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Notes on Quality Management

  • Plan Quality Management
    • Determines the quality standards for the project and product
    • Creates the quality management plan, process improvement plan, and the quality metrics
  • Control Quality (QC)
    • Evaluates the products or outputs to ensure that they comply with the requirements
    • Creates the QC measurements, verified deliverables, and validated changes
  • Manage Quality (QA)
    • Translates the quality plan into executable quality activities.
    • Increases the probability of achieving quality objectives
    • A component of the Manage Quality process is conducting quality assurance
    • QA audits the results from QC (the QC measurements) against the quality metrics to identify areas for improvement
    • Considered the umbrella over continuous process improvement
    • Managing quality activities are considered a cost of conformance (money spent to avoid failures)
  • Quality Approaches
    • Deming – Organizations can increase quality and reduce costs by practicing continuous process improvement and by thinking of manufacturing as a system, not bits and pieces.
    • Juran – Applied the Pareto principle to quality issues (80% of the problems originate from 20% of the causes) and also developed “Juran’s Trilogy”: quality planning, quality control, and quality improvement.
    • Crosby – Created the principle of Doing it Right the First Time (DIRFT).
    • Shewhart – Developed the Plan-Do-Check-Act (PDCA) Cycle.
  • Quality Terms
    • Quality – The degree to which characteristics fulfill requirements.
    • Grade – A category assigned to products or services having the same functional use but different technical characteristics.
    • Precision – The values of repeated measurement are consistent.
    • Accuracy – The measured value is very close to the target value.
    • Attribute Sampling – The result conforms, or it does not.
    • Variable Sampling – The result is rated on a scale that measures the degree of conformity.
    • Special Causes of Variance – Unusual events, difficult to predict.
    • Common Causes of Variance – Normal process variation (aka random causes)
    • Tolerances – The result is acceptable if it falls within the range specified by the tolerance.
    • Control Limits – The process is in control if the result falls within the control limits.
  • Quality Concepts
    • Customer Satisfaction – Satisfaction is achieved through understanding, evaluating, defining, and managing expectations.
    • Continuous Improvement – The PDCA cycle is the basis for quality improvement; quality initiatives should improve the quality of the project’s management as well as the quality of the project’s product.
    • Prevention Over Inspection – Quality should be built into the products, not inspected in; prevention is proactive versus inspection which is reactive.
    • Mutually Beneficial Partnership with Suppliers – Managing the relationship with the focus on long-term relationships versus short term gains.
    • Management Responsibility – Quality requires the participation of all team members, but it is management’s responsibility to provide the appropriate tools required to deliver quality.
  • Quality Tools
    • Ishikawa / Fishbone / Cause & Effect: The problem statement at the head of the fishbone is the starting point to trace the source of the problem back to its root cause.
    • Control Chart: Plots quality results in terms of control limits to determine stability; upper and lower specification limits reflect the maximum and minimum values allowed.
    • Flowchart: Maps a process, showing activities, decision points, etc, in order to help the team anticipate quality problems and where they may occur.
    • Histogram: Bar chart that shows a distribution of variables, where the height of the bar represents the frequency of occurring.
    • Affinity Diagram: Organizes potential causes of defects into groups showing areas that should be prioritized
    • Scatter Diagram / Correlation Chart: Shows the pattern of relationship between two variables. Uses a regression line to explain or predict how the change in an independent variable will change a dependent variable.