Use OEE and Efficiency to Drive Improvement in Manufacturing

Executive Guide – Everything from getting the calculations right to improvement strategy.

Using OEE or Efficiency to drive improvement has a genuine bottom-line benefit, if implemented correctly.

It is essential that it is driven from the top to succeed. If it is deemed “just a manufacturing thing”, it will fail. As such, it is important for the MD or CEO to understand the whole process so they can support the team in making it happen. This guide covers it all, from calculations to strategy.

A 10% to 40% improvement in efficiency is a genuinely achievable target in just a few months and will translate to a 6 or 7 figure bottom-line benefit.

Let’s get started with the calculations…

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Calculating OEE and Efficiency - UK

The Difference between OEE and Efficiency

In a nutshell, there is very little difference between calculating OEE and Efficiency. The only difference is the way in which it is broken down. The final number is mathematically the same. Here is the proof:

Efficiency = Good Ouput / (Planned Time x Maximum Speed)

OEE = Availability x Quality x Performance

Which look very different of course. But when you substitute the full calculations for AQP, you get:

Availability = (Planned Time – Downtime – Changeovers) / Planned Time

Quality = Good Output / (Good Output + Waste)

Performance = (Good Output + Waste) / Maximum Speed x (Planned Time – Downtime – Changeovers) 

When multiplied out in OEE, the highlighted terms cancel out, leaving:

OEE = Good Ouput / (Planned Time x Maximum Speed)

Which is precisely the same as Efficiency. If you prefer to use OEE rather than Efficiency, you can use this to help validate your calculations. When building your OEE management system, it is an effective way to validate inputs and isolate data errors.

Availability, Quality and Performance
What is the point?

The whole point of OEE is that you go and do something about it. You want it to direct you to the biggest improvement opportunities (see Improvement Cycles in part 2).

If you measure your processes and get an OEE of 60% it is of little value alone. You need to break the number down and OEE achieves that with AQP. Imagine then your AQP is:

Availability = 70%
Quality = 95%
Performance = 90%

Availability is therefore the issue on this basis. But this is not enough.

You need to find out why availability is low. It is therefore necessary to capture downtime and changeover losses then go and fix the top issues.

Why not just cut to the chase and capture those losses in the first place? AQP add no real value in most cases. In fact, in some ways, they can be obstructive.

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Database Calculating OEE KPI - UK

How OEE can Mis-Direct

In the example above Availability as a whole, may be the biggest issue. The top three of your biggest issue may be a tempting improvement target. But it is often the case that the biggest single issue in Quality or Performance may outweigh many top issues in Availability (what we describe a ‘flat pareto’). For example, your biggest availability loss may be a type of changeover accounting for 2% of OEE loss.

You may never eliminate the changeover as they usually have to take some time. After weeks of work, operator engagement, some machine mods, you may get 1% back (see part 2, which explains why downtime and changeover loss recovery is often mis-calculated). What if your biggest issue in Performance is a speed loss of 10%? What if that loss is caused by a single easy to fix problem? 10x the impact in a fraction of the time.

The initial direction of Availability did not help as the losses at the next level down still need consideration.

Inclusion

Efficiency measurement is normally underpinning some sort of improvement programme. The most successful of which include a wide range of team members from all around the business. The maths of OEE is not particularly hard, but remember some people find any maths hard. Therefore, introducing anything unnecessarily complex will create a barrier to inclusion and ultimately resistance to change.

Unless you have very good reason, AQP can just be an unnecessary layer of complication.
Straight Efficiency and gap analysis are often more effective.

Get Part 2 of this Article

Included in the second part of this article:

How Loss Recovery is Often Mis-calculated

The Impact of Material Loss on OEE, Efficiency and Yield

Tips for using Efficiency to drive improvement

How to implement Improvement Cycles

Applying Lean to the Improvement Cycle (apply Lean to Lean)

OEE and Efficiency – Step by Step Implementation Plan

The Essentials of an Efficiency Management System

And, “Seriously, you are not going to do this on spreadsheets”

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