Every supplier can quote a payback period, and almost none of those numbers survive contact with an investment committee. The reason is not dishonesty; it is that a payback figure is a conclusion, and a supplier can only supply the part of it they control. Output, utilisation, resin price, energy tariff, labour rate and scrap rate all belong to the buyer, and a model built without them is a model of the supplier’s optimism.
The cost of accepting a vendor payback number is paid twice. The obvious cost is a capital decision made on a figure nobody could defend. The less obvious one is what happens later: when the saving does not appear, the discussion turns into a dispute about the original assumption instead of into a plan to recover the difference.
Sailwin has built PET blow molding machines for 15+ years, with 500+ machines delivered into 60+ countries, CE marking, ISO 9001:2015 manufacturing and a 2-year whole-machine warranty. Because the machines log 40+ parameters in real time, run at blow pressures of 25–40 bar with preform heating between 90 and 115 °C, and complete a mould change in under 30 minutes, the operational inputs a financial model needs are measurable rather than assumed. This article sets out how to build a payback case that an engineer, an accountant and a bank can all accept, with the assumptions exposed where they can be challenged.
Key Takeaways
- A payback figure is an output, never an input. Build it from your own utilisation, resin, energy and labour data, and label every assumption so it can be tested.
- Utilisation breaks more models than machine price. Rated output multiplied by hours is theoretical; rated output multiplied by hours and real OEE is the only figure that generates savings.
- Only three savings categories are normally defensible: resin, energy and labour — and each one needs a baseline measured before the machine arrives.
Build Your Payback Case With Engineering Inputs
Send your bottle specification, target output and current cost data — our engineers return the machine and mould configuration plus the operational inputs your financial model needs.
1. Why Vendor Payback Numbers Fail Due Diligence
A supplier’s payback calculation normally rests on the machine running at its rated output for a generous number of hours, producing saleable bottles at a resin price and an energy tariff that are never stated, with no ramp-up and no learning curve. Each of those is individually plausible. Together they produce a number that only holds in a plant that does not exist.
The most common single error is treating rated capacity as a saving. If a machine rated 7,500 BPH replaces a machine rated 5,000 BPH, the honest question is not how many extra bottles it can theoretically make, but how many extra bottles you can actually sell and run. Capacity that is not used is a cost: it consumes floor space, depreciation and maintenance attention while producing nothing.
The second most common error is ignoring the cost side. A new machine adds depreciation, may require additional compressed air and chilled water capacity, changes the spare parts profile and may need more operator training. A model that lists six savings and no new costs is not conservative; it is incomplete.
2. The Inputs That Actually Move a PET Blow Molding ROI Case
Rank the inputs by how much damage an optimistic assumption does, not by how easy they are to find. The order below is the order a reviewer will attack them in.
| Input | How to source it defensibly | What an optimistic figure does |
|---|---|---|
| Utilisation and OEE | From your own production records over a full year, including planned stops and rejects | Inflates output-based savings on every line of the model at once |
| Bottle weight and resin price | Measured weights from current production, and a resin price hedged or averaged over a period | Turns a material saving into the largest and least stable line in the model |
| Energy baseline | Metered consumption per thousand bottles before the change, at the same product mix | Claims savings against a baseline nobody measured, which cannot be verified afterwards |
| Labour content | Operators and quality staff per shift, with a stated assumption about redeployment rather than headcount removal | Overstates savings where staff are redeployed instead of released |
| Scrap and rework rate | Reject counts with reasons, recorded daily rather than estimated monthly | Hides the real gain, because scrap reduction is often the most reliable saving available |
| Ramp-up and learning curve | A stated number of weeks at reduced output, drawn from the commissioning plan | Assumes savings begin on day one, which flatters the first year and the payback figure |
| Discount rate | Your finance department’s rate, not the one that makes the project clear a threshold | Makes a marginal project look comfortable and destroys credibility when reviewed |
A payback period is a symptom of the assumptions underneath it. Show the assumptions and the number defends itself; hide them and no number is large enough to be believed.
Get the Operational Inputs for Your Investment Case
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3. Building the Model Step by Step
Do the calculation in a fixed order, because each step constrains the next. Start from effective output, then apply the savings, then subtract the incremental costs, and only then calculate the return.
