Barcode scanner utilising machine vision

Machine Vision: Seeing and believing ROI

Machine vision represents one of the most exciting Industrial Internet of Things (IIoT) and industry 4.0 technologies to emerge and revolutionise supply chain operations with experts predicting the machine vision market to expand at a compound annual growth rate (CAGR) of 7.2% over the five-year forecast period (2023–2030).

The market drivers of this growth are largely due to an increasing demand for enhanced quality control and inspection. But its integration with collaborative robots and Artificial Intelligence (AI) will dramatically improve industrial automation in the warehouse, the manufacturing plant and throughout the supply chain.


The intelligent lens for industrial automation

Machine vision replaces the human eye with processes used to enable robots and computers to visually perceive and interpret their surroundings. They use advanced imaging techniques like cameras, sensors, and imaging processing algorithms to mimic the capabilities of human vision. Allowing them to be used to enhance business processes.

This means that machines can perform tasks that require visual inspection or analysis. Such as extracting meaningful information from images or video streams and using it to make intelligent decisions.


Machine Vision drastically optimises supply chain operations and industrial automation and has many potential benefits, including:


Barcode scanning

  • Traditional barcode scanners have long been the backbone of warehousing, logistics and manufacturing data capture. But they are ultimately limited by their ability to scan and capture one piece of data at a time.

The pairing of modern camera technology and machine vision removes this limitation. Thus enabling supply chain organisations to collect multiple pieces of data at speed. It can be programmed to scan multiple barcode types at various angles, identify the number of items in a box and even flag items that are defective or damaged.


3D vision capabilities

  • When organisations use 3D vision capabilities with a machine vision system, they can capture accurate and detailed information regarding the precise shape of an object. Even if it is complex or irregular.

This allows them to detect surface defects with higher accuracy and reliability, ensure products meet specific requirements and classify them based on specific attributes.

Businesses can use this information to detect errors early, reduce the risk of faulty products reaching the market and even compare the product with the 3D model or CAD design to ensure it meets specifications.


Increasing efficiency

  • With machine vision, robotics and automation technologies in place, staff don’t need to work on repetitive, time-consuming tasks anymore. This provides excellent growth.
  • Machine vision isn’t just a technology for collecting and evaluating data at the moment. It’s also a powerful tool for preparing effectively for upcoming demand and forecasting tasks further down the process.

This technology can utilise various types of data to enhance warehouse operations and achieve greater success. This data includes information on inventory, logistics, distribution, market trends, customer demand, economic climate, and weather. By analysing and processing this data, AI and machine vision can make informed decisions and optimise warehouse processes. This ultimately leads to improved efficiency, cost savings, and increased customer satisfaction.


Real-time visibility

  • The real-time visibility provided by machine vision means that businesses can accurately check the defined criteria of a product at speed. Thus providing a solution that can not only improve accuracy but also compliance. By removing the need to complete time consuming manual secondary checks the throughput is increased dramatically.


AI and machine vision working in harmony

While machine vision technology does provide outstanding improvements for the supply chain, it’s enhanced by the integration of AI.

Machine vision complements AI by providing the image data accurately and at the speed that AI needs to make complex decisions, adapt, learn and make intelligent decisions. AI algorithms also enable machines to learn continually. Hence, their performance continues to improve over time.

Integrating machine learning with robotics solutions can provide additional data that allows for streamlining of the process. For example, using machine vision with a robotic arm picking solution gives the robot the data it needs to pick individual items from a tote containing multiple items. Essentially it provides the ‘eyes’ and ‘sensors’ for the robots, and the guidance needed for ultimate efficiency.


Seeing and believing ROI

For all the myriad of benefits it brings organisations working in the supply chain with budgets squeezed many organisations may be fearful of taking the leap. It is important to note that machine vision can be implemented into existing operations with minimal change to the existing infrastructure. The integration to the host is a similar story depending on the level of logic in the solution. Moreover, the flexibility of the solution means that it can be implemented in weeks. While, ROI can be achieved in months.

The benefits from the integration of machine vision with complementary technologies that boost the efficiency of the supply chain are multi-fold and will be transformational to the warehouse environment and the supply chain industry.

By Jamie Mottershead, Technical Director, Renovotec

Featured in:- Future Parity Magazine

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