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6 Ways AI Tools for Manufacturing Are Changing the Game
Artificial intelligence (AI) is revolutionizing a lot of ways businesses run. It is also changing the way we create products and manage our production team. We look at examples of AI tools for manufacturing and how this new technology is altering our processes and increasing production.
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insights from 237,500+ hours of manufacturing marketing experience
In 1913, Henry Ford changed the concept of factories by developing the production line. Instead of a single person with the skill to work on the whole car, he gave unskilled workers one job in creating the finished product.
Today, AI is revolutionizing the manufacturing industry in similar ways. Many see a future where robotics and machine learning are part of the process. Here are some examples of how AI is used in manufacturing:
6 Changes AI is used in manufacturing
Besides robotics, AI has changed the course of manufacturing history in other ways. Here are the top six AI manufacturing examples.
#1 Inventory management
AI offers a number of features that are hugely beneficial to inventory management, like:
- Real-time analytics and measurements
- Data enhanced software
- Accurate stock control
- Improved stock prediction
- Automated reordering processes
AI can understand and learn about how your stock changes and then make predictions about what needs to be updated. It can even notify suppliers for you, so you can maintain leaner inventories and minimize over- or under-stock situations.
#2 Predictive maintenance
It’s no surprise that AI, which learns, processes, and predicts, is an impactful tool for predictive maintenance. Enhancing maintenance technology with AI tools for manufacturing can show when a machine or equipment is likely to fail and recommend services or preventive measures.
The benefit of the prediction is that you can schedule a planned service rather than an unexpected breakdown. There will be fewer disruptions, and the machines themselves will not undergo breakdown stress, which can increase their life span.
#3 Generative designs
Generative design in the manufacturing industry occurs when engineers, designers, and AI come together to create solutions for product designs.
The designer can use the technology to input the design goals for the product, such as the material type, budget constraints, and space or weight limitations. The AI tool will take all that data and then output all the possible designs that meet those criteria.
Each solution will have pros and cons that the client or designer can review and adjust to accordingly. The process can then start from the beginning again with new parameters, or an end result will be finalized.
#4 Cobots for product automation
Collaborative robots, or cobots, are the beginning of robotic automation being accessible for smaller and medium-sized companies. Cobots are usually given jobs that are potentially dangerous for humans or dirty.
#5 Digital twins technology for virtual simulations
Another area in which AI is enhancing manufacturing is digital twins. A digital twin replicates a physical asset in a virtual environment, including its behavior, functionality and features. It uses a number of technologies, including AI.
Digital twin technology uses machine learning algorithms to process large quantities of sensor data and identify data patterns. Artificial intelligence and machine learning (AI/ML) provide data insights about performance optimization, maintenance, emissions outputs, and efficiencies.
AI comes in as it can analyze large amounts of sensor data from the digital twins. From the data, you can identify patterns and give insight into performance optimization.
#6 Project management with enhanced AI
Project management technology has also evolved with AI. In manufacturing, where you have to stick to deadlines and have a number of different teams and departments collaborating, it makes sense for everyone to be on the same page.
AI has been introduced into project management by giving predictive timelines and notifications and automating certain tasks.
4 AI manufacturing tools available right now
A number of manufacturing companies have already implemented AI technology in their daily operations. A few of the best AI manufacturing examples currently in use are:
- Click up: Originally, this software was just a project management tool. However, the developers have added AI to enhance it. Today, it is used by manufacturing companies as a manufacturing project plan. AI has improved productivity and quality control through automation of operations. Processing mapping tools can also link strategic discussion with AI-based execution.
- DataRobot: DataRobot offers a full-lifecycle AI platform. It can do predictive maintenance, quality control and even coordinate the supply chain management. The result is improved efficiency and productivity, two main objectives for any management team.
- GE Additive: On the outskirts, you might think this is similar to DataRobot, but there is a different focus with this software. It can do predictive maintenance and quality control, but it has the added benefit of doing asset performance management. This added feature will improve overall equipment effectiveness at your business.
- IBM Watson: IBM uses AI extensively in its own companies. However, they have also made products that use AI for their clients, including this nifty analytics and cognitive insight platform. You can use it to do intelligent decision-making, help with supply chain optimization, and the usual predictive maintenance. Because IBM Watson IoT uses algorithms to break down sensor data, it will also give insights into workflows.
Are there benefits to using AI in manufacturing?
Now that we have looked at how AI tools for manufacturing, let’s look at the benefits AI technology has brought. Here are a few of the top ones you can expect:
- Energy efficiency: Newer technology, including AI, must uphold the latest regulations for energy efficiency. However, AI can also optimize energy by analyzing data from various parts of the production process. It can suggest or even automate adjustments to reduce every consumption without compromising output quality.
- Enhanced safety: Machine learning can absorb large amounts of data to make predictions and modifications. This procedure can be applied to the manufacturing system and the worker’s environment. The AI can monitor workplace conditions and predict potential safety issues. It can suggest safety protocols for all hazardous situations.
