Top 10 ways to utilise AI in smart manufacturing
Manufacturing Global details 10 ways in which artificial intelligence (AI) can be harnessed by manufacturers to drive smarter manufacturing.
Predictive maintenance
One of the largest use cases — Predictive Maintenance. In 2018 the technology made up over 24% of the total market. Predictive maintenance harnesses advanced analytics and machine learning to determine the condition of both a single or entire set of assets, to determine the remaining useful life of an asset.
Quality
At 20.5%, quality inspection and assurance is the second largest industrial AI, with automated optical inspection showing as the largest subcategory.
This technique uses computer vision technology to autonomously scan devices for catastrophic failure and/or quality defects, driving cost and test time reductions.
In a recent report by BOSCH, the company reported a 45% reduction in time to test, and a US$1.3mn cost savings as a result of AI.
Manufacturing process optimisation
The concept of harnessing robotics and autonomous machines to replicate monotonous human tasks within the manufacturing process, this technology uses reinforcement learning techniques to train the robotics and autonomous machines to achieve sufficient accuracy.
Supply chain optimisation
Utilising AI for predictive inventory management. This technology harnesses predictive analytics to reduce inventory planning time, minimise inventory cost, optimise repairments and find optimal reorder points.
Cyber security and privacy
AI driven cybersecurity and privacy typically involves the automation of observing a network’s infrastructure and detecting threats in real-time, and is often part of a larger cybersecurity strategy and solution.
Other features include: network traffic analysis, endpoint detection and response and malware sandboxes
Robotic physical surveillance
Another form of robotics within the supply chain and manufacturing sector is the use of automated robotics to conduct surveillance of physical sites to detect security threats. An example of this is XPO Logistics’ C3-XPO.
Data management
Within the manufacturing sector a vast quantity of data is produced daily, with this in mind organisations are harnessing AI data management solutions to perform tasks such as data acquisition, data filtering, data cleaning, data integration and data analysis in real-time.
Smart Assistance
Perhaps one of the more common technologies, many manufacturers are harnessing voice assistants. Organisations are integrating voice assistant technology into real-time industrial monitoring systems. This allows workers to gain insights without coding specific commands.
Design
Within the manufacturing industry, automated component design is one of the most common uses of AI in research and development. The aim is to have software independently develop dozens of designs in a short period of time to discover the optimal design. Common AI technology used for this are digital twins and simulations.
Exploration
Particularly seen within mining, quarrying, oil and gas industries, organisations are harnessing AI and automation for resource exploration. To analyse and determine the optimal point for resource extraction. This is especially useful in difficult to access areas such as the ocean subsurface or mountains.
For more information on manufacturing topics — please take a look at the latest edition of Manufacturing Global.
