analysis)

FMEA is a structured, proactive tool for identifying potential failure modes in a system, product, or process, and for assessing their effects on performance. By assigning severity, occurrence, and detection ratings to each failure mode, FMEA enables teams to prioritize risk mitigation efforts.
See also: Risk Priority Number (RPN), FMECA

FMECA (Failure Mode Effects & Criticality Analysis)

FMECA extends FMEA by including a criticality analysis, which quantitatively evaluates the severity and probability of failure modes. This method helps organizations prioritize corrective actions based on how critical a failure would be to the overall system or product performance.
See also: FMEA, Criticality Analysis

FPY (First Pass Yield)

First Pass Yield is a performance metric that measures the percentage of products or outputs that meet quality standards without requiring any rework or correction during the initial production process. It is calculated by dividing the number of conforming units by the total units produced.
See also: Process Efficiency, Quality Metrics

Facilitator

A facilitator is an individual who guides discussions, meetings, or workshop sessions to ensure that objectives are met. In quality improvement projects, a facilitator maintains focus, encourages participation, and helps manage group dynamics without imposing content-based opinions.
See also: Scrum Master, Coach

Factor (Experimental)

In experimental design, a factor is any independent variable that is deliberately changed to observe its effect on a dependent variable. Factors can be quantitative (e.g., temperature, speed) or qualitative (e.g., color, type).
See also: Independent Variable, DOE (Design of Experiments)

Factorial Design

A factorial design is an experimental setup that investigates the effects of two or more factors simultaneously by testing all possible combinations of factor levels. This approach reveals not only individual factor impacts but also interaction effects between factors.
See also: Experimental Design, DOE

Failure

A failure is any event or condition in which a system, component, or process does not perform as intended or does not meet its specified requirements. Failures can result from design flaws, manufacturing defects, or process deviations.
See also: Defect, Nonconformity

Failure Cost

Failure cost is the expense incurred due to a product or process failing to meet quality standards. It includes internal costs (such as scrap and rework) and external costs (such as warranty claims and recalls).
See also: Quality Costs, Cost of Poor Quality

Failure Mode Analysis (FMA)

Failure mode analysis is a process similar to FMEA that focuses on identifying and categorizing the ways in which a product or process might fail. While it systematically lists failure modes and their causes, it may not always incorporate the full quantitative risk evaluation found in FMEA.
See also: FMEA, Root Cause Analysis

Failure Mode and Effects Analysis (FMEA)

(See the definition above under "FMEA (Failure Mode and Effects Analysis)")

Failure Mode Effects and Criticality Analysis (FMECA)

(See the definition above under "FMECA (Failure Mode Effects & Criticality Analysis)")

Failure Rate

Failure rate is the frequency with which an engineered system or component fails, typically expressed over a specified time period (e.g., failures per hour). In reliability engineering, it is used to predict product lifespan and maintenance needs.
See also: Reliability, Mean Time Between Failures (MTBF)

Failure Tracking

Failure tracking is the systematic recording and monitoring of failures in a process or product. This data collection helps identify patterns or recurring issues that can be addressed through continuous improvement practices.
See also: Corrective Action, Continuous Improvement

Fault Tree Analysis (FTA)

Fault Tree Analysis is a top-down, deductive methodology used to analyze the causes of system failures. By mapping out the logical relationships between different failure events, FTA helps identify critical risk areas and supports preventive measures.
See also: Event Tree Analysis, Root Cause Analysis

Feeder Lines

Feeder lines are subsidiary production lines or processes that supply components, materials, or subassemblies to a main assembly or production line. Their synchronized operation is critical for maintaining smooth overall workflow and reducing bottlenecks.
See also: Production Flow, Value Stream Mapping

Feedback

Feedback is the information or reaction received about the performance of a system, process, or product. In quality management, feedback is used to make adjustments and drive continuous improvement initiatives.
See also: Continuous Improvement, Process Control

FIFO (First In, First Out)

FIFO is an inventory management and production scheduling principle where the oldest items are processed, sold, or used first. This method helps prevent issues like obsolescence and waste, ensuring a smooth rotation of stock.
See also: Inventory Management, LIFO

Fishbone Diagram

Also known as an Ishikawa or cause-and-effect diagram, the fishbone diagram is a visual tool that helps identify the root causes of a problem. Causes are typically categorized (e.g., methods, machines, materials) to facilitate structured problem solving.
See also: Root Cause Analysis, 5 Whys

Fit for Use

A product or service is considered "fit for use" when it meets or exceeds the requirements of its intended application. This concept emphasizes that quality is defined by the ability to satisfy user expectations and perform reliably in actual use conditions.
See also: Customer Requirements, Quality Assurance

Five S’s (5S)

The 5S methodology is a workplace organization tool that aims to increase efficiency and reduce waste through five steps:

1. Sort – Eliminate unnecessary items.
2. Set in Order – Organize the necessary items.
3. Shine – Clean the work area.
4. Standardize – Establish standards for processes and organization.
5. Sustain – Maintain and review standards.
   See also: Lean Manufacturing, Workplace Organization

Five Whys (5 Why Analysis)

The Five Whys is a simple, iterative interrogative technique used to explore the root cause of a problem by asking "why" repeatedly (typically five times) until the fundamental issue is identified.
See also: Root Cause Analysis, Fishbone Diagram

Five-Phase Lean Approach

The five-phase lean approach is a framework for implementing lean principles within an organization. Although terminology may vary, the phases commonly include:

1. Define value
2. Map the value stream
3. Establish flow
4. Create pull
5. Pursue perfection

This systematic approach aims to eliminate waste, optimize processes, and continuously improve quality.

See also: Lean Transformation, Value Stream Mapping

Fixed Sample Size Plan

A fixed sample size plan is a type of acceptance sampling in which a predetermined number of units from a batch are inspected. Based on the results, the entire lot is either accepted or rejected. This approach is often used when consistent sampling parameters are required.
See also: Acceptance Sampling, Quality Control

Flowchart

A flowchart is a diagrammatic representation of a process, displaying the sequence of steps, decision points, and actions using standardized symbols. Flowcharts facilitate clear communication and help identify potential process improvements or bottlenecks.
See also: Process Mapping, Workflow Diagram

Flow (Workflow)

In the context of workflow, flow refers to the smooth and efficient progression of tasks within a process or production system. A well-designed flow minimizes delays, bottlenecks, and idle times, contributing to overall process effectiveness.
See also: Process Optimization, Value Stream Mapping

Force Field Analysis

Force field analysis is a decision-making tool used to identify, analyze, and weigh the driving forces that support a change and the restraining forces that oppose it. The technique helps organizations plan strategies to reinforce positive influences while mitigating negatives.
See also: Change Management, SWOT Analysis

Fractional Factorial Design

Fractional factorial design is an experimental strategy that investigates only a fraction of the possible combinations of factors. This design reduces the number of experiments needed while still providing insights about the main effects and some interaction effects, albeit with certain confounding limitations.
See also: Factorial Design, Experimental Design