The ROI of rigid-box automation is not the difference between machine price and labour cost. It is the financial value of additional accepted production, lower conversion cost, controlled quality and reduced operating risk over the life of the project.
A useful model must represent the factory’s real product mix. Nominal machine speed, average wage and a single payback formula are not enough when batches, formats and materials change every day.
Start with accepted boxes, not theoretical cycles
Calculate the number of saleable boxes produced during a normal shift after changeovers, planned stops, material replenishment, quality checks and rejects. The core production equation is:
Accepted output = scheduled time × effective running rate × availability × first-pass yield
Use separate assumptions for the major product families. A large deep box, a standard cosmetics box and a short-run special geometry should not share one performance value.
1. Establish the current-state conversion cost
Document the existing process before modelling the investment. Include direct operators, indirect material handling, setup labour, rework, scrap, energy, maintenance, floor space and outsourcing. Record constraints that limit sales or cause late delivery.
If current data is incomplete, run a representative time study across several product families rather than filling every gap with optimistic estimates.
2. Value labour correctly
Separate labour eliminated, labour redeployed and new skills required. Automation may reduce repetitive handling while increasing the need for line supervision, material preparation and technical maintenance.
The economic model should use the company’s fully loaded labour cost and realistic shift coverage. Redeployed people create value only when the alternative activity is defined.
3. Quantify changeover economics
For mixed luxury-packaging production, changeover can be more important than maximum speed. Measure from the last accepted box of one batch to the first accepted box of the next. Include recipe loading, mechanical adjustment, material change, quality approval and start-up scrap.
Annual changeover cost is the combination of lost productive time, labour and discarded materials across the expected number of changes.
4. Include quality and material yield
Calculate the cost of rejects at their point of detection. A box rejected after wrapping contains more material and conversion value than a component rejected earlier. Include rework labour, replacement material and the impact of quality claims or delayed orders where measurable.
Use first-pass yield and setup scrap as separate variables. Automation should be evaluated on both stable production and the transition into stable production.
5. Model energy and utilities
Record energy at comparable operating conditions and include idle, production and changeover states. Add compressed air, heating or cooling where relevant. The useful comparison is energy per accepted box or per representative batch—not installed motor power alone.
6. Add maintenance and downtime risk
Include planned maintenance, wear parts, technical support, software, training and a provision for unplanned downtime. Estimate the contribution lost when the line is unavailable, especially if there is no alternative production route.
Availability assumptions should be supported by maintenance capability, spare-parts strategy and supplier response—not by a percentage copied from an unrelated process.
7. Value capacity and commercial flexibility
An investment may enable products that are currently outsourced, rejected or impossible to industrialise. Model this separately from cost savings. Use contribution margin rather than revenue and apply a probability to opportunities that are not yet contracted.
Also consider the value of shorter lead times, smaller economic batches and the ability to serve more product variants without disproportionate setup cost.
Build a five-year TCO model
| Cost or benefit | Include in the model |
|---|---|
| Initial project | Equipment, options, tooling, logistics, installation and site work |
| Ramp-up | Training, qualification material, reduced initial output and engineering time |
| Operating cost | Labour, energy, consumables, maintenance, software and floor space |
| Quality | Setup scrap, running rejects, rework and measurable claims |
| Capacity value | Contribution from accepted incremental production and insourcing |
| Risk | Downtime exposure, demand sensitivity and residual value |
Calculate payback and test the assumptions
Simple payback can be expressed as net project investment divided by annual net cash benefit. Also calculate a discounted cash-flow view if the project horizon and company policy require it.
Run at least three scenarios: conservative, expected and high utilisation. Vary volume, product mix, first-pass yield, changeover time and ramp-up. A robust project should remain understandable when one assumption moves in the wrong direction.
The minimum data package for an engineering discussion
- format and material matrix;
- annual volumes and batch sizes by product family;
- shifts, operators and current production route;
- changeovers per shift and measured setup time;
- scrap, rework and quality constraints;
- expected growth and required delivery window.
ROI assessment
Build the model around your production mix
Share your formats, volumes, batches and current process. SATE can use them to structure a preliminary technical and economic assessment of the appropriate automation architecture.
Request an ROI assessment Explore SATE solutions