Playbook

OEE Diagnosis Flow: From Data to Operator-Led Experiments (Interactive Playbook)

An interactive, operator-centred playbook that guides teams from reliable baseline OEE measurement through quick root-cause checks, a one-week experiment planner, results capture, and standardization or escalation steps.

Interactive Tool

OEE Diagnosis Flow: Interactive Experiment Planner

Turn OEE numbers into rapid, local experiments that produce measurable gains

This interactive playbook helps supervisors and CI leaders move from baseline OEE measurements to short operator-led experiments that target the top losses. Use it on the shop floor with operators to confirm root causes, plan a clear 1-week test, measure outcomes, and either standardize the fix or escalate to engineering. The form captures the experiment plan and results so your team can build a living improvement record.

Quick tips: collect 30 days of data for a reliable baseline; focus on the top 3 losses; keep experiments simple and measurable; give a single owner responsibility for each run.

Enter availability percentage for the last 30 days (0-100). Use plant OEE/SCADA/MES or manual logs. Required for baseline comparison.
Enter performance (speed) percentage for the last 30 days.
Enter quality (good parts / total parts) percentage for the last 30 days.
Enter the overall OEE percentage for the last 30 days (or let the system calculate from availability/performance/quality).
Choose the loss categories that account for the majority of the OEE gap. This guides the experiment focus.
If you chose 'Other,' briefly describe the loss type.
Summarize what operators observed during quick checks or 5-why discussions (keep it short — facts, not long narratives). Include who was consulted and one-line findings.
State a concise hypothesis: what you will change, why, and the expected measurable effect (e.g., reduce minor stops by 50% and increase OEE by 3%).
Person accountable for running the experiment and reporting results.
Use YYYY-MM-DD. For quick experiments, aim for immediate start or within 48 hours.
Typical quick test = 3–7 days. Enter a whole number.
Be specific: which metric(s), data source (operator log, OEE system, stopwatch), sampling frequency, and acceptance criteria. Example: 'Log number of minor stops per shift, collect machine-logged run time hourly.'
Clear, numeric thresholds or qualitative pass/fail criteria the team agrees on before starting.
Enter the change in overall OEE (positive for improvement, negative if it worsened). Leave blank until after the run.
Summarize what happened during the run: unexpected complications, operator feedback, secondary benefits, or new issues discovered.
If the experiment met success criteria, describe how the change will be standardized (updated standard work, training, materials, visual aids). Include owner and implementation timeline.
Choose 'Yes' if the fix requires engineering changes, spare parts, or significant capital resources.
Capture required actions, estimated resources, and who to contact in engineering/maintenance.
Capture what you learned, what to try next, and any suggested adjustments to the experiment approach.
Optional: list IDs or links to photos, run charts, or documents saved to your system.
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