Alice Leroy
Virtually any kind of plastic can be recycled if someone wants to put the time and effort into doing it. However, no form of recycling is without its challenges. One of the big challenges with plastic is maintaining quality. Recycling tends to reduce quality one way or the other. If quality is reduced too much, you end up with a recycled product for which there is no market.
As recyclers continually seek to improve their processes, manufacturers are investing in new technologies that will enable improved quality control. Enter artificial intelligence (AI). By incorporating AI mold monitoring systems, injection mold manufacturers can improve part quality while actually using more recycled material.
Inconsistency Can Be a Problem
An injection mold manufacturer here in the States might purchase pellets of recycled plastic from Tennessee-based Seraphim Plastics. Seraphim sells the material as plastic regrind. Regrind is mixed with virgin plastic pellets to make new products.
Combining recycled and virgin plastic is fine in principle. But in practice, it is challenging. One of the biggest problems is part consistency. It can vary from part-to-part, batch-to-batch, or lot-to-lot. Inconsistencies are mainly due to how recycled plastic pellets perform during manufacturing.
Failing to produce consistent quality makes a manufacturer less reliable, especially for mission critical parts. So it’s in the best interests of the injection mold industry to figure out how to improve quality without completely abandoning recycled plastic.
Monitoring the Mold
AI mold monitoring systems continuously take a variety of measurements from deep within the heart of an injection mold machine. Sensors monitor everything from temperature to pressure and plastification. But there’s more. As data is harvested and analyzed, AI systems get increasingly better at predicting what will happen under certain conditions.
Predictive analytics is what we are talking about here. And it can help manufacturers make necessary changes to both plastic formulas and molding processes. The right changes should increase consistency across each and every part run. That is the key. Solve the consistency issue and manufacturers will have the opportunity to use more recycled plastic.
Banning Plastic Is Not a Viable Option
Learning that manufacturers are leveraging AI to improve recycled plastic quality is exciting enough. But it’s even more so when you consider all of the calls to ban plastic. Banning plastic is not a viable option. It is not going to happen. We are better off putting our energies into coming up with more effective ways to recycle it.
AI represents a step in that direction. Right now, manufacturers rarely make products entirely from recycled plastic. PET water bottles are an exception to the rule. But by and large, recycled plastic pellets are mixed with virgin pellets for the simple fact that there would be a noticeable drop off in quality if a manufacturer went with 100% recycled material.
That may change as AI mold monitoring matures. We may be headed toward a day when AI systems can accurately predict a loss of quality, thereby giving a manufacturer time to make adjustments. Successfully monitoring and adjusting could ultimately mean more products being made exclusively from recycled plastic.
We Can Always Find a Way
If nothing else, the idea of leveraging AI to improve the quality of recycled plastic products proves that we can always find a way to clean up our messes if we want to. There is no need to continue the unnecessary war against plastic.
We would be far better off putting that same time in energy into improving recycling and recovery efforts. Leveraging AI can help us do both better. Isn’t it worth investing in?
