LE

Operations Management – Chapter 4: Quality & Performance

Learning Objectives

  • Students should be able to:
    • 4.1 Define the four major costs of quality and articulate how ethical behavior influences the total cost of delivering products & services.
    • 4.2 Explain the core principles of Total Quality Management (TQM) and the Six Sigma system.
    • 4.3 Describe the interface between acceptance sampling and on‐going process-performance approaches in a supply chain.
    • 4.4 Construct and interpret process control charts in order to judge whether a process is in or out of statistical control.
    • 4.5 Evaluate whether a process is capable of meeting design specifications.
    • 4.6 Summarize the purpose and content of International Quality Documentation Standards (e.g., ISO 9001:2015) and the Baldrige Performance Excellence Program.
    • 4.7 Discuss the systems approach to TQM—how all the elements integrate into one coherent philosophy.

Costs of Quality

  • General points
    • Companies invest heavily in systems, training, & organizational change to lift quality and process performance.
    • A defect = any failure of a process to satisfy its customer.
  • The four (text lists five when ethics is separated) classic cost categories:
    • Prevention costs – \text{Cost incurred to avoid defects before they happen}. Examples: training, process engineering, quality planning.
    • Appraisal costs – \text{Cost of assessing the performance level of processes}. Examples: inspections, audits, testing labs.
    • Internal failure costs – \text{Cost of defects found before the product/service reaches the customer}. Examples: scrap, rework, re-inspection, downtime.
    • External failure costs – \text{Cost of defects discovered after receipt by the customer}. Examples: warranty claims, returns, field service, recalls.
    • Warranty = written guarantee to repair/replace or make-good on defective output.
    • Ethical failure costs (spotlighted separately) – Societal & monetary losses tied to knowingly passing defective goods/services downstream, thereby endangering stakeholders (stockholders, customers, employees, partners, creditors, broader society).
  • Ethics–quality connection: investing in higher internal costs (prevention/appraisal) is ethically preferable to risking external/ethical failures that damage trust, safety, and the firm’s reputation.

Total Quality Management (TQM) and Six Sigma

  • TQM Philosophy – built on three mutually reinforcing principles:

    1. Customer Satisfaction
    • Conformance to Specifications – Does output meet explicit written specs?
    • Value – Appropriate balance of price vs benefits/performance.
    • Fitness for Use – Suitability of the product/service for the customer’s actual application.
    • Support – Quality of after-sale service, installation, training, repair.
    • Psychological Impressions – Intangibles (brand image, aesthetics, feel, courtesy, ambiance).
    1. Employee Involvement
    • Cultural Change: “Quality at the Source” – everyone responsible for their own quality.
    • Teams / Empowerment:
      • Problem-solving teams – ad-hoc groups tackling specific issues.
      • Special-purpose teams – cross-functional task forces.
      • Self-managed teams – autonomous units owning a process segment.
    1. Continuous Improvement (Kaizen)
    • Never-ending search for better methods, lower waste, improved consistency.
    • Plan–Do–Check–Act (PDCA) Cycle – aka Deming Wheel:
      • Plan – Identify gap, analyze root causes, devise remedies.
      • Do – Implement change on a limited scale/pilot.
      • Check – Measure results vs expectations.
      • Act – Standardize successful change or begin new cycle.
  • TQM Wheel (Fig 4.1) – visual summary placing Customer at the hub, surrounded by Employee Involvement and Continuous Improvement, supported by the necessary hard & soft management practices.

  • Six Sigma System

    • "Comprehensive & flexible" framework for achieving, sustaining, maximizing business success by minimizing defects & variability.
    • Leverages TQM pillars but adds a stronger analytical/financial discipline.
    • Goal: design processes whose mean is centered and whose natural variation (±3\sigma) sits well inside the specification limits, i.e. output lies six standard deviations (6\sigma) away from either design limit → ~~3.4 defects per million opportunities (DPMO).
    • Uses data-driven DMAIC (Define–Measure–Analyze–Improve–Control) or DMADV for design.
    • Focuses on both spread reduction and mean centering (Fig 4.3).

Acceptance Sampling

  • Definition – use of statistical sampling to decide whether to accept or reject a lot received from a supplier.
  • Key parameter: Acceptable Quality Level (AQL) – maximum % defective that the consumer is willing to tolerate on average.
  • Interface (Fig 4.4) – acceptance sampling acts as a gate between supplier & buyer, complementing upstream process controls.
  • Logic: Inspecting samples (instead of entire lot) trades off inspection cost vs risk of accepting bad lots or rejecting good ones.

Statistical Process Control (SPC)

  • Core Idea – Apply statistics to verify a process is delivering what the customer wants while it is running.
  • Variation of Outputs
    • Because of many small influences, no two units are exactly identical.
  • Performance Measures
    • Variables data – measured on a continuous scale (e.g., length, time, temperature).
    • Attributes data – counted as conforming/nonconforming (e.g., number of wrong orders).
  • Inspection Strategies
    • Complete inspection – every unit checked; reserved for extremely critical operations or when cost of passing a defect >> cost of inspection.
    • Sampling plan – defined by:
    • Sample size (n)
    • Sampling frequency / time between samples
    • Decision rules (when to adjust, stop, investigate)
  • Distribution relationships (Fig 4.5) – sampling distribution of means narrows (variance \sigma^2/n) relative to process distribution.
  • Causes of Variation (Fig 4.6)
    • Common (random) causes – natural, unavoidable, collectively create stable variation.
    • Assignable causes – specific, identifiable, correctable factors (machine out of alignment, wrong material, operator error).
  • Control Charts
    • Graphical time-ordered plots with three horizontal lines:
    • Center Line (CL) – process average target.
    • Upper Control Limit (UCL) and Lower Control Limit (LCL) – decision thresholds, typically \pm 3\sigma of sampling distribution.
    • Purpose: distinguish common-cause variation (stay inside limits, random pattern) from assignable-cause signals (rule violations, runs, trends, points outside limits).
    • Fig 4.7 – relation between limits & sampling distribution.
    • Fig 4.8 illustrates typical patterns:
    • (a) Normal – no action.
    • (b) Run (trend) – investigate.
    • (c) Sudden shift – monitor closely.
    • (d) Point exceeds limit – take corrective action.

Process Capability

  • Concept – whether a stable process (i.e., in control) can meet design specifications consistently.
    • Nominal value – design target.
    • Tolerance – permitted deviation (USL & LSL).
  • Graphical cases (Fig 4.13, 4.14):
    • (a) Process capable – distribution entirely inside specs.
    • (b) Process not capable – too much spread or mean off-center, some output outside specs.
    • Reducing variability (smaller \sigma) increases capability even without changing the mean.
  • Popular indices (not explicitly shown in slides but standard):
    • Cp = \frac{USL - LSL}{6\sigma} – compares width of spec band to natural process spread.
    • Cpk = \min \left(\frac{USL - \mu}{3\sigma},\frac{\mu - LSL}{3\sigma}\right) – also captures centering.
    • Rule of thumb: Cp, Cpk \ge 1.33 often required; \ge 2.0 for Six Sigma design.

International Quality Documentation Standards

  • ISO 9001:2015 (latest in ISO 9000 family)
    • Specifies what a firm must document & do to meet customer and regulatory quality requirements, enhance satisfaction, and drive continual improvement.
    • Focus areas: context of the organization, leadership commitment, process approach, risk-based thinking, knowledge management.

Malcolm Baldrige Performance Excellence Program

  • Purpose – Encourage & recognize robust quality and performance excellence in U.S. organizations; share best practices.
  • Benefits of applying
    • Rigorous self-assessment → clarifies “what quality means” to the organization.
    • Proven ROI: firms report higher productivity, market share, morale.
  • Seven major criteria
    1. Leadership
    2. Strategic Planning
    3. Customer Focus
    4. Workforce Focus
    5. Operations Focus
    6. Measurement, Analysis, and Knowledge Management
    7. Results (financial, customer, workforce, process, leadership outcomes)

Systems Approach to TQM

  • Figure 4.15 (Integrative View) depicts how all quality elements interrelate:
    • Leadership & Strategy create vision and infrastructure.
    • Customers & Markets define requirements.
    • Workforce, Suppliers, Processes execute & improve.
    • Information & Analysis supply feedback.
    • Results feed the next planning cycle → closed-loop system aligning goals, processes, and performance.
  • Emphasizes that piecemeal tools (control charts, teams, ISO certification, etc.) only succeed when embedded in this holistic framework.

Ethical, Philosophical & Practical Implications

  • Ethical lapses (e.g., knowingly shipping defects) incur ethical failure costs that can dwarf all other categories via lawsuits, recalls, loss of life, and reputational damage.
  • Quality is not merely a technical parameter but a social contract with customers & society.
  • Continuous improvement & employee empowerment embody respect for people, fostering a culture of learning and accountability.
  • Implementation must balance statistical rigor (SPC, Six Sigma) with human factors (training, teamwork, leadership).

Numerical / Statistical References & Key Equations

  • Six Sigma target: defect rate ≈ 3.4 \text{ DPMO} (when mean centered and \sigma stable).
  • Control limits for (\bar x)-chart: UCL = \mu + 3\left(\frac{\sigma}{\sqrt{n}}\right), LCL = \mu - 3\left(\frac{\sigma}{\sqrt{n}}\right).
  • Capability indices (already shown above): Cp, Cpk.
  • Relationship between sampling & process distributions: variance of sample mean = \sigma^2 / n$$.

Connection to Prior & Future Topics

  • Builds on Process Analysis (Chapter 3): quality determines effectiveness of the mapped processes.
  • SPC, capability, and ISO certification feed directly into Supply Chain Integration and Lean Systems (future chapters) by ensuring consistent, waste-free flows.
  • Six Sigma tools merge with Design for Manufacturing & Service (product development) to create built-in quality.