Sustainability is without a doubt one of the most widely discussed topics of recent years. Since manufacturing is associated with depletion of resources and overall negative impact on the environment, 21st century producers need to rethink many concepts to adapt to the requirements of sustainable business practices. Besides being crucial for maintenance of the healthy environment conditions, sustainable manufacturing pays off in a company’s increased efficiency and competitiveness. 

Major manufacturers around the world give special attention to implementing sustainable workflows to their production processes. In a study of the Boston Consulting Group, 92% of the companies surveyed said they have either implemented or plan to implement the elements of green manufacturing [1]. Such companies as LG Electronics, BMW, Schneider Electric and Peugeot are among top ten sustainable manufacturers [2], demonstrating how green production practices correspond to successful business performance.

One of the most important strategies for sustainable production is automation of processes. Recent studies have shown that automation of quality control in the manufacturing plants positively affects the productivity of the company and minimizes its environmental footprint [3]. Automated visual quality assurance has proven to be a relevant component for sustainable manufacturing. Based on the latest Deep Learning technologies, the automatic quality inspection solutions perform visual quality control with almost 100% accuracy. 

AI-based quality assurance increases the sustainability of the manufacturer in all respects. First of all, the defective products are detected early in the production process, which results in reduced waste. With the newest development of visual quality assurance (, the inspections on the whole production line can be conducted by a single camera without any physical connection to the plant. This makes the manufacturing process hundreds times more energy efficient compared to using classic quality inspection tools. Furthermore, fully automated visual quality inspection brings an important social impact to the manufacturing companies. Automation of the fault detection process relieves workers from the monotonous workflows and enables them to perform tasks according to their level of education.

With all that said, the benefits of quality automation for manufacturers are clear. It ensures environmental and social sustainability reflecting the economical benefits for the company. Reduced waste and efficient energy consumption have a direct positive economical impact. However, the social aspect brings as much economic value for the manufacturer as the environmental one. The employee, freed from monotonous tasks, works much more efficiently and with greater concentration [4].


[1] Berns, M. (2009): BCG Report: The Business of Sustainability. The Boston Consulting Group.

[2] Chibelushi, W. (2020): Top 10 most sustainable manufacturing corporations in the world (

[3] Makky, M., Soni. P. (2013): Towards Sustainable Green Production: Exploring Automated Grading for Oil Palm Fresh Fruit Bunches (FFB) Using Machine Vision and Spectral Analysis. In: International Journal on Advanced Science Engineering Information Technology. 3(1). P. 1-8.

[4] Loukidou, L. et. al. (2009): Boredom in the workplace: More than monotonous tasks. In: International Journal of Management Reviews. 11(4). P. 381-405.

by | Mar 2, 2021