Cost pressure for manufacturing companies is constantly rising. To remain competitive, they must maximize output and reduce production costs. This can, in the worst case, have a negative impact on product quality and process reliability. Used correctly, modern process analytical technology can improve all these aspects.
Often, the investment in Process Analytical Technology initially seems very high. A ROI analysis provides the necessary transparency to facilitate investment decisions and to illustrate their benefits in monetary terms.
Larger investments must be carefully thought through right from the start. In the following calculation example from the chemical industry, we show you the savings potentials that can be associated with an investment.
A manufacturer of polyurethane (PU) with 2 reactors at one site and a production volume of 3600 t/year achieves a gross profit margin of €7 million/year.m
Location: | 2 reactors á 12 t |
Raw material costs: | 1,500 €/t |
Product market price: | 2,500 €/t |
Gross profit: | 1,000 €/t |
To simplify, a consistent production is expected over the whole year. On average, 3 samples are taken per reactor per day. Laboratory analysis is maintained and needed for calibration preparation and regular checks. The effort can be reduced by an estimated 80%.
Analysis costs: determination of NCO, acid number and viscosity → 50 € / sample.
365 days x 3 analyses x 2 reactors x 50 € = 109.500 €/a
Savings: 109,500 €/a x 80 % = 87,600 €/a
In the past, there was an average of 3 faulty batches per reactor (approx. 4 % of batches/a). With PAT, the number of faulty batches could be reduced to 1 per reactor (1.3 %).
Total output: | 150 batches/a = 3600 t/a |
Scrap: | 2 x 2 batches x 12 t = 48 t/a |
Raw material costs | 48 t/a x 1.500 €/t = 72,000 €/a |
Disposal costs: | 48 t/a x 500 €/t = 24,000 €/a |
Lost profits: | 48 t/a x 1.000 €/t = 48,000 €/a |
Total costs: | 144,000 €/a |
Due to faulty batches, production time is also lost. Other costs such as personnel, equipment or energy costs are neglected in this example.
Thanks to online analytics, the process time of the individual batches could be reduced. Approx. 3% more batches can now be produced.
Additional output: 3% x 3600 t/a x 1,000 €/t = 108,000 €/a
Total costs: 160,000 €
Savings laboratory costs: | 87,600 €/a |
Potential savings raw material/disposal: | 144,000 €/a |
Additional Outpout: | 108,000 €/a |
Total Savings: | 339,600 €/a |
PAT-Investition: | 160,000 € |
160,000 € / 339,600 €/a = 0.47 a = 5.7 Monate
Conclusion: The initially "supposedly" high PAT investment pays off after only 5.7 months.
Feel free to contact us and talk to us about your challenge! Our Hellma Solutions team is there for you and will help you determine your ROI. Depending on your requirements, we will put together the necessary components and develop an analysis method individually tailored to your application.