Casco Development > ShopVue Blog > Detecting Bottlenecks by High Activity
Detecting Bottlenecks by High Activity 

By Morgan Witthoft, Senior Consultant, Casco Development

In the last article, we imagined a factory producing 9,000 widgets in a month. During that month (and here we've simplified your factory to some sort of utopian frictionless single-flow model), all the workpoints produced 9,000 pieces; but some workpoints spent hours waiting in frustration while the bottleneck ran constantly just to keep up.

This leads to your first metric: look for very active workpoints.

The bottleneck might be the workpoint that appears to be active a high percent of the time.

The computation is:

                (direct hours) div (scheduled hours minus downtime)

For example,

  • Scheduled hours = 80 (two shifts Mon-Fri)
  • Downtime = 6h (some time on maintenance and mechanical failures)
  • Remaining time = 74h
  • Setup plus run (machine hours) = 73.9h
  • Whenever the workpoint can be busy, it is.

Notice this is not the same as OEE utilization, because it does not distinguish planned versus unplanned downtime.

Like OEE, you should measure over several date ranges to look for a consistent pattern.

Also notice the data you need:

  • How many shifts is each workpoint scheduled active in a week?
  • When is the workpoint down (unable to function) as opposed to merely quiet (idle)?
  • How many machine hours (not labor hours) on setup and run?

Reasons why you can't confidently conclude that you've found the bottleneck include:

  • Some machines are well-utilized due to intentionally producing excess product to stock,
  • Percent of downtime varies over time. The machine having the most problems this particular week could temporarily appear to be the bottleneck
  • The real bottleneck might be a workpoint that you have erroneously understaffed. It sits in unnecessary idle time, delaying the whole factory; but this metric treats idle time as evidence that a workpoint is not a bottleneck.