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When working with manufacturing teams doing line balancing, I constantly encounter the same mistake. They typically forget to consider OEE (Overall Equipment Effectiveness) when doing their takt time calculations. This mistake could easily lead to missed deliveries and unplanned overtime.

When working with manufacturing teams doing line balancing, I constantly encounter the same mistake. They typically forget to consider OEE (Overall Equipment Effectiveness) when doing their takt time calculations. This mistake could easily lead to missed deliveries and unplanned overtime.

Planned cycle time (PCT) or Target Takt Time (TTT) are commonly used numbers to use as buffer numbers when performing takt time calculations. Some popular lean books provide rough guidelines like 85-90%. So in those scenarios the calculation would look like this:

**Demand = 400 pieces per day**

**Available time per shift = 420 minutes**

**2 shifts per day available**

**Takt Time = Available time / Demand = (2 x 420) / 400 = 2.1 minutes per piece**

**Planned Cycle Time = 85% x 2.1 minutes = 1.79 minutes**

Ok, so we target 1.79 minutes for our line balance right? Well not quite. The 85% Planned Cycle Time rule of thumb fudge factor is only designed to protect you against basic productivity losses. But there are many other things to consider in the calculation like quality losses, machine breakdowns and changeovers. Well, the metric that we already have that many manufacturing sites already measure is OEE. OEE is the product of three factors - quality losses, productivity losses and availability losses. So alternatively, using the same demand and availability profile as before lets consider this example:

**OEE = 75.4%**

**Planned Cycle Time (using OEE) = OEE % x Takt Time**

**Planned Cycle Time (using OEE) = 75.4% x 2.1 minutes = 1.58 minutes.**

Clearly there is a big difference between balancing a line at 2.1 minutes vs 1.79 minutes vs 1.58 minutes!

I did allude to "two big mistakes" in the title of this post. The first one was ignoring OEE - the second one is not working to improve it. Some teams just "accept" that their OEE is what it is instead of actively working to understand and improve the results. Let's look at an example

What if the total cycle time for our example cell is 5.7 minutes meaning from start to finish the total work content to make one piece is 5.7 minutes.

Using the standard manpower formula:

**Manpower = Total work content / Planned Cycle Time = 5.7/1.58 minutes = 3.6 people**

Ok, so clearly we can't do the work with 3 people and we need to staff 4 heads RIGHT? Well wait a minute. We should focus our efforts on improving OEE to drive the optimal line balancing. The first step would be to identify the targets for OEE.

**What OEE would we require for a staffing of 3 people? Lets assume that 8% is an acceptable overtime level.**

**3 people with 8% overtime = 3.24 people (equivalent)**

**3.24 people = 5.7 minutes / (2.1 minutes * X)**

**Solving for X = 83.77%**

What does this mean? It means we need to improve our OEE from

__75.4% to 83.77% in order to achieve a staffing of 3 people with no planned overtime__. Seems like a daunting task but lets breakdown our OEE to see exactly what we are dealing with here. So we take a deeper look into our OEE number and find this:**OEE = Availability % x Quality % x Productivity %**

**Availability = 98%**

**Quality = 81%**

**Productivity = 95%**

**OEE = 75.4%**

Well the number that stands out here is clearly quality so what if we focus only on quality? How much would we have to improve quality to reach our OEE target of 83.77% assuming Availability and Productivity stay the same? Using some basic math:

**83.77% = 98% * X * 95%**

**Solving for X = 90%**

This means

__in order to achieve an OEE of 83.7% (which would allow us to staff with 3 people at 8% overtime) we need to improve our quality from 81% to 90%__. What we have to do now becomes much clearer because of our calculations. In the meantime, while we are making those improvements, the management team needs to consider a containment action. 3.6 people (from the original manpower calculation) is 3 people with 20% overtime. This is challenging but definitely possible - and we have to understand its only a temporary measure. Alternatively the team can use 4 people temporarily - the downside of this is that the operators get use to a standard work with 4 operators as opposed to 3 and it becomes difficult to adjust the work content later. Also, the 4 person standard work carries 0.4 heads worth of waste unless you are able to flex that operator to another line.
To summarize, Productivity and Quality targets are often picked out of thin air but we should be applying a common sense data driven approach. Lean shouldn't be a science project but we do need to use the metrics at our disposal. We need to ask ourselves what future state are we trying to achieve and what improvements do we need to make to achieve that vision.