Abstract:
In this new age of the fourth industrial revolution manufacturing market has become more
competitive with state-of-the-art technologies. The new technologies are making the
manufacturing process more robust and efficient in nature. Process automation is one of the key
areas where industries can give more emphasis to face the growing challenges of the market. Here
systems embedded with machine vision can play a pivotal role in quality assurance and efficient
process automation. Also reducing the cost of production significantly in all sorts of manufacturing
processes. For the computational purpose, an open-source Linux operated portable credit-cardsized computer is used along with its camera module. The camera is used to capture the images of
the objects and pass the information to the computer. The computer analyzes the captured images
through a machine learning algorithm and detects unwanted objects to removes them from the
production line as part of quality inspection and sorting. The object is defined by its color. Objects
having color defined as defective are removed from the conveyor. This study will provide guidance
for implementing automated color error detection based system to sort defective items in many
fields where continuous evaluation and improvement of the quality are demanded.
