This part translates the behavioral and supervisory concepts from Courses A through F into macro-level technical frameworks, bridging the human elements of communication, time management, and problem-solving with advanced, digitized, and synchronized shop-floor architecture.
- Synchronized Flow Architecture & Advanced Value Stream Mapping (VSM)
- 1.1 Macro-Level Value Stream Mapping (VSM): Expanding beyond basic time-motion audits (Course D) to map end-to-end plant material and information flows, identifying global bottlenecks, and calculating total lead time versus processing time.
- 1.2 Heijunka (Production Leveling): Implementing volume and mix leveling to absorb demand volatility, preventing the shift surges and line fatigue addressed in Courses C and D.
- 1.3 Supermarket Design and Pull System Control: Establishing kanban loops, minimum-maximum stock thresholds, and internal pull signals to replace rigid push-based production schedules.
- Integrated Total Productive Maintenance (TPM) & OEE Maximization
- 2.1 Autonomous Maintenance (Jizen Hozen): Institutionalizing operator-led cleaning, lubrication, inspection, and tightening (CLIT) to eliminate the root causes of micro-stoppages analyzed via analytical tools (Course E).
- 2.2 Planned Maintenance & Reliability Engineering: Integrating scheduled interventions, predictive vibration analysis, and thermography with shop-floor execution to drive Overall Equipment Effectiveness (OEE) toward world-class benchmarks (greater than 85%).
- 2.3 MTBF and MTTR Reduction Methodologies: Applying structured engineering diagnostics to minimize Mean Time Between Failures (MTBF) and shorten Mean Time To Repair (MTTR) during unexpected line interruptions.
- Digitized Shop Floors & Industrie 4.0 Integration
- 3.1 Smart Andon and Real-Time IoT Tracking: Upgrading visual management boards (Courses A and C) to automated, sensor-driven digital dashboards that instantly broadcast downtime codes, cycle status, and quality alerts.
- 3.2 Cyber-Physical Systems on the Assembly Line: Deploying collaborative robots (cobots), automated guided vehicles (AGVs), and pick-to-light systems while maintaining operator oversight and safety compliance.
- 3.3 Advanced Data Analytics for Predictive Quality: Leveraging machine learning models on shop-floor historical data to detect variation trends before process limits are breached (expanding on Course E’s process capability module).
- Enterprise-Wide Quality Assurance & Zero-Defect Strategies
- 4.1 Advanced Product Quality Planning (APQP) & PPAP: Aligning frontline execution with design-stage controls, Failure Mode and Effects Analysis (FMEA), and Production Part Approval Processes.
- 4.2 Advanced Poka-Yoke Architecture: Designing fail-safe hardware and software interlocks that completely eliminate human error across complex multi-tasking workflows (Course C).
- 4.3 Statistical Process Control (SPC) in High-Speed Environments: Training supervisors to interpret X-bar and R charts, distinguish between common-cause and special-cause variations, and enforce immediate containment actions.
- Submissions & Assessment
- 5.1 Practical Submissions: Complete Current-State and Future-State Value Stream Maps, an Autonomous Maintenance Autonomous Audit Sheet, and a Digital Andon Deployment Proposal.
- 5.2 Online Theory Examination: Scenario-based questions covering OEE calculations, Heijunka balancing, and Industrie 4.0 data interpretation norms.
- 5.3 Practical Viva / OJT Evaluation: Live plant defense of a proposed TPM countermeasure and demonstration of statistical process control chart interpretation on the shop floor.
