Parts identification in fasteners has traditionally been a manual procedure that relies on the human eye to distinguish a specific part. While recognizing components with the naked eye is relatively accurate, it is not always the most precise means of identification.

The human eye is prone to fatigue, which can negatively impact a person’s work performance. Eye strain can cause employees to miss up to 15 minutes of work each day. As a result, it can mean losing more than $2,000 per year for every affected employee.

Image recognition for manufacturing is an emerging technology that provides the best alternative solution – redefining the identification of parts in fasteners.Due to its accuracy, image recognition not only improves operational throughput but also significantly boosts production quality. The advanced technique also integrates well with other data science methods, such as deep learning and big data analytics. As a result, it increases efficiency while reducing operational expenses.

How Image Recognition for Manufacturing Is Redefining Parts Identification in Fasteners

Parts identification in fasteners has traditionally been a manual procedure that relies on the human eye to distinguish a specific part. While recognizing components with the naked eye is relatively accurate, it is not always the most precise means of identification.

The human eye is prone to fatigue, which can negatively impact a person’s work performance. Eye strain can cause employees to miss up to 15 minutes of work each day. As a result, it can mean losing more than $2,000 per year for every affected employee.

Image recognition for manufacturing is an emerging technology that provides the best alternative solution – redefining the identification of parts in fasteners.Due to its accuracy, image recognition not only improves operational throughput but also significantly boosts production quality. The advanced technique also integrates well with other data science methods, such as deep learning and big data analytics. As a result, it increases efficiency while reducing operational expenses.

Value of Image Recognition for Manufacturing Operations

A set of algorithms designed to label and classify different elements in an image makes up image recognition software. Image recognition models take the picture as an input and cross-check it with an existing classified label database. If it finds a match, it labels the image or parts of the picture accordingly.

A recent report from Markets and Markets reveals that the image recognition market will grow at a CAGR of 19.5%, from $15.9 billion in 2016 to $38.9 billion by 2021. The crucial aspect behind the growing demands for image recognition lies in its integration with other technologies, producing a comprehensive system known as computer vision.

However, computer vision is not a brand-new concept. Since the 1980s, quality assurance and packaging have applied image analysis using cameras, single-board image processors, and grayscale machine-vision algorithms. However, until recently, image processing algorithms had rigid rules, forcing developers to hard-code object forms and sizes for the software to recognize them.

The easiest way to grasp how valuable image recognition is in manufacturing today is to delve deeper into its inner workings.

Defining a data set specific to the business is the first step. In the fastener industry, it is a database containing matching images of fasteners and other parts. Using deep learning methods, the image recognition model starts identifying matching pictures in the data set. The identification process called feature extraction allows the computer to compare specific patterns in pixel format, resulting in accurate identification.

Since parts manufacturing follows a strict standard in dimension and shape, image recognition models perform feature extraction faster. It allows the machine to identify variations in parts as errors if it does not match the standard features on the database.

Manufacturing Activities that Benefit from this Technology

Integration of image recognition models to other technologies makes it extremely useful in automating numerous manufacturing activities. Image recognition now has added capabilities such as event detection, object tracking, and image reconstruction. Here are some manufacturing activities that the technology of computer vision helps to automate:

Automated Visual Inspection

Instead of human QA inspectors, an automated optical inspection (AOI) solution helps speed up component inspection. It is an excellent solution for production environments with exhaustive visual quality inspections.

AOI is essential in businesses that manufacture printed circuit boards, as well as for the fastener industry. Small components can be hard to identify and distinguish consistently using the naked eye, especially with the onset of eye fatigue in human workers. Inefficient manual inspection is no longer an issue with computer vision, allowing for faster production.

Optical Grading and Sorting

Optical grading of manufacturing components with the use of cameras is nothing new. However, delegating the entire task to a machine has been almost impossible – until now. Previously, this process required a human operator to fine-tune image analysis consistently. With advancements in image recognition, systems can now operate autonomously with more reliable and accurate results.

The grading and sorting accuracy applies to all types of fasteners, including:

• Cap screws
• Hex bolts
• Pin fasteners
• Rivet fasteners

Image recognition coupled with deep learning can help the computer analyze the quality of each fastener, depending on the shape, size, and other distinguishing physical characteristics. Since machines do not have any lapses in concentration compared to humans, they can consistently identify defects and guarantee high-quality production output.

Warehouse Automation

Combining computer vision with advancements in robotics can help make warehouse operations run more efficiently. Warehouse robots will no longer require human guidance to navigate around repositories. Aside from scanning barcodes, robots can detect spatial distance, allowing them to perform warehouse tasks faster.

Advantages Specific to the Fastener Industry

Here are some advantages of using image recognition that apply to fastener manufacturers:

• Accuracy: Humans are prone to error when performing repetitive tasks for long periods. Image recognition delegated to machines prevents this, accurately identifying component after component regardless of how small some fasteners are.
• Speed: Image recognition works faster than the human eye, reducing manufacturing time significantly. Furthermore, robots installed with this technology do not need to take breaks and can continue to work in sync for a long time.
• Safety: Machines with computer vision can quickly identify problem points and react faster. If there is an issue in the processing plant, machines can identify it quicker and perform automatic shutdowns when necessary.
• Cost-effective: An automation system with computer vision is faster to deploy compared to training workers. Its ability to eliminate human errors and increase product throughput makes investing in this technology cost-effective in the long run.

Versatile: With image recognition as a subset of an automation system, the technology can go beyond parts identification. From monitoring quality control to ensuring compliance to ISO standards, it has plenty of other uses in various plant operations.

Improve the Outcome of Fastener Manufacturing

Image recognition models are now more accurate and easier to train. When paired with advancements in deep learning algorithms, it becomes proficient in handling almost any task that requires optical capabilities.

It offers a host of benefits to manufacturers aside from reducing operating costs and improved product quality. Businesses can redeploy their human staff to duties that require a human touch, adding more value to their customers.

To learn more about the latest trends, attend the International Fastener Expo 2021 and bring yourself up to speed with the technological advancements that can improve your fastener business.