10 AI innovations impacting the manufacturing industry
by Doug Walker, Editor
Doug Walker provides 10 ways artificial intelligence innovations are impacting the manufacturing industry.
10 AI Innovations impacting the manufacturing industry (Credit: jesterpop on Shutterstock)
The manufacturing industry is the largest sector using artificial intelligence for efficient production workflow and real-time market insights. According to projections, the size of the manufacturing market using AI will be $4,798 million by 2026.
The current stage of manufacturing industry evolution, Industry 4.0, is based on Fourth Industrial Revolution (4IR) technologies, including machine learning, Internet of Things (IoT), automation, and augmented reality.
For industry stakeholders looking to invest in the lucrative AI-powered manufacturing industry but still skeptical on how to do that, here are 10 artificial intelligence innovations impacting the manufacturing industry.
- AI-enabled quality assurance
Quality assurance is an important aspect of the manufacturing industry, as it is essential that products meet key functional requirements and safety standards. Traditionally, quality assurance of every industrial product from electronics to pharmaceuticals to automobiles is carried out manually by highly skilled professionals.
Manual quality assurance demands high precision, attention to detail, and a significant amount of time.
AI-enabled quality testing using image recognition can increase the defect detection rate by 90% compared to manual testing.
- Predictive equipment maintenance
Timely machinery maintenance in the manufacturing industry is essential to productivity and maximised workflows. Unexpected downtime of manufacturing tools can lead to unwanted delays and business losses.
In fact, businesses suffer a loss of $50 billion annually due to unplanned downtime. Moreover, 46% of the time, the reason for the downtime is a technical fault in manufacturing machinery.
Artificial intelligence is proving useful in forecasting equipment defects so predictive maintenance can be carried out before costly problems occur.
- Automated inventory management
AI can be utilised to automate inventory management. Machine learning algorithms can help with monitoring supply and forecasting sales. Instead of manually tracking products or materials, automated management can save time and the associated risk of error.
According to a report by McKinsey, AI for inventory management can save manufacturing businesses from sales forecasting errors and overstocking inventory by up to 50%.
- Collaborative robots
Previously, robots were programmed to work on a single task only. But collaborative robots, or cobots, are equipped with the latest AI technologies like deep neural networks and can be reprogrammed to take on diverse tasks like CNC machining, packaging, and plastic injection molding while working safely alongside humans.
- AI-enabled supply chain management
Supply chain management is a crucial part of any manufacturing business. As businesses expand, the logistics of sourcing raw materials and fulfilling purchase orders daily can become a daunting task. To support this need, AI-powered supply chain management systems are efficient and smart.
Technologies like machine learning and natural language processing help develop tools and software that enable manufacturers to optimise their production supply through automation.
- Generative design
Generative design helps product designers in exploring different product designs virtually according to their resource constraints. Industrial designers input the design goal, set the design parameters like production material and manufacturing constraints, and the AI system outputs several design models.
- Digital twin
A digital twin is a digital representation of a physical product developed using AI technology. Digital twins of products help manufacturing professionals carry out virtual simulation scenarios in the production phase.
IoT technology is used to collect data from integrated sensor components, which is then fed to the AI system for processing, performance analysis, and future simulations.
According to Gartner, 13% of IoT-based industries use digital twins.
- AI-powered customer service
A lot of industries, including retail and healthcare, have adopted AI-powered customer service. The manufacturing industry is also reaping the benefits of AI-powered customer service through personalised customer experiences and the use of chatbots.
AI chatbots help manufacturers provide customer service to a large number of customers at once.
- Big data management
One of the prominent AI innovations in the manufacturing industry is data management. With digital data increasing day by day, an AI-based system provides all the right tools to gather, analyse, and utilise data for business profit and growth.
Predictive analysis and data analytics are used together with IoT technology to gather useful data from sensors and cameras. The data is then used to predict and improve resource utilisation, customer satisfaction, IT issues, etc.
- AI cybersecurity
Smart manufacturing units with IoT-based equipment have become more exposed to cyber threats. Cyberattacks on a single production line only can cause a huge loss. However, AI is used today to safeguard the smart manufacturing environment from online attacks.
AI algorithms for risk detection and attack prevention mitigate cyber threats by alarming the cyber security team the moment an attempt is made.
