AI is the Game-changer Your Injection Molding Process Needs

Summary

In the ever-evolving world of manufacturing, artificial intelligence is transforming plastic injection molding. Whether you're already leveraging AI or beginning to explore its potential, understanding the benefits of AI in injection molding can unlock unprecedented opportunities for your business.

Improving maintenance methods

Staying on top of injection machine maintenance is a practical way to operate profitably and meet clients’ expectations. Unexpected outages raise costs and could contribute to lengthy downtime that significantly disrupts workflows.

However, researchers addressed the problem by creating an AI-driven prescriptive maintenance tool and testing it with a plastic injection molding machine. The solution works in multiple ways. First, it identifies the relevant anomaly or fault, plus the estimated remaining useful life of the affected components. However, a sustainability element also comes into play with the prescriptive maintenance feature. The system proposes the best solution for fixing the issue based on environmental and economic factors.

The researchers’ test scenario relied on data from 13 sensors that recorded parameters such as temperature, pressure and injection time. The system processes incoming information and examines it to detect anomalies. Once it finds a problem, the algorithms attempt to find the root cause. They then evaluate possible solutions from a list of appropriate maintenance actions.

Conclusions based on lab experiments showed this approach can reduce material waste and improve energy efficiency. Those involved also identified how this maintenance framework could support knowledge transfer, equipping less-experienced technicians with the decision-making capabilities to make faster, more confident choices when handling specific problems.

Such applications could also help people see which issues most often affect plastic injection molding operations. Other industries have already developed such options. One example for fleet technicians showed that 35% of issues affecting an e-commerce company’s delivery vehicles were tire-related.

Poor cleanliness, inadequate lubrication and worn components can all cause unexpected downtime. People should establish a maintenance checklist to avoid many of those issues. However, they should also strongly consider using AI to catch problems they may otherwise miss.

Enhancing quality control

As professionals learn more about the benefits of AI in injection molding, many realize the technology can help them meet quality goals while increasing customer trust and satisfaction. Artificial intelligence can analyze production data, pinpointing the issues that lead to below-standard products. The findings can then allow humans to determine if quality has decreased due to specific machines, new suppliers, operator errors or other factors.

Injection molding enables excellent consistency between items. That is normally an advantage, but it can become a problem if a brand produces too many faulty products and people cannot identify the cause.

Such was the case with a provider who produced a specialty plastic bottle for a health care client. Factory managers could not determine what caused a higher-than-average defect rate in the containers. Another complicating factor was that this production challenge arose during the early stages of the COVID-19 pandemic, when the health care industry faced extraordinary shortages and demands.

However, the injection molder began using an AI solution to monitor, predict and prevent numerous common defects. That change happened when defect rates had reached at least 20%, prompting executives to realize it was time for improvement. Since the chosen product gathered data from more than 300 sensors, those leaders soon had a wealth of information to study.

A 90-day pilot gave decision-makers sufficient knowledge of different parameters and how they affected the plastic container’s overall quality. Further investigations revealed two defect types caused 80% of the calculated scrap rates. Leaders utilized AI to bring a 25% improvement. They also deployed a complementing solution combining artificial intelligence and the Industrial Internet of Things to change parameters as necessary to achieve optimal results automatically.

Minimizing setup time and improving compliance

Some commercially available solutions suggest shorter setup times are among the other benefits of AI in injection molding. Such offerings could benefit less-experienced machine operators or those with heavy workloads.

One artificial intelligence product guides the initial molding process, supporting repeatability and optimization. The system works by learning the best setups and replicating them for future projects. It also accounts for the parameters that can cause weight changes in parts made with plastic injection molding.

More specifically, the AI analyzes factors such as the manufacturing environment’s humidity and temperature and differences in the resin’s physical properties. Once it detects a weight change, it automatically makes the necessary adjustments to accommodate it.

Those capabilities support better consistency while saving operators’ time. This solution also accommodates add-on scales, allowing users to input the actual weight differences into an internal database.

AI also supports business leaders who must abide by strict regulations when producing injection-molded components. They must document and optimize all process parameters, satisfying regulatory bodies and increasing customer trust.

One product improves process monitoring for injection molding by automatically measuring cavity pressure and determining whether the output deviates from standards. A complementing solution predicts item quality with the pressure data and temperature curves. Then, managers can spot instances where the results may fall short of regulations and make the necessary adjustments before the issues become uncontrollable or defective products reach the market, resulting in mandated recalls.

Experience the benefits of AI in injection molding

These examples highlight why you have numerous compelling reasons to bring artificial intelligence into your plastic into your plastic injection molding workflows. Get the best results by carefully analyzing each step of the current processes and determining which are most error-prone or otherwise problematic. Then, explore which solutions are most appropriate for getting the desired outcomes. Maintain a goal-oriented mindset by choosing metrics to track and determining how you will measure the AI technology's effectiveness.

It is also a good idea to speak to employees about which process steps would most benefit from AI guidance. They will appreciate it if you explain how the technology will affect their roles and how long it will take to learn a new platform or system. Although applying AI to injection molding is a relatively new option, many companies have developed specialized options. Having a clear idea of what you want to achieve by using the technology will help you find the most suitable possibilities.

_{This feature originally appeared on ISA Interchange.}