Innovation has always been key to the manufacturing sector’s success. However, current developments in artificial intelligence (AI) are accelerating transformation at a rate never seen before.
Artificial Intelligence-driven digital solutions are revolutionizing all facets of manufacturing, ranging from inventory control to manufacturing floor procedures. This change is altering not just efficiency but also the design, production, and delivery of products.
However, the World Economic Forum states that around 56% of manufacturers are still experimenting with AI use only in small-scale projects. Moreover, only 28% of the survey respondents have passed the pilot stage of the implementation. You can stand out from the competition by implementing AI to transform your manufacturing operations.
In this article, let’s explore some ways in which AI is transforming manufacturing with its digital solutions.
Smarter Production Lines
Automation has long been a staple of manufacturing productivity, but artificial intelligence (AI) elevates the game by allowing robots to learn and adapt. AI-powered automation systems are able to assess large volumes of data and make choices instantly. On the other hand, traditional automation systems adhere only to preset protocols.
AI-driven robots, for instance, are now able to modify their motions in response to real-time data, which lowers mistakes and improves precision. Lower operating expenses and better-quality products are the results of this.
A PYMNTS article gives an example of using AI robots in an automotive manufacturing company based in Boston. It states that the company has revealed its AI-driven factory robot, named ‘kilo.’ The robot has a load capacity of up to 130 kilograms. It uses sensors and 4D radar imaging technology along with AI to follow workers and navigate the factory with over 100 predefined routes.
Furthermore, another use of AI is predictive maintenance, which assists in anticipating equipment failures before they occur. AI algorithms can forecast when machines require repair, averting expensive downtime by evaluating previous data and real-time sensor inputs.
How can AI help in production?
AI is capable of processing data from vibration, thermal imaging, and oil analysis to evaluate the condition of machines. Manufacturers may also precisely and effectively forecast the downtime that will impact production scheduling and associated operations by using insights from artificial intelligence (AI). For example, they can replace parts that may potentially fail or have them stocked in the inventory.
AI-Driven Decision Making
The potential of AI to improve decision-making processes in manufacturing is among its most revolutionary features. Every day, manufacturers have to make innumerable decisions about everything from inventory management to production scheduling.
Historically, these choices were frequently made without access to real-time data, relying instead on human intuition and experience. Manufacturers may now make data-driven choices faster and more accurately.
As noted by MCA Connect, AI-powered decision-making is the brainchild behind this revolution. Manufacturers can now predict equipment failure, schedule autonomous maintenance, avoid costly downtime, etc., with the help of artificial intelligence. Moreover, they can even manage supply chain disruptions, which are a constant worry, more efficiently.
According to Harvard Business Review, AI can help leaders make important decisions under pressure. Data shows that around 85% of business leaders have felt stress while making critical decisions. Digital solutions like data analytics and business intelligence platforms powered by AI can help relieve this stress by bridging the data-insight gap.
Enhancing Quality Control
AI’s influence on manufacturing is particularly noticeable when it comes to quality control. Manual quality checks have been done historically, which takes time and increases the possibility of human mistakes. AI has made it possible for manufacturers to deploy computer vision systems for real-time product inspection.
These artificial intelligence (AI) technologies are able to identify even the smallest flaws that the human eye would overlook. They make sure that defective items are discovered before they are delivered to customers.
They can also help gather information that is useful in identifying patterns in the quality of the products. The production process may then be constantly improved by using this data to eliminate errors and raise overall quality.
A Deloitte article states that computer vision can also be used for factory synchronization and dynamic scheduling. This solution uses loT, or cameras positioned throughout a building, to follow the flow of products and materials in real-time.
The purpose of this information syncing is to allow for the dynamic scheduling and resource allocation of other production systems. This use case has led to increased Overall Equipment Effectiveness (OEE), decreased inventory, and enhanced agility.
How does AI contribute to quality control in manufacturing?
AI in quality control for manufacturing can offer speed, precision, and automation that is unmatchable by traditional methods. Manufacturers are able to increase product quality, decrease faults, and maintain high levels of productivity thanks to the combination of AI and machine vision.
Streamlined Supply Chains
Effective management of global supply chains is challenging due to their complex nature, which involves numerous factors and interconnections. But AI is really good at managing sophisticated systems.
Artificial Intelligence (AI) can assist enterprises in predicting supply chain disruptions before they happen by evaluating historical data and current market conditions. AI gives producers the information they need to swiftly modify their plans, whether it’s anticipating raw material shortages or identifying possible delivery delays. This enables businesses to continue running smoothly and stay ahead of obstacles, even in the face of unforeseen setbacks.
A 2022 McKinsey & Company survey found that AI has the most revenue increase potential in supply chain management. Around 52% of the respondents said that implementing AI decreased supply chain management costs while increasing revenue. Similarly, the recent survey by the company found that the Generative AI boom has resulted in a 5% revenue increase in supply chain management.
How can AI streamline logistics operations and reduce costs?
By streamlining procedures and lowering the demand for human labor, artificial intelligence (AI) may lower the cost of logistics. For instance, by anticipating demand and maximizing inventory levels, AI might assist logistics organizations in lowering inventory costs. Similarly, it can also help detect optimal routes for deliveries to reduce costs associated with fuel usage and wasted time.
Although the use of AI in manufacturing is still in its infancy, there is a great deal of room for expansion. We will witness even more sophisticated uses of AI technology as it develops. The advantages of manufacturers adopting these digital technologies are many and obvious. AI is making manufacturing smarter, more adaptable, and more sustainable. It is opening the door for a time when production processes will be just as dynamic as the industries they support.