Step 1 — effective annual output. Effective output is rated output multiplied by operating hours multiplied by real OEE. The arithmetic is worth doing explicitly: a machine rated 7,500 BPH running 6,000 hours a year produces 45 million bottles at 100% OEE, and proportionally less at any realistic figure. Everything downstream scales with this one number, which is why an optimistic OEE corrupts the whole case.
Step 2 — resin saving. Annual resin saving is effective output multiplied by the reduction in bottle weight, multiplied by resin price per kilogram, adjusted for the regrind credit and for the share of production that is scrapped. This is usually the largest single saving and the one most sensitive to assumptions, because both the weight reduction and the resin price are outside the machine supplier’s control.
Step 3 — energy saving. Annual energy saving is metered consumption per thousand bottles multiplied by effective output, multiplied by your tariff, multiplied by the fraction of the consumption gap you actually capture. Two verified machine characteristics drive it: servo drive reduces energy consumption by up to 30% compared with conventional hydraulic drive, and high-pressure exhaust recovery reduces compressor load by about 20%. Note the phrase "up to". Model the fraction you can defend from a metered baseline, not the best case.
Step 4 — labour, quality and scrap. Labour savings should be stated as hours redeployed multiplied by a loaded rate, with an explicit note on whether the headcount actually leaves the cost base. Scrap reduction is often the most reliable saving of all, because a lower reject rate converts directly into saleable output at full selling value.
Step 5 — net annual cash saving. Subtract incremental operating costs: additional maintenance and spare parts, any added compressed air or chilled water capacity, floor space, insurance and any increase in depreciation that affects cash. The difference between the savings total and this figure is the number that belongs in the model.
Step 6 — payback, then net present value. Simple payback in years is total investment divided by net annual cash saving, where total investment includes the machine, moulds, installation, utilities, commissioning, training and the working capital tied up in preform inventory. Then calculate net present value over the asset’s expected life at your finance department’s discount rate, because payback ignores everything after the payback point and systematically favours short-lived projects.
Present both. A payback figure answers "how long until we get our money back"; the net present value answers "is this the best use of the money". Investment committees ask the second question even when they open with the first.
4. Sensitivity: Which Assumption Breaks the Case First
Run a sensitivity table before submitting the case, varying each key input on its own across a plausible range while holding the others. In PET bottle projects, utilisation usually moves the answer more than any other single input, because it scales output, resin saving, energy saving and labour saving simultaneously. Resin price is the most volatile input and the one worth hedging or averaging. Bottle weight reduction is the input most within engineering control, which is why lightweighting work often improves the business case more than changing the machine does.
Mould economics deserve their own line rather than being folded into the machine cost. Mould cost is a fixed sum spread over the volume that mould will run, so a casing built for modest annual volume carries a much higher cost per bottle than the machine’s output figure suggests. If the case only closes at high volume per mould, state that clearly rather than burying it.
5. Case Study: Rebuilding a Payback Case Around Measured Data
A beverage bottler had two competing proposals, each with a headline payback figure. Neither model could be reconciled with the plant’s own utility and production data.
- Two proposals with headline payback figures that could not be reproduced from plant data
- No metered energy baseline per thousand bottles, so energy savings could not be verified later
- Reject counts recorded monthly, which hid the scrap trend that mattered most to the case
- Baseline established first: metered energy per thousand bottles, measured bottle weights and daily reject counts
- Output expressed as rated output multiplied by planned hours multiplied by the plant’s own OEE record
- Energy saving modelled from the servo drive figure as an upper bound and a defended fraction as the planning case
- Mould cost amortised per product against expected lifetime volume and shown as a separate line
- The decision was made on reproducible data, so both suppliers were compared on the same basis
- Sensitivity showed which assumptions had to be protected, and those became operating targets rather than opinions
- Benefits became measurable after installation, because a baseline existed to measure them against
Scenario based on a Sailwin customer project; site-specific figures available on request during engineering review.
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Related Reading:
• PET Blow Molding Machines: Full Range Overview
• How Much Does a PET Blow Molding Machine Cost?
• Mould Cost Breakdown for PET Blow Molding
• Energy Consumption per 1,000 Bottles
• Bottle Lightweighting and Resin Savings
• PET Blow Molding OEE: What Good Looks Like
