Ten extra minutes on a cleaning cycle may not look like much.
But repeat it across every production run, every week, every year, and the cost starts to look very different. Add in the production time lost elsewhere on the line, the utilities burned through longer processes, the extra maintenance just to keep things moving. And small performance gaps become big operating costs.
That is the problem with underperformance, the cost is rarely one big number, it accumulates.
For one large food and beverage co-packer in Japan, manual cleaning between product changes was taking 180 minutes per cycle. After Tetra Pak helped identify an opportunity to automate cleaning-in-place and refill of the homogenizer dampener, manual cleaning time was reduced to 90 minutes. That contributed to more than 12 additional hours of available production time each week and annual savings of €27,000.
The lesson isn't that cleaning can be faster. It's that a recurring operational gap carries a much larger annual cost than it first appears.
Before asking, “What will it cost to improve this?”
A better question is, “What is the current way of operating already costing us?”
When deciding what to improve, you first need to understand what is happening today.
That means looking beyond the performance of an individual machine. A constraint may sit in the equipment itself, but it may also come from controls, process configuration, cleaning routines or the way different parts of the line interact.
The aim is to establish a credible operating baseline: how much production time is available, where time is being lost, what the current process costs to run and where performance is being constrained.
Only then can you judge whether improvement is worth the investment.
Capacity can be part of that opportunity. Releasing production time from an existing line can support additional throughput. In other situations, an upgrade can adapt an existing line to new production requirements without replacing equipment that still has useful life.
One challenge with underperformance is that its cost is often spread across different parts of the operation.
Lost production time may appear in one place. Utilities or chemicals in another. Maintenance effort somewhere else.
A broader total cost of ownership view brings those effects together around a simpler question: what could be recovered if the performance gap were reduced?
In this context, TCO starts with what the process costs to run and maintain. It also accounts for the value of lost capacity and the cost of making the change. This gives the investment decision one view of both the current operation and the proposed improvement.
For an efficiency decision, that might include productive time lost to cleaning or changeovers, the cost of running the current process, and the value of capacity that could be released from existing equipment.
It should also include the cost and disruption of making the improvement itself.
What matters is comparing the economics of the current state against the economics of changing it, not building a longer list of inefficiencies.
Go back to the Japan example, where a 90-minute saving looks operational when seen once and financial when seen across a year. That’s the important shift that turns a recurring performance gap into a number the business case can use.
Once the baseline is understood, the real question is how much improvement is realistic for that factory, not how much is theoretically possible.
Production schedules, operating hours, product mix and equipment configuration all affect the answer.
A beverage manufacturer facing high steam consumption and rising operating costs provides one example. Tetra Pak assessed the process and identified product-to-product regeneration as the appropriate improvement.
Following the upgrade, steam consumption fell by 969,000 kg per year, around 30% compared with the previous design under the stated operating conditions. That corresponded to annual cost savings of €37,000.
What matters here is the line from operating problem to process change to economic result, not the percentage on its own.
That context matters. Published upgrade figures are tied to assumptions such as equipment type, capacity, production hours and operating conditions because achievable value varies from one application to another.
Savings alone do not make an investment case.
Installation time, commissioning, production stops and process adjustments all need to be considered too.
When several Spanish customers sought to reduce energy use following sharp increases in energy costs, Tetra Pak introduced UHT indirect mode alongside other improvements across seven UHT lines.
The projects delivered a reported 70% reduction in energy consumption, primarily steam, per line. Careful adjustment of process parameters kept the impact on product quality negligible, while planning minimised production downtime. The customers saw return on investment within a few months.
That gives the more complete view: what can be saved, and what it takes to achieve the saving.
The objective is to identify where the gap between current and realistic performance is large enough to justify action.
Tetra Pak® Upgrades supports that process by looking at how equipment, processes and systems perform together, then helping identify and prioritise opportunities based on measurable operational outcomes.
A Direct Heating Module upgrade, for example, can reduce CIP time by 10% and detergent costs by 50%, with the potential to increase production running time by 10% for the specified equipment and application.
But the technology should come after the diagnosis.
What is happening now? What is it costing over time? How much of that gap can realistically be closed? And is the expected value greater than the cost and disruption of change?
Use those answers to identify where action is worth taking and prioritise the right improvement. That is how value already sitting in existing equipment can be unlocked either through additional capacity, or a change in what the line can produce, or a measurable reduction in operating cost.