Artificial intelligence has been making waves in the manufacturing industry for some time now. Early adopters of AI technology have seen significant improvements in productivity and efficiency, and the trend is only set to continue.
In fact, with the continued development of artificial intelligence in manufacturing and companies like Google, Apple, and Facebook making significant investments in AI, the possibilities of where this technology can take us are endless.
But if you are still wondering where we go from here, let’s look at some of the most recent developments in AI for manufacturing and its potential in this blog post.
Table of Contents
Artificial Intelligence: A Brief Introduction
Artificial Intelligence is a term used to describe machines and programs artificially incorporated with human-like abilities to perform various tasks. This intelligence is built with the help of complex algorithms and mathematical functions. Cars, smartphones, social media feeds, video games, banking, surveillance, and many other aspects of our daily lives use AI.
- Cars have sensor technology that collects data about how people drive (and pollution levels)
- Smartphone manufacturers use AI in functions like speech recognition
- Social media feeds show posts based on what users’ interests may suggest
All thanks to algorithms designed by math functions alone.
Use Cases of AI in Manufacturing
AI in manufacturing is used to analyze sensor technologies and internet of things (IoT) technologies to gather and store data to understand how production output can be improved and made more efficient.
The technology is also employed to enhance the individual user experiences via augmented reality technologies that assist in-field workers in performing their duties or supporting their health and safety.
AI supports manufacturers to ensure they wear the appropriate personal protective gear and assists them throughout the operational process. In short, Artificial Intelligence provides that entire operations are safe.
Amazon & Walmart (Warehouse Maintenance)
AI-powered robots are becoming increasingly common in factories around the world. These machines learn from their surroundings and make decisions based on data, allowing them to work alongside humans or even take on tasks that are too dangerous for people.
One example of AI-powered robots is Kiva Systems’ warehouse robots, used by companies such as Amazon and Walmart. These robots can navigate a warehouse and pick up items that need to be shipped to customers.
Baker Hughes (Preventive Maintenance)
Baker Hughes, one of the world’s largest oil field services companies, harnesses Artificial Intelligence to identify maintenance issues. The American company collaborated with Microsoft Azure and an AI company called C3.ai to build an AI-based app for its resources to view real-time production data, estimate future production, and optimize operations for improved production rates.
The developed application uses machine-learning (ML) algorithms to accumulate historical and actual-time data across manufacturing operations & creates a virtual representation of production across the value chain. The app also detects anomalies, forecasts production, and prescribes scopes for improving production performance.
Tomoni (Plant Productivity)
Tomoni, a digitalization platform from Mitsubishi Power, encompasses controls, instrumentation, data analytics, Artificial Intelligence, etc. The suite of intelligent solutions is aimed at making plants smarter. The average Mitsubishi power plant has about 10,000 sensors that generate over a million data points every minute. Tomoni collects various data and arranges it into a usable form.
Tomoni is helping Mitsubishi create an increasingly intelligent facility that will be able to perform various levels of autonomous operation. An increase in digitization of interconnected devices & systems enables control systems to achieve more with advanced analytics.
Sentry Equipment (Product Design)
Sentry Equipment, an original equipment manufacturer, based in Oconomowoc, WI evolved its SentryGuard sampling machine using AI. SentryGuard guides operators using the Aveva System Platform to save development time. The sampling machine analyzes sample data, provides alerts, and guides operators to resolution.
Google (Google Photos)
The most famous example of artificial intelligence being put into use was when Google created its app called “Google Photos.” This program learns from user behavior patterns over time, so it becomes smarter each day without any human intervention.
How can Manufacturing Businesses Leverage AI?
While no organization may start garnering exceptional results from AI immediately after embracing it, the technology can certainly enhance and transform traditional manufacturing processes. We highly recommend the meaningful usage of AI for game-changing business outcomes.
The following are some of the readily available AI & MI solutions used by manufacturers today:
The technology is widely used to identify employees, conduct thermal screenings, conduct contact tracing, and perform facility sanitization. The technologies can also find long-term solutions associated with workplace safety events. These solutions lead to a safer work environment, healthier employees, and productivity.
Building Management and Physical Security
Manufacturing businesses often struggle to balance the costs and the requirements for live security teams against safeguarding company assets and employees. Most overlook traditional physical security, risking the safety of their facilities and employees. With advanced CCTVs, building management systems, and artificial intelligence, implementing security solutions that recognize common security scenarios, including visitor or delivery vehicle arrival or theft, is now more affordable.
The industrial sector has been a major target for cyberattacks in recent years. A new report from Cambridge, Massachusetts, shows that manufacturing is the most targeted industry by cyber attackers.
Given the importance of industrial manufacturing to economies worldwide, it’s no surprise that cybersecurity is a top concern for manufacturers. Artificial intelligence can play a crucial role in helping to secure industrial manufacturing facilities and systems.
AI can monitor industrial control systems (ICS) for anomalous activity that could indicate a cyberattack. Also, it can analyze data from ICS to identify patterns to improve security and create virtual models of industrial facilities for training and testing security protocols.
AI can reduce the false positive rate of security alerts and help to reduce the amount of time and resources spent investigating potential threats. Furthermore, it can help organizations proactively identify potential cyberattacks.
AI can play a vital role in predictive maintenance. By analyzing data from sensors and machines, AI can predict when a machine is likely to break down and needs repairs. Using this data, manufacturers can avoid costly downtime and schedule maintenance at a more convenient time.
In the future, AI is likely to become even more important in manufacturing. As the technology continues to develop, we expect to see more factories using it to improve their operations.
AI is playing a key role in making manufacturing more sustainable. By reducing waste and optimizing resources, organizations can reduce their environmental impact. In addition, AI can be used to develop recycling and reuse programs that minimize the need for new raw materials.
One of the biggest benefits of AI for manufacturing is its ability to reduce costs. Organizations can free up their employees to focus on more value-added activities by automating repetitive tasks. Also, Artificial intelligence can identify cost-saving opportunities throughout the supply chain.
Hurdles to Cross Before AI Becomes More Prevalent
Artificial intelligence has the potential to revolutionize the manufacturing industry. By automating tasks, providing new insights through data analysis, and optimizing production processes, A
It helps manufacturers increase efficiency, reduce costs, and improve quality. In fact, according to a McKinsey report, AI could add $1.2 trillion to the economy by 2030.
However, while many manufacturers are eager to adopt AI, they face significant challenges. One of the biggest challenges is finding the right talent. Manufacturers need to hire AI developers with the right skill set to develop and implement AI solutions.
There is a global shortage of AI talent. According to a recent survey by Element AI, only 22% of organizations believe they have the talent they need to implement AI.
To train AI algorithms, manufacturers need high-quality data sets. Data in many organizations are siloed, making it challenging to obtain the necessary data for training. Also, data collected by different machines or parts of the manufacturing process may be incompatible.
Despite these challenges, manufacturers are still investing in AI.
In a recent Deloitte survey of global manufacturing executives, 43% of respondents said their companies were already using AI or piloting AI projects, and another 18% said they planned to do so within the next 12 months.
The numbers suggest that manufacturers believe AI will play a significant role in the future of manufacturing and are working to find ways to overcome adoption challenges.
Frequently Asked Questions
Q1- How can I hire Artificial Intelligence developers?
You can hire AI developers through online job platforms such as Upwork or Freelancer. Online job boards such as Indeed or Dice are excellent platforms for finding professionals. Alternatively, you can contact artificial intelligence development companies to discuss your project requirements.
Q2- What type of AI is used in Manufacturing?
Different types of AI can be used in manufacturing, including:
Machine learning: This AI allows machines to learn from data, identify patterns, and make predictions.
Natural language processing: It enables computers to understand human language.
Robotics: Robotics involves the use of robots to carry out tasks.
Predictive analytics: It uses data to make predictions about future outcomes.
Q3- How do I include AI in my manufacturing business?
The key to incorporating AI into your manufacturing business is to start with a goal. What problem are you trying to solve, or what opportunity are you trying to capture? If your answer is artificial intelligence, then ask yourself why. The answer will lead you to a specific use case for AI—something like computer vision to improve uptime. The next step is learning about available technologies and considering if they can be used for your business goals.