Make Automatic Quality Control Faster, Cheaper &. Accurate

Make Automatic Quality Control Faster, Cheaper &. Accurate

The strength, flexibility, and durability of plastic make it ideal for countless applications, from energy-efficient electronics and lighter and more fuel-efficient cars to disposable medical devices that improve patient safety. In all cases, quality control is essential to ensure that the performance of plastic parts meets expectations. By 2020, this challenge will become more complicated due to the impact of the epidemic. Plastic processors have to deal with fluctuations in consumer demand, labor shortages, supply chain fluctuations, and new workplace safety regulations. This perfect storm has placed an unprecedented burden on manufacturers trying to maintain machine utilization and production line efficiency while producing high-quality products.

1.Fluctuations in consumer demand

This year, COVID-19 struck, due to the shrinking consumer activity, many injection molders saw a decrease in demand for large-volume orders for some parts. At the same time, the demand for disposable plastic products has surged. These products have been the focus of environmental protection organizations for many years, but in the face of the epidemic, consumers are more concerned about the hygiene and safety provided by these disposable products. At the same time, plastic product manufacturers have increased demand for prototypes and small batches of medical grade equipment and basic worker supplies.

Increasing and reducing the output of various products means adjusting quality control requirements and processes. For mass production, a small part of the product is usually visually inspected by a human operator. Sometimes, the inspection of individual parts is even performed by the customer before the parts are incorporated into the assembly. In addition, small batches and new products require fast and increased quality inspection protocols, that is, the ability to inspect each component and follow up the inspection process, requiring very little on-site infrastructure or expertise.

2.Production line quality inspection automation

Injection molding machines and other plastic processors are faced with more product portfolios than before and need to quickly adjust their quality inspection procedures. In the past, human operators who performed inspections could not meet the requirements, especially for medical device parts, which usually required strict quality agreements. Considering the new normal of unpredictable consumer demand, the key to success lies in flexibility and adding “a pair of eyes”

Take the global automotive plastics market as an example. Last year, the global automotive plastics market was valued at more than 35 billion U.S. dollars. Many injection molders are running dozens of production lines, and each production line has its own machine vision for quality control. They are facing the challenge of how to effectively deal with production line conversion and modification. While many surface inspections of plastic parts are subjective in nature, this assessment is difficult to complete by machine vision alone.

Artificial intelligence allows manufacturers to quantify defects that were previously qualitatively or subjectively judged by operators. There may be guidelines for surface inspection, but they are visually recognized and not standardized because the programming of custom machine vision systems is very complicated. Artificial intelligence and deep learning facilitate this standardization and promote automated inspections that are faster, cheaper, and more accurate than ever before. Plastic manufacturers can quickly integrate Vision AI software with common automation protocols, such as GigE Vision standard cameras and Modbus TCP. By connecting to the manufacturer's existing hardware, Vision AI provides great flexibility to deal with production line quantity changes, labor constraints, higher inspection rates and stricter quality requirements.

As the world rediscovers the unique versatility of plastics to meet new challenges, artificial intelligence and machine learning can help manufacturers speed up the inspection process, reduce errors and false alarms, and conduct quality control checks without anyone.