Getting the best performance out of an automated packaging line is a difficult task. It is made up of a series of independent machines that each perform a different function such as filling, labeling, packing, etc. The machines are linked together by an overall control system that records the states of each machine (ie. waiting, functioning or malfunctioning) and sets their speeds. Being in series, these machines are vulnerable to the “weakest link” phenomenom. If one goes down, they all go down.

Remember that game show the Weakest Link?

The first step in maximizing your throughput is identifying your constraint, or bottleneck. Take the efficiency of each machine and multiply it by its maximum rate. This will give you the net rate of each machine. The machine with the lowest net rate is your constraint and your goal should to keep it running as fast and as often as possible.

Example:
A simple packaging line: (ppm = products per minute)

Some interesting notes:

• Each machine runs 92% or higher, but the line net efficiency is only 83.9%. This is because downtime on just one machine shuts down the whole line (ie. if the Casepacker jams, the Filler and the Labeler also shut down). The net efficiency of the line is calculated by multiplying the efficiencies of each machine in sequence:
  0.94 * 0.97 * 0.92 = 0.839 = 83.9%
• To get the overall line speed, multiply the net efficiency by the max rate of the slowest machine: 0.839 * 200 = 167.7 ppm
• The machine with the lowest net rate is the labeler (194 ppm), making it the constraint. 194 ppm is the upper limit of what we can achieve on this line.

So how do you achieve the upper limit of 194 products per minute? By making sure downtime on the Filler and Casepacker don’t ever cause the Labeler to shut down. By adding an accumulation table in between the Filler and the Labeler, you are segregating the line into two separate systems. This breaks the compounding effect of the machine efficiencies.

Since the line is now in two sections, we have to calculate their throughput separately. The throughput of the first section is 282ppm (0.94 * 300 ppm = 282 ppm). The throughput of the second section is 178.5 ppm (0.97 * 0.92 * 200 ppm = 178.5 ppm). We are still limited by the bottleneck of the second section, so the throughput of this line is 178.5 ppm, a 6.4% increase over our previous line.

Since we haven’t reach our upper limit of 194 ppm we should add another buffer between the Labeler and the Casepacker.

Now we’ve broken the line into three sections with each machine running independently. We have no compounding of efficiencies, so all we have to do is pick the lowest net rate of the machines. In this case, the Labeler’s net rate is 194 ppm and this is throughput of the line, a 15.7% increase over our original throughput of 167.7 ppm.

What does 15.7% mean to a company’s bottom line?

If you are having trouble meeting market demand for a product it could be huge.
Let’s say the line is running:
2, 8 hour shifts per day
7 days a week
Profit is a conservative 50 cents per product

2 shifts * 8 hours * 60 minutes / hour * $0.50 cents * 26.3 extra products per minute = $12,624.00 per day in additional revenue

Over six months it generates $2,203,880.00

Tags: accumulation, line analysis, packaging, production, throughput

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