Nigeria’s manufacturers can make a fortune from machine vision


“Each bottle of beer passes through an inspection sensor, which triggers a vision system to flash a blinking light and take a picture of the bottle.”


A growing global competitive landscape and evolving customers’ expectations are driving manufacturers to invest new capital in modern technology.

Along with artificial intelligence, deep learning, businesses are also embracing machine vision as the fourth industrial revolution takes firm hold in manufacturing processes.

Machine vision is literally the ability of a computer to see and process information about what it sees. It relates to all industrial and non-industrial applications in which a combination of hardware and software provides operational guidance to devices in the execution of their functions based on the capture and processing of images. It is similar in complexity to voice recognition – the ability of a machine or program to receive and interpret dictation or to understand.

It is important to make the distinction between machine vision and computer vision although they are overlapping technologies. A machine vision system requires a computer and specific software to operate while computer vision doesn’t need to be integrated with a machine.

It is also different from machine learning in that the latter is an application of artificial intelligence that provides data the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning can be used to program machine vision systems in some areas.

Desmond Moru, Computer Vision and Robotics Department, CEIT-1K4 Research Alliance, TECNUN SCHOOL of Engineering University of Spain, uses the example of a fill-level inspection system at a brewery to define machine vision.

“Each bottle of beer passes through an inspection sensor, which triggers a vision system to flash a blinking light and take a picture of the bottle.

After acquiring the image and storing it in memory, the vision software processes or analyzes it and issues a pass/fail response based on the fill level of the bottle. If the system detects an improperly filled bottle i.e. a fail, it signals a rejection of the bottle. An operator can view rejected bottles and ongoing process statistics on a display simultaneously.”

How it works

By using one or more video cameras, analog-to-digital conversion (ADC), and digital signal processing (DSP), a machine vision system produces data that gets sent to a computer or robot controller. The data sent is based on the set-up process, whereby one “teaches” the machine-vision system, defining what is good or bad, or outside of limits. The camera/computer visually looks at a part and is programmed to indicate whether the process should proceed, stop, or adjust. If it is outside of boundaries, the program is triggered to throw up a flag.

A few global manufacturing facilities have used machine vision systems since the 1950s, but it began to expand in the 1980s-1990s.

A BCC Research data gives an idea of how big the space is, by pegging the global market for machine vision system components at $19.0 billion for 2016 and an estimated $30.8 billion by 2021.

For Nigeria manufacturers’ spend on technology has often competed with the rising cost of production and foreign exchange volatility. The bulk of the manufacturing establishment in Nigeria is located in the urban area with epileptic national power supply, whereas, the source of the raw materials which is the rural areas are devoid of essential facilities and poor road networks for the easy conveyance of raw materials to the urban centres. The result is the high cost of production.

Culled from BusinessDay

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