Quality Assurance and Process Variation Study of Process Variation

Quality Management System: Assurance versus Control

• Quality Assurance (QA)     * Phase: Associated with Project Execution.     * Focus: The primary focus is on process improvement.     * Function: It ensures that the processes used to manage and create the deliverables are followed and are effective.

• Quality Control (QC)     * Phase: Associated with Monitoring and Controlling of the Project.     * Focus: The focus is on the product or output.     * Purpose: To check and test that specific quality requirements and standards are met.

The Hierarchy of Quality Management

• The Big Picture Overview: Quality is managed across a descending hierarchy of complexity:     * Systems: The overarching structure.     * Processes: The high-level sets of activities.     * Subprocesses: Broken down components of a process.     * Steps: Individual actions within a subprocess.

Defining a Process

• Conceptual Definitions:     * A series of actions, operations, or functions leading to a specific end result.     * A set of inputs that undergo one or more transformations to produce outputs.     * The steps of a proscribed or formal procedure.     * A structured set of interrelated operations, activities, and tasks that produce a set of specific outputs.

• Process Components:     * Inputs: Resources such as Material, Energy, and Information ($I$).     * Transformations: The internal process steps that convert inputs to outputs.     * Outputs ($X$): The final results, categorized as either Products or Services.     * Operator Inputs ($u$): Includes initial settings, feedback, and corrective actions.     * Disturbances ($d$): Environmental factors and external variables including:         * Temperature.         * Humidity.         * Vibrations.         * Dust.         * Sunlight.

The 7 Ms: Categories of Process Inputs

To identify where variation or quality issues may arise, inputs are categorized into the "7 Ms":

1. Man: The human element, including operators and staff.

2. Machine: The equipment and physical plant used for production.

3. Methods: The procedures, recipes, or protocols followed.

4. Mother Nature: Environmental conditions (e.g., climate, external noise).

5. Management: Oversight, organizational structure, and decision-making.

6. Materials: Raw materials and purchased components.

7. Measurement system: The tools and procedures used to collect data and evaluate quality.

Classification of Process Inputs

Every input entering a process can be classified for better control:

• $C$ - Controllable: Factors that can be adjusted or maintained (e.g., machine speed).

• $NC$ - Noncontrollable: Factors that cannot be adjusted (e.g., certain environmental conditions).

• $N$ - Noise: Unwanted or random variables that interfere with the process.

• $X$ - Critical: Factors that have a significant and direct impact on the quality of the output.

Process Variation and the Mathematical Model

• Definition of Variation: The measure of "differences" in the manufacturing process. Variation can occur within the process itself or in the final outputs.

• Core Principle: Less Variation leads to Higher Quality.

• The Variation Equation:     * The relationship between process variables and the output can be expressed as:     * $X = f(M, I, u, d)$     * Where:         * $M$: Physical Plant, Equipment, etc.         * $I$: Purchase/Inputs.         * $u$: Operator and Real-Time Control.         * $d$: Quality Control ($Q.C.$), Utilities, and environmental disturbances.

Understanding Variability in Manufacturing

In every manufacturing operation, variability exists. It is defined as the difference between the produced quality measure and its intended target. High variability is problematic because it leads to waste or excess production costs.

1. Variability Inherent in the Process (Common Causes)

• Nature: Also known as chance causes, expected variation, or chronic causes.

• Source: Small, random occurrences that are built into the system.

• Examples:     * Product variability inherent in the design.     * Random effects of components and raw materials.     * Small mechanical linkage variations in a machine.     * Slight variations in an operator's performance.     * Discrepancies in test equipment and test procedures.     * Machine vibration and temperature fluctuations.     * Human variation in setting control dials.

• Status: A process existing only with common causes is considered a Stable Process. A stable process has the same normal distribution of output at all times and is said to be "In Control."

2. Variability from Assignable Causes (Special Causes)

• Nature: Also known as unexpected variation, unnatural causes, or sporadic causes.

• Source: External factors that are not part of the standard stable process; they often contribute to a large part of the overall variability.

• Examples:     * Gradual changes in temperature or tool wear.     * Operator fatigue.     * Two operators or machines performing at different averages.     * Two or more processes operating at different levels.     * A single source operating with an unstable average.     * Major human errors or incorrect recipes.     * Specific failures like a blown gasket or natural disasters like an earthquake.     * Batches of defective raw materials.

• Status: A process with special cause variation is an Unstable Process.

Detecting and Managing Variation

Control Limits

• Definition: These are the "Voice of the Process."

• Calculation: They are calculated from actual process data.

• Application: They appear on control charts and apply to subgroups of data.

• Function: They provide an early warning. They show the range of variability expected from the process and tell us when to take action on the process itself.

Specification (Spec) Limits

• Definition: These are the "Voice of the Customer."

• Definition Source: These are defined and set by the customer or design requirements.

• Application: They appear on histograms and apply to individual items.

• Function: They determine the "fitness-for-use." They separate good items from bad and tell us when to disposition the product (e.g., release it for sale, re-work it, re-grade it, quarantine it, or scrap it).

Key Differences and Rules

• Specification Limits are promises to the customer about what will be provided and should be based on total system losses.

• Control Limits are based purely on actual process output.

• Rule: Specification limits do NOT influence control limits.

• Financial Impact: Variation (process variability) directly affects the total process losses.

Strategies for Reducing Variation

• Reducing Variation in a Stable Process:     * Since variation is inherent, changes must be based on a scientific approach.     * Methods include structured problem solving and planned experiments (e.g., Design of Experiments).

• Reducing Variation in an Unstable Process:     * Reactive Approach: Quickly detect special cause variations and stop production until the process is fixed.     * Preventive Approach: Identify the root source of special causes and eliminate them permanently.     * Warning: Management must not ignore special causes, as they disrupt the predictability of the system.