4 MIN. READ
Artificial intelligence (AI) to the general public usually brings to mind sentient robots such as those seen in science fiction movies.
For manufacturers, AI currently means software and machines that reduce waste, increase efficiency and enable novel new methods of producing goods.
But make no mistake: the rate of progress in the field suggests that reality is quickly catching up to cinema.
Rapid Implementation
The spread of AI-enhanced devices in industrial manufacturing is exponential. Some research firms are predicting that by 2024, over 15 million of these AI devices will be in use worldwide.
Growth rates are also expected to reach 65% during that period. As the benefits of machine learning and intelligent algorithms become even more publicized, expect to see these figures trend upward.
Data Management
The data that is collected and studied by AI systems is overwhelmingly stored on either local servers or on the devices themselves.
Manufacturers are not convinced that public cloud servers can provide the security to not only guard their sensitive data, but prevent hacking attacks that may hijack equipment or disrupt their operations.
Such storage methods are referred to as edge implementation. Chipset manufacturers are aware of this factor and have created specialized AI-enabled servers.
These servers make it easy for companies to integrate AI with existing infrastructure while still maintaining close control of their data.
Predictive Repairs
The most common forms of AI utilized by manufacturers are predictive, monitoring and defect detection software.
Production downtime can cost thousands of dollars per minute on some lines. Industry-wide, an estimated $50 billion annually is lost due to unplanned downtime.
Therefore, any system that lets a company know in advance what components require maintenance is a huge benefit.
Machine learning combined with algorithms predicts when assets require maintenance or replacement. These systems can also schedule repairs to coincide with reduced production times so that there is minimal impact to the business.
Some systems even suggest the required tools and procedures, helping the repair crew save even more time. Currently at least 16 million devices perform these tasks at manufacturing plants around the world.
Efficiency Algorithms
Predictive software can be paired with analytical software to maximize efficiency across entire facilities.
San Francisco-based Sight Machine offers a platform that studies real-time data from a manufacturer, creates a digital "carbon copy" of the entire company and then pinpoints ways procedures can be modified.
Its system has been used by industry giants such as Nissan, Nike and GE.
Along the same lines, SparkBeyond also utilizes prediction and analytics; however, it expands beyond the manufacturer's walls to include all sorts of global information in its research.
In addition to commonly analyzed data such as production rates and costs, it also includes weather, World Bank data and geospatial inputs.
These external inputs can tell a manufacturer whether foreign sources' raw materials are about to go up in price or if severe weather will likely affect shipments.
Quality Control and Design
Customers expect products to be as close to perfect as possible. AI assists in this quest by monitoring and alerting managers of changes in parameters that could negatively affect quality.
These parameters may include temperatures, pressures, machine performance/faults, deviations from ideal conditions and variations in raw materials' characteristics.
This feature is invaluable in industries such as aerospace engineering, where control over a component's life cycle is not just a matter of regulations, but of safety.
In some cases, AI is being given the reins to find the best possible solution for existing products. Using generative design software, designers can create a set of constraints and goals to achieve, then let AI search for unique solutions.
An advantage of AI in this role is that it has no bias or preconceived notions of "how it should be done." Iterations can be repeated until a design that fits the requirements is perfected.
Industrial Robot Safety
Robots are a growing part of the AI revolution. At the end of 2018, there were an estimated 1.3 million industrial robots in plants worldwide.
Due to concerns about safety, companies have adopted industrial robots and embraced AI to mitigate risk to human workers. Veo Robotics achieves this by enabling its robots to continuously surveil and monitor their surroundings. In the event that they detect a human or recognize a mechanical or software error, they will shut down by default.
This makes working side by side with robots a safe activity for humans rather than one where a misstep can cause injury.
As AI continues to improve, some fear that machines will take all the available jobs. While some positions will go away, other opportunities will present themselves.
Intelligent Data
Humans will still be needed for decision-making, and decisions are easier to make when you have the right information.
IndustryNet is an industrial marketplace that provides detailed information on 400,000 U.S. manufacturers and suppliers of more than 10,000 parts and services. Request quotes, get in contact with key personnel or simply see where providers are located. Expert researchers work to provide the most up-to-date information.
All data is analyzed and compiled by humans so you can be sure you're getting accurate information. IndustryNet also offers marketing solutions to improve visibility for industrial buyers. Learn more about IndustryNet's marketing solutions.
