This document discusses how to calculate Overall Equipment Effectiveness (OEE) and factors like set-up time, utilization, efficiency, and first-pass yield. It recommends measuring set-up times separately to better understand their impact on machine throughput. An example calculation shows an OEE of 59% based on 75% utilization, 90% efficiency, and 88% first-pass yield. It outlines collecting OEE data by machine to identify improvement opportunities, educating operators, and holding supervisors accountable for addressing issues to improve effective use of resources.

1. ASKTHE EXPERT:
LEAN LEADERSHIP - CAN WE
TALK ABOUT OEE?
By Larry Fast

2. •Question: How should set-up time be factored
into the OEE calculation?
•Answer: Overall Equipment Effectiveness (OEE) is
a powerful metric used to improve the effective
use of resources, by machine. Here’s the
formula: OEE = Machine Utilization x Efficiency x
First-PassYield

3. • Utilization (hours of actual machine uptime ÷ scheduled hours):Typically, the biggest reductions to
utilization are due to set-ups and maintenance downtime. To reduce the impact of set-up times on
machine throughput, you must measure and report the time spent on set-ups as a discrete measure for
each machine. You can do the same for time spent on PMs. Data should be collected so that accounting
can calculate the variance, +/- the standard. Importantly, from a capacity standpoint it doesn’t matter on a
constraint—it’s still lost production time. Focus on why machines are down regardless of whether it’s
planned or unplanned. That will identify where the biggest opportunities lie so you can do a kaizen blitz on
the right machines. Always work on the constraint work centers first! Let’s assume the utilization for the
machine is 75% in a 120-hour week, i.e., 40 hours times 3 shifts x .75 = 90. That means the machine is
available for production 90 hours a week. Lots of opportunity to improve throughput.
• Efficiency (some call it Performance) (actual machine speed ÷ rated/standard machine speed) If the
machine runs at 10% less than rated speed then the efficiency is just 90%; 90 hours x .90 = 81 hours.
• First PassYield (% ofWIP that flows through the process uninterrupted, i.e. no rework or scrap). First pass
yield is the quality metric and is 100%, minus material interrupted in process such as rejections/rework and
scrappedWIP. Let’s assume FPY is 88%. Note: I strongly recommend the use of the RTY (rolled
throughput yield) as the much more accurate measure. [See my November 2016 article regarding rolled
throughput yield vs. FPY.] Typical FPY numbers I regularly see are in the high 80s/low 90s and always
overstate reality. Typical RTY numbers are in the 60s and 70s and are much more accurate and useful.
Pareto-ize this data and improve the whole process, not just one operation of the process. You’ll get to the
root causes of flow interruptions much more quickly, and the improvement in performance will be much
larger.

4. • Using the above examples, OEE would be .75 x .90 x .88 = 59% OEE.
• Next Steps: Manufacturing/value stream managers should meet with the first line
supervisors, quality manager, accounting and other staff as necessary to develop the plan
of attack. The first thing to do is to start collecting OEE data, by machine, on the
constraint equipment in each value stream or department. If you can get accurate
information out of your current systems, great. Many operations cannot from legacy
systems. If not, collect it manually and get started while challenging the quality manager
to work with the necessary people to create a formal authorized system for use by all. For
the short-term, start with a 24-hour worksheet attached to a clip board at each machine
and ask the operators to mark the page each hour, e.g., green marker for “machine
running at rated speed,” yellow marker for “machine in set-up” or red marker, “machine is
down.”
• Collect these data first thing each morning and record into a spreadsheet. Begin to track
until the data points clearly to where the largest opportunities are. This is where you will
start. It won’t take very long for the worst performing machines to be identified for
action. Then it’s time to simply create the improvement project with bold deliverables,
assign scarce resources and get it done. When the first project is complete go to the next
biggest waste of capacity on the No. 2 constraint in the plant and so on. The leverage on
these opportunities is huge for the bottom line so staff multiple improvement projects if
resources can be made available.

5. • Please be sure when you ask operators for help that you educate them on what you’re going to
do with the information they collect and why it’s important. Be sure and let them know you
also want to collect their insights into the process that go along with the data integration
they’re recording.
• Be sure to hold the first line supervisors accountable for regular follow up on gemba
walks. They can and must respond in real time to machines that are not performing well. My
favorite way to do that is with andon lights at each constraint. Green light means quality, run
speed, all good. Yellow means there are issues with one or more components of OEE and
corrective actions should be in progress. Red means the machine is down. (Red andon lights
should also include an alarm to command immediate attention.)
• Finally, any operator or maintenance person I’ve ever talked to has a much better day when the
machine is running properly than when it is not, so it’s usually easy to get their support. They
are a critical part of the team so make sure they feel that in all interactions -- no finger
pointing.
• And salaried folks: ACT WITH URGENCY and common purpose. A lost machine hour on a
constraint work center is an immediate hit to operating margin and maybe to your best
customer’s order delivery promise.
• “What you do has far greater impact than what you say.” -- Stephen Covey
• “Watch the little things; a small leak will sink a great ship.” -- Benjamin Franklin