In manufacturing, the tolerance for error is extremely low. This means that while AI can be harnessed to improve the way manufacturing businesses operate, it must be done strategically alongside skilled human workers.
7 ways AI is changing manufacturing
1. Predictive maintenance
Before the advent of AI, machine maintenance was tightly scheduled to minimize the risk of accidental failure. Now, companies can leverage predictive AI systems to customize the maintenance needs of each piece of equipment, creating optimized schedules for individual machines and increasing efficiency without increasing costs.
Milling facilities, for example, often have problems with spindles that break easily, slowing down production and increasing operating costs. However, by integrating AI programs into the software, these plants can keep up to date monitoring to detect potential points of failure before they cause problems.
2. Quality assurance
Using AI to enhance quality assurance practices will not only yield better end results, it will also help businesses determine optimal operating conditions on the shop floor and determine which variables are most important to achieving those goals. This reduces the rate of defects and greatly reduces the waste generated, thus saving time and money.
3. Defect inspection
It is now possible to "outsource" the job of finding defects, thanks to AI's ability to visually inspect items faster and more thoroughly than humans.
The right system can be trained on a relatively small number of images and then deployed to perform the same work that would normally require dozens or hundreds of workers. In addition, it can perform root cause analysis, enabling companies to address potential issues that might otherwise be overlooked, thereby increasing production and optimizing production.
4. Warehouse automation
Consumers are shifting their buying habits to e-commerce, which means warehouse efficiency is becoming a top priority for businesses that need logistics excellence to stay competitive.
Warehouse automation covers everything from implementing AI solutions to process invoices, product labels, and supplier documentation, to leveraging algorithms to optimize shelf space, which can bring a huge ROI to warehouse operations.
5. Assembly line integration and optimization
To truly optimize production and reduce costs requires more than just collecting data from the manufacturing floor. Information must be scanned, cleaned, and constructed in a way that allows for functional analysis. AI can quickly and easily classify and structure aggregated data across an entire facility, giving people an actionable, practical overview of what's happening at every stage of the production process.
This also allows for a degree of assembly line automation, such as reorganizing the production line if one machine fails.
6. AI product development and design
As the technology continues to advance and improve, AI is expected to have the most significant impact on product development and design over the next five years. Manufacturers are already using it for generative design to create innovative prototypes and speed up time-consuming tasks such as meshing and geometry preparation.
7. Small and medium-sized enterprises benefit
The robotics industry is evolving rapidly, so AI-powered robots are becoming less of a novelty and more a part of everyday life in many industries. This is good news for small businesses as it means a wider range of available options at more achievable price points. Previously, only large companies with budgets to invest in research and development and cutting-edge technology could afford to make robots part of their operations.
The future of AI in manufacturing
An effective AI takes two to three years to train on historical data, so the lack of acceptance has left the industry behind. Often, adoption issues are more of an economic one, and this step is the most difficult to take due to the initial cost.
While most operators still prefer to use their intuition and judgment in the field, digital factories can make it easier, safer, and more profitable to replace skilled operators when they leave.
With the global trend towards digitalization and sustainability, the face of manufacturing is changing. Many manufacturers have been reluctant to make the transition, but since change is inevitable, it's better to start embracing AI now than to wait to get behind and catch up.
