Course Code: SCM303
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Synopsis

The manufacturing and operations function in supply chain management (SCM) ensures that intermediate and finished goods and services are market-ready to meet planned or actual demand. SCM303 Quality Management and Improvement examines quality management (QM) principles, methods, and tools to enhance quality in manufacturing and service industries. Students will gain insights into the approaches that drive quality management, such as the Gap Model, ISO 9000, Six Sigma, Seven QC Tools, and Kaizen. The course focuses on quality control (QC) practices such as Statistical Process Control, control charts and process capability indices. Learners will apply Lean and Lean Six Sigma approaches, Just-in-Time systems and Kanban to eliminate waste and improve efficiency. Additionally, the course examines the use of data analytics to drive quality improvement and emerging trends that are shaping the future of quality management. By combining theory with practical applications, students will be well-equipped to implement quality initiatives that drive continuous improvement across various industries.
Level: 3
Presentation Pattern: EVERY JAN

Topics

  • Quality Management (QM) in Practice
  • QM Concepts and Philosophies
  • The Gap Model, ISO 9000, and Six Sigma
  • The Seven QC Tools, Kaizen, and Breakthrough Improvement
  • Quality Control (QC) in Practice
  • QC Systems, Variation and Statistical Process Control
  • Constructing and Interpreting Control Charts
  • Process Capability and Process Capability Indexes
  • Lean and Lean Six Sigma Approaches
  • Just-in-Time Systems and Kanban
  • Data Analytics for Quality Management and Improvement
  • Emerging Trends in Quality Management and Improvement

Learning Outcome

  • Show how quality management concepts and philosophies are applied in practice to ensure and enhance quality in manufacturing and service industries.
  • Propose strategies for process optimisation using Lean and Lean Six Sigma approaches to reduce waste and improve efficiency.
  • Examine how data analytics systems can be integrated into the manufacturing and service environment to monitor, control, and improve processes.
  • Appraise Statistical Process Control charts to ensure consistency in operational processes.
  • Inspect process capability indexes to determine how well the processes meet quality specifications.
  • Demonstrate how big data analytics can be applied to identify trends, predict failures, and make informed decisions for continuous improvement.