Does your bagging machine produce at the speed it should?

Quick answer: A bagging machine’s capacity should not be evaluated solely by the number of bags per minute indicated in the technical specifications. The nominal speed represents the machine’s capacity under specific operating conditions. In practice, downtime, adjustments, product variations, losses, and limitations of downstream equipment can significantly reduce the line’s actual productivity.

Therefore, to understand the performance of a bagging operation, it is necessary to look beyond nominal speed and evaluate how much the line actually produces over the course of a shift, day, or month.

Most production engineers know the nominal speed of the bagging machine. The number is listed in the technical specifications, was presented in the proposal, and has often become a reference for the production target.

But there is a more important question:

Of the bags per minute that the bagging machine can produce, how many actually reach the pallet at the end of the line?

This difference between nominal capacity and actual productivity can reveal bottlenecks that go unnoticed during operation.

A bagging machine may operate at high speed, but if bag closing, conveying, product organization, or palletizing cannot keep up with that pace, the machine’s capacity does not necessarily translate into higher production.

Why machine speed is not the same as line productivity

A bagging machine with a nominal capacity of 6 bags per minute can, under ideal conditions, reach this speed. However, this does not mean that the line will deliver 6 bags per minute throughout the entire shift.

Between nominal capacity and actual production, there are several factors that impact the result: micro-stoppages, adjustments, setup time, product changeovers, supply replenishment, variations in product characteristics, packaging losses, and reduced speed during operation.

It is precisely this difference between what the machine could produce and what the line actually delivers that needs to be monitored.

One way to carry out this analysis is through OEE (Overall Equipment Effectiveness). The indicator considers three dimensions:

• Availability: how much of the planned time the line was effectively available for production;
• Performance: how much the line produced compared to its nominal capacity, considering speed losses and minor stoppages;
• Quality: how much of the production resulted in products within the established standards.

The three factors are multiplied, not added.

For example: a line with 90% availability, 90% performance, and 99% quality has an OEE of 80.2%, not 90%.

This calculation helps reveal an important point: even small losses at different stages can have a significant impact on final productivity.

And that is why looking only at the number of bags per minute of the bagging machine may not be enough to understand the actual performance of the operation.

Bags per minute: what determines a bagging machine’s speed?

There is no single ideal speed for all bagging operations. Production pace varies according to product, package weight, bag type, dosing system, and bagging machine configuration.

Therefore, rather than simply looking for a reference number, it is important to understand which factors determine the machine’s capacity and whether it is suited to the operation’s needs.

*Speeds are general references. Actual capacity depends on product characteristics, packaging, machine configuration, and operating conditions.

Weight is only part of the equation

It is natural for a bagging machine to operate at different speeds depending on the bag weight. The greater the weight, the greater the amount of product handled in each cycle, and this can directly influence the pace of the operation.

Products with different characteristics, such as density, particle size, flowability, and behavior during dosing, may also require specific configurations and affect the speed achieved.

The same applies to the packaging. Bag type, closing system, and material characteristics can interfere with the line’s pace.

Therefore, comparing two bagging machines based only on the number of bags per minute can lead to a misleading conclusion.

The best indicator is the application’s capacity

Instead of asking only:

“How many bags per minute does this bagging machine produce?”

The analysis should start with:

“How many bags per minute does this operation need to produce, with the desired weight, product, and quality level?”

From there, it is possible to size the bagging machine and, above all, verify whether the subsequent stages of the line can keep up with this pace.

Because achieving the bagging machine’s nominal speed is only part of the challenge.

The goal is not to have the fastest machine. It is to have a line capable of turning capacity into actual production.

OEE in the food industry: what number is actually “good”?

This is where the sector’s biggest misunderstanding lies. The famous “85% world-class OEE” originated in the Japanese automotive industry in the 1970s and was applied, without adjustment, to food plants that have mandatory sanitation cleaning, allergen changeovers, and waiting times for quality release. These are different realities.

Current data show the extent of the confusion. The global average for discrete manufacturing is between 55% and 65%, while in the food and beverage sector, the actual excellence benchmark is closer to 82% due to structural CIP and sanitation downtime.

In other words: a food line operating at 78% OEE is not behind; it is very well positioned. And a line that “always reports 85%” may be misleading itself, because manual measurement often overestimates the actual figure by 8 to 12 percentage points.

The practical message for the production engineer is straightforward:

• Below 40%: red flag; there is significant structural loss.
• 40% to 60%: typical range, with plenty of room for improvement.
• 60% to 82%: good to very good range in food manufacturing.
• Above 82%: excellence for the sector, difficult to sustain as a plant-wide average.

Before comparing your food-industry OEE with your neighbor’s, establish an honest baseline. A plant that moves from 62% to 75% OEE gains the equivalent of 15% more capacity without purchasing a new machine. That is the scale of the money being left on the table.

Where end-of-line productivity really gets lost

When a line performs below the benchmark, the instinct is to look at the filling stage. Almost always, that means looking in the wrong place. End-of-line productivity losses are concentrated in the final stages: closing, grouping, and handling.

The logic is mechanical.

The packaging machine or bagging machine at the beginning of the line is usually the fastest and most stable stage.

The problem appears when the finished product needs to be grouped and palletized. As Pac Right’s analysis of line bottlenecks summarizes, the slowest or most unstable stage controls the entire production output, and that stage is rarely filling.

Three symptoms reveal the bottleneck at the end of the line:

1. Accumulation before palletizing. If the products already bagged by the bagging machine accumulate on the conveyor while waiting for the palletizer, it is the palletizer that sets the pace of the final stage of the line, even if the bagging machine has the capacity to operate faster.
2. Inconsistent sealing. Failures or wear in the closing system reduce repeatability and packaging quality long before the machine experiences a definitive stoppage.
3. Dependence on labor for manual stacking. Manual pallet stacking adds dependence on labor precisely when the product is one step away from shipping, and this is exactly where automatic palletizing usually delivers its first gains.

There is one detail that amplifies all of this: an end-of-line system without control integration does not signal when accumulation is beginning to form. Lines with palletizers and case packers connected through a PLC automatically adjust their pace to one another, preventing this cascading effect.

The answer is not always to automate everything at once. Sometimes, the specific bottleneck needs to be addressed. Before making any investment, it is worth mapping what is actually holding the line back.

Compare your line and find the missing number

You already have your machine’s nominal speed. What you may be missing is the other side of the equation: what is the actual OEE of your line, and where exactly is performance being lost between filling and palletizing?

A productivity assessment combines these two figures and shows the gap between what your operation currently delivers and the benchmark for your segment. Talk to an Indumak specialist and receive an assessment of your end-of-line operation based on your product, volume, and targets.

FAQ

What is a good OEE in the food industry? In the food industry, the actual excellence benchmark is around 82%, rather than the 85% often cited as a generic reference. The global manufacturing average is around 60%. A food production line between 60% and 82% is already in a good range, considering mandatory cleaning and sanitation downtime.

Why does my line perform below the machine’s nominal speed? Because nominal speed does not account for micro-stoppages, setup time, speed reductions at the end of the roll, or startup scrap. These invisible losses do not appear in the downtime report, but they reduce end-of-line productivity throughout the shift.

Where does the production line usually lose the most performance? At the end of the line, mainly during closing, grouping, and handling. The filling stage is usually the fastest and most stable. The actual bottleneck is almost always in the final stages, when the finished product needs to be sealed, packed into cases, and stacked at the right pace.

How do I know if I need to automate my end-of-line operation? A good indication is product accumulation before palletizing, inconsistent sealing, and dependence on manual stacking. If the line’s performance drops when volume increases, the end of the line is likely the limiting factor. A productivity assessment can confirm where the bottleneck is before any investment.