This curriculum spans the technical and organisational challenges typical of a multi-workshop operational improvement program, covering the same scope of work involved in scoping production analyses, aligning stakeholders, integrating heterogeneous data systems, and establishing sustained monitoring practices across complex manufacturing environments.
Module 1: Defining System Boundaries and Scope
- Selecting which operational units to include in the analysis based on throughput dependency and data availability.
- Deciding whether to include supplier and customer interfaces when assessing production bottlenecks.
- Resolving conflicts between plant managers over cross-facility process ownership during scoping sessions.
- Determining cutoff points for batch processing lines where semi-finished goods transition between departments.
- Documenting exceptions for legacy equipment excluded from digital monitoring systems.
- Establishing escalation paths when stakeholders dispute the inclusion of support functions like maintenance and QA.
Module 2: Data Collection and Instrumentation Audit
- Mapping existing PLC and SCADA tags to production events for time-stamped activity logging.
- Identifying manual data entry points that introduce latency or inaccuracies in cycle time records.
- Assessing sensor calibration schedules to determine data reliability for OEE calculations.
- Integrating handheld barcode scans with automated machine data to reconcile downtime codes.
- Deciding whether to retrofit older machines with IoT sensors based on ROI and downtime frequency.
- Validating shift handover logs against automated system timestamps to detect reporting gaps.
Module 3: Process Mapping and Value Stream Validation
- Conducting Gemba walks to verify as-is process maps against actual operator workflows.
- Reconciling ERP-defined routings with observed workarounds on the production floor.
- Identifying non-standard material handling paths that bypass planned conveyance systems.
- Documenting rework loops that are not reflected in official process documentation.
- Adjusting value stream boundaries when shared equipment serves multiple product families.
- Resolving discrepancies between engineering process diagrams and maintenance team schematics.
Module 4: Performance Metric Selection and Baseline Establishment
- Choosing between cycle time, takt time, and lead time as the primary throughput indicator.
- Defining what constitutes planned versus unplanned downtime for OEE reporting.
- Setting thresholds for minor stops that are excluded from formal downtime tracking.
- Normalizing performance metrics across shifts with differing operator experience levels.
- Deciding whether to include changeover time in availability or treat it as a separate metric.
- Establishing baseline periods that exclude known anomalies like equipment trials or safety audits.
Module 5: Bottleneck Identification and Constraint Analysis
- Using buffer accumulation patterns to identify hidden constraints upstream of apparent bottlenecks.
- Distinguishing between chronic bottlenecks and temporary capacity shortages due to maintenance.
- Assessing whether a bottleneck shifts based on product mix and scheduling patterns.
- Validating constraint locations using both machine utilization data and WIP inventory levels.
- Deciding when to accept a bottleneck as fixed due to capital constraints or design limitations.
- Coordinating with maintenance teams to determine if recurring faults at a station are root causes or symptoms.
Module 6: Change Management and Stakeholder Alignment
- Presenting efficiency findings in operational terms to floor supervisors rather than financial metrics.
- Addressing resistance when data reveals underperformance in high-tenure teams or departments.
- Coordinating with union representatives when process changes affect job classifications or staffing levels.
- Managing conflicting priorities between production volume targets and quality improvement initiatives.
- Documenting informal practices that contradict official procedures but maintain output stability.
- Scheduling intervention rollouts during planned shutdowns to minimize disruption to delivery commitments.
Module 7: Continuous Monitoring and Feedback Loop Design
- Selecting dashboard refresh intervals that balance real-time visibility with system load.
- Defining alert thresholds for performance deviations that trigger corrective actions.
- Integrating operator feedback forms into digital monitoring systems for anomaly reporting.
- Assigning ownership for weekly review of efficiency trends across production cells.
- Updating baseline metrics after process improvements to prevent false anomaly detection.
- Archiving historical states of process maps and metrics to support root cause analysis of regressions.
Module 8: Technology Integration and Scalability Planning
- Evaluating whether to use edge computing devices for preprocessing machine data before cloud upload.
- Designing API contracts between MES, ERP, and analytics platforms for consistent data flow.
- Standardizing data formats across facilities with different automation vendors and vintages.
- Planning phased deployment of analytics tools to prioritize high-impact production lines.
- Implementing role-based access controls for production data across operations, engineering, and finance.
- Assessing data retention policies for raw sensor logs versus aggregated performance reports.
