You don’t need to spend five figures on a consultancy to find out that your glass tempering line has a lag between stages, or that your loading dock backs up every Tuesday. Time studies are a powerful tool for pinpointing inefficiencies, and they can be done in-house—if you follow the right process.
Start with a clear objective. Are you measuring labor utilization? Machine cycle times? Wait times between material movement? Narrow your scope to one line or work cell—like your glass lamination area or cutting station for acrylic sheets.
Next, define each task within the process. Break them down to the smallest repeatable unit: loading raw material, adjusting feed rate, activating the cutting cycle, quality check, offloading, etc. Each step should be observable and consistent across shifts.
Now, grab a timer and track these tasks in real-time. Ideally, have a supervisor or engineer conduct this so the operator can perform normally. For instance, in a plant shaping float glass panels, you might find that setting up the cutting table takes 90 seconds on average—but spikes to 3 minutes when templates aren’t organized. That’s your bottleneck.
Be sure to capture both manual and machine cycles. Just because a robotic loader runs “automatically” doesn’t mean it’s efficient—look at lag time, misfeeds, and the time operators spend restarting sequences.
After data collection, convert those time metrics into percentages of total task time. This allows you to visualize what portion of the shift is spent on value-added tasks versus idle time, rework, or walking.
Use a Pareto analysis to prioritize fixes. Maybe 80% of downtime on your slitting line stems from 20% of process steps—like material staging or roll changeovers. Now you know where to target lean improvements or retraining.
And don’t just run the study once. Set a recurring cycle—quarterly or semiannually. Every time you bring in new equipment, materials, or shift patterns, the baseline shifts. The more you time your processes, the more control you gain over them.
