Machine vision and food inspection automation
By the end of 2018, the US food and beverage industry will produce enough goods to create $16.2 billion in revenue. In the long run, this number is second only to China. China is the world's largest food and beverage producer and the world's most populous country with a population of nearly 1.4 billion.
To make the US food and beverage industry work smoothly, complex processing, production, packaging and distribution are required. Things don't always go as planned, and producers may find themselves facing product recalls, outbreaks of foodborne illness, and even consumer complaints. Industry 4.0 provides an intelligent and efficient method to ensure the highest levels of food inspection and food safety standards with the help of machine vision.
Machine vision definition
Machine vision has only recently been considered a tool widely used in the food production industry. In fact, machine vision was first used in food quality testing in the 1980s. These early iterations of machine vision consisted solely of a camera camera that was used to inspect the muffin line to ensure that oversized products did not enter the machine. Although this process is rough, it has proven to be effective.
Today's machine vision systems are much more complicated. The Automated Imaging Association (AIA) classifies machine vision as a combination of hardware and image analysis software to assist the device by capturing images. Today's machine vision systems often have more or less sophisticated artificial intelligence that analyzes patterns and extracts data from objects within their line of sight. The obtained data is then compared to any existing data extracted from the system database - the database is managed manually, not automated. Once the data has been reviewed, the system will draw conclusions about the captured project.
The entire process, from start to finish, takes less than a second. However, in such a short period of time, the system collected a lot of useful information about the project. Data on the color, maturity, deterioration and internal temperature of the food is available in a blink of an eye. It is even possible to obtain information that is undetectable by the human eye, such as machine vision to analyze the internal components of food by using different wavelengths. It can also be used for packaging defect detection, preventing material waste, mislabeling and expensive food recalls.
Food Inspection, Boss Magazine According to data from the US Food and Drug Administration and the US Department of Agriculture's Food Safety and Inspection Service, there were 456 food recalls in 2017. This includes multiple food safety violations/recalls of the same product. Undeclared food allergens (especially in dairy products) are the first choice for recall reasons. Listeria is the second most common cause of recalls and usually affects popular breakfast foods. There are also 24 Salmonella-based recalls and 2.4 million pounds of ready-to-eat breadcrumb chicken products that contain undeclared milk content, making people who are allergic to dairy products at risk.
Although the total number of recalls has declined from 2015 and 2016, the recall is still a major issue in food production. In fact, as an industry, although the increase in machine vision usage can significantly improve health and safety standards, food production lags far behind other line industries in terms of automation.
The food production industry is doing very well. It must remain efficient while producing food that meets consumer needs, as well as federal health and safety regulations. In addition, manufacturers need to weigh the costs of traditional low-margin businesses and the higher safety and quality requirements of the food production value line.
Achieving machine vision may require an initial investment higher than many manufacturers, but it can increase processing efficiency, reduce costly mistakes, negligence and recalls (some of which may lead to more expensive litigation), and can offset investment costs in a shorter vision.
In addition, consumer costs need to be considered. Because the health and safety of consumers are threatened, the food inspection process must adopt a zero tolerance policy for errors. Once a brand or product fails, it loses the trust of the customer. Improperly labeled food or signs of neglected infection in meat or poultry can cause loss of life. This year alone, the FDA has linked 44 deaths to salmonella outbreaks. The Salmonella outbreak is associated with a dietary supplement containing kratom, a tropical tree native to Southeast Asia. These deaths can be avoided if the factory producing these supplements has machine vision or other automated inspection processes.
Application of machine vision in food inspection
When it comes to food safety, machine vision delivers unparalleled quality, precision and efficiency. From the detection of raw materials to whether the food is overcooked or cooked, automated visual food testing can even capture the finest details of the food.
However, the food inspection process is not just a review of food items. If there is any damage to the package, the food is likely to be degraded. Machine vision can detect packaging defects, identify and correct erroneous labels, and even identify packaging that is mislabeled due to human or machine errors.
If a food is part of an intermediate process, or is itself an intermediate product, machine vision can help track and track all relevant components (and their associated data) from the production process to the finished product. This is a particularly critical step for food producers who get food ingredients from other manufacturers, as the quality and safety of every link in the supply chain increases as each additional investment increases. More and more complicated.
Automated visual food testing provides strong quality control and more efficient production processes, laying the foundation for innovation in the food production industry. Machine vision is not just the latest technological advancement in food inspection, it is also an opportunity for the food production industry to improve health and safety standards – this is what we can do.