I’m often surprised how much time up front is spent talking about the nuts and bolts and specifications of the equipment being purchased, and how little time is spent really defining what success looks like.  The equipment (automation, robots, PLC’s, conveyors, whatever) are all just means to achieve a business outcome.  At the end of the day, what you really care about are reduced production costs, higher product quality, or greater production capacity.

That is what should be measured, that is what an integrator should be held accountable to.  Define the contract such that the integrator needs to deliver this – regardless of the bits and bytes of what they put into it.  If they missed or under estimated something – it’s their responsibility to do what needs to be done to achieve the business outcome that was agreed upon – period.

OEE (Overall Equipment Effectiveness) is a quantitative method used measure performance and takes into account the three major things in an automation system #1 How fast does it run, #2 The system uptime, and #3 The product quality coming out of it.

Here’s how you calculate it.

OEE = Performance Efficiency * Availability * Yield

Performance Efficiency = How fast does it run

Example – the system is designed to run 100 pieces per minute, the final system as it is installed runs 98 pieces per minute.

PE = 98 ppm/100 ppm * 100% = 98%

Availability = How much time the system runs of the total available time (uptime)

Example – In a week’s worth of production, over 2 shifts (4800 available minutes), the system has 5 minutes of downtime and 20 minutes of changeover.

Availability = (4800 minutes – 5 minutes – 40 minutes) /4800 minutes * 100 % = 99.06%

Yield = Percentage of good widgets made (quality)

Example – 2 defective pieces out of 1000 pieces made

Yield = (1000 pieces – 2 pieces)/1000 pieces * 100% = 99.8%

OEE = PE * Availability * Yield

OEE = 98% * 99.06% * 99.8% = 96.9%

Figure this out up front.  Work with the integrator to agree on what this number needs to be.  Agree on the inputs that are required to achieve this (i.e. the system needs to have good product going into it, if it is going to have good product coming out).   Spending the extra time up front to define and agree on this metric will ensure you get what you really want at the end of the project.

In some upcoming blog posts, I’ll walk through some examples of how to put this together.