Quality Control and Management Overview

Quality Control and Management

• Quality control and management involves people, processes, and improvement.
• A key quote from William Cooper Procter (1887) highlights the importance of quality merchandise, efficient production, and economic profitability.
• Modern quality activities include product design assurance, procurement quality assurance, and product quality audits.
• Key elements of quality include proper design, high-quality raw materials, and organizational involvement in the product.

Modern Importance of Quality

• Quality is important for productivity (efficiency), cost of operations (economical production), and satisfying customers.
• Building quality into an organization is critical but challenging, including infrastructure.

Evolution of Quality

• Quality is not a recent invention, dating back to ancient civilizations.
• Ancient Egyptian, Greek, and Roman civilizations produced high-quality products and infrastructure.
• The Industrial Revolution saw mass production and division of labor, leading to separate quality control departments and implementing benchmarking.

How Evolution in Other Areas Affected Quality Today

• This topic shows the interconnectedness of various fields influencing quality (statistical quality control, business process reengineering, total quality management and lean, Six Sigma, Toyota Production System, Just-in-Time (JIT), Ford Production System, information technology - e.g. MRP, ERP, CRM, & supply chain).

Quality Today

• Today's quality activities encompass numerous processes beyond just product quality (design assurance, procurement quality, audits).
• Emphasis on proper product design, quality raw materials, and organizational involvement is crucial for high-quality products.
• Development of industry-wide standards is a current focus.

From Product Quality to TQM

• Quality Assurance focuses on the technical aspects of products, using statistical measurement, and problem-solving methods.
• Total Quality Management (TQM) is a comprehensive approach to quality including long-term customer relationships, employee training, and leadership.
• TQM seeks to integrate quality principles into organizational processes and management systems.

Defining Quality

• Defining quality can involve perfection, fast delivery, product usability, consistency, waste elimination, customer delight, total customer satisfaction, and compliance with standards.

Formal Definitions of Quality

• Quality can be defined through various lenses (transcendent, product-based, user-based, value-based, manufacturing-based). These encompass aspects like excellence, product attributes, fitness for use, quality versus price, and conformance to specifications.

Leaders in the Quality Revolution

• Key individuals in the quality movement include W. Edwards Deming, Joseph M. Juran, Philip B. Crosby, Armand V. Feigenbaum, Kaoru Ishikawa, and Genichi Taguchi.

Deming Cycle

• The Deming cycle ("Plan-Do-Check-Act") is a continuous improvement framework for understanding and addressing problems including standardizing, evaluating corrective actions, and improving systemic root causes.

Deming's System of Profound Knowledge

• Deming emphasized the importance of understanding systems, variations, knowledge theories, and psychology in improving quality.

Systems

• Analyzing organizational processes as interconnected systems is crucial, highlighting cross-functional parts, purpose, and overall optimization.

Variation

• Variation is inherent in natural processes and is not readily controllable.
• Excessive variation in processes results in product failures, unhappy customers, and high costs. Statistical methods help understand and minimize variation to improve results.

Sources of Variation in Production Processes

• Variation may arise through various factors within the process (materials, operators, methods, measurement instruments, tools, machines, environments, and human inspection). Defining variation's origins aids in addressing them effectively along with process inputs & outputs.

Common and Special Causes of Variation

• Understanding the difference between common and special causes of variation helps diagnose problems and adjust processes.

Importance of Understanding Variation

• Variation management aids in identifying predictable and unpredictable aspects of processes and ensures consistency.

Theory of Knowledge

• Knowledge requires theory to provide cause-and-effect relationships and to enable prediction. Practical experience alone does not explain theories.

Psychology

• Motivating employees intrinsically is crucial for quality improvement; fear demotivates people.
• Management should nurture a work environment that fosters workers' pride and enjoyment of their work.

Juran's Quality Definition

• Juran defines quality as "fitness for use," viewed from both internal and external perspectives (product performance linked to customer satisfaction, and absence of defects for customer peace of mind).

Juran's Quality Trilogy

• Juran introduced a universal framework for quality improvement—"the Quality Trilogy" (quality planning, quality control, quality improvement).

Philip B. Crosby

• Crosby's principle emphasizes that "quality is free," meaning the real cost lies in "unquality"—nonconformance to stated requirements, rather than inherent costs in quality.

Philip B. Crosby - Four Absolutes of Quality Management

• Crosby's four absolutes for managing quality: defining quality as conformance to requirements, adopting a prevention-based system, establishing zero defects as the standard, and measuring quality by costs.

Statistical Process Control (SPC)

• Statistical Process Control (SPC) is a methodology for monitoring processes, identifying special causes of variation, and signaling the need for corrective action.

Statistical Process Control (SPC) - Tools

• SPC utilizes several tools such as control charts, histograms, Pareto diagrams, cause-and-effect diagrams, check sheets, process flow diagrams, and scatter diagrams to find defects and their causes.

Control Charts

• Control charts are graphical tools in SPC for showing process performance over time compared against upper and lower control limits for quality characteristic (e.g. variations in process over time).

Histogram

• Histograms visually display data distribution, subdividing a characteristic into classes or bins. The y-axis represents the number of observations in each bin.

Pareto Diagram

• Pareto diagrams represent data on the frequency of occurrence of defects to prioritize efforts according to their frequency of occurrence.

Cause-and-Effect Diagram

• Cause-and-effect diagrams trace potential causes of defects to the primary source.

Check Sheets

• Check sheets track quality issues and provide a record of problem frequency.

Process Flow Diagram

• Process flow diagrams map a process's steps from start to finish.

Scatter Diagram

• Scatter diagrams illustrate correlations between two variables.