Skip to main content
Quality Control Plans in Lean Management, Six Sigma, Continuous improvement Introduction

Quality Control Plans in Lean Management, Six Sigma, Continuous improvement Introduction

$249.00
How you learn:
Self-paced • Lifetime updates
Who trusts this:
Trusted by professionals in 160+ countries
Your guarantee:
30-day money-back guarantee — no questions asked
When you get access:
Course access is prepared after purchase and delivered via email
Toolkit Included:
Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
Adding to cart… The item has been added

This curriculum spans the design, deployment, and governance of quality control plans across complex production environments, comparable to multi-phase continuous improvement programs that integrate statistical methods, mistake-proofing, and cross-functional alignment in regulated manufacturing settings.

Module 1: Foundations of Quality Control in Lean and Six Sigma Systems

  • Selecting appropriate quality control methodologies based on process stability, data availability, and organizational maturity
  • Integrating quality control plans (QCPs) into existing Lean value stream maps without disrupting flow
  • Defining critical-to-quality (CTQ) characteristics in collaboration with cross-functional stakeholders
  • Aligning QCP scope with Six Sigma project charters and operational boundaries
  • Establishing baseline process capability (Cp/Cpk) before implementing control mechanisms
  • Documenting process inputs, outputs, and control points using standardized templates for audit readiness

Module 2: Designing Process-Specific Control Plans

  • Mapping control methods (e.g., SPC, poka-yoke, checklists) to specific process steps in high-variability operations
  • Determining inspection frequency based on historical defect rates and cost of failure
  • Specifying measurement systems and gage R&R requirements for each control point
  • Assigning ownership of control activities to defined roles (e.g., operator, supervisor, quality engineer)
  • Integrating reaction plans for out-of-control conditions into standard work instructions
  • Designing visual control displays that support real-time decision-making on the shop floor

Module 3: Statistical Process Control Implementation

  • Selecting appropriate control chart types (X-bar R, I-MR, p, u, etc.) based on data type and subgrouping strategy
  • Establishing rational subgroups to ensure meaningful process variation analysis
  • Setting control limits using initial process data and revising after confirmed process shifts
  • Training operators to interpret control charts and initiate containment actions
  • Integrating SPC data collection into MES or paper-based shop floor systems
  • Managing false alarms by distinguishing between common cause and special cause variation

Module 4: Mistake-Proofing and Error Detection Systems

  • Conducting failure mode and effects analysis (FMEA) to prioritize poka-yoke implementation
  • Selecting between contact, fixed-value, and motion-sequence methods based on error type
  • Validating poka-yoke effectiveness through controlled failure testing
  • Integrating sensor-based error detection with automated process shutdown mechanisms
  • Assessing cost-benefit trade-offs of automated vs. manual mistake-proofing solutions
  • Maintaining poka-yoke devices as part of preventive maintenance schedules

Module 5: Integration with Lean Production Systems

  • Aligning inspection frequency with takt time to avoid bottlenecks in pull systems
  • Embedding quality checks into standardized work sequences without increasing cycle time
  • Linking andon signals to control plan violations for immediate escalation
  • Using 5S standards to maintain measurement equipment calibration and accessibility
  • Coordinating in-process checks with kanban withdrawal points
  • Adjusting control plans during line re-balancing or model changeovers

Module 6: Data Management and Control Plan Maintenance

  • Establishing data retention policies for SPC records to support root cause analysis
  • Updating control plans following process changes, engineering revisions, or tooling replacements
  • Conducting periodic audits of control plan execution versus documented procedures
  • Managing version control and change logs for control plan documents
  • Linking control plan data to enterprise quality management systems (QMS)
  • Automating data collection where manual entry introduces risk of inaccuracies

Module 7: Governance, Compliance, and Cross-Functional Alignment

  • Defining escalation paths for recurring non-conformances identified in control plans
  • Aligning internal control plans with customer-specific requirements (e.g., AIAG, IATF 16949)
  • Coordinating control plan reviews during APQP phase gates
  • Resolving conflicts between production throughput goals and quality control demands
  • Training supervisors to audit control plan adherence during gemba walks
  • Integrating control plan metrics into management review dashboards

Module 8: Advanced Control Strategies and System Optimization

  • Implementing automated SPC with real-time data feeds from PLCs or SCADA systems
  • Using predictive analytics to anticipate process shifts before control limits are breached
  • Applying multivariate control charts for interdependent process parameters
  • Optimizing sampling plans using sequential or adaptive sampling techniques
  • Linking control plan outcomes to OEE calculations and loss analysis
  • Scaling control strategies across multiple sites while maintaining consistency and local adaptability
!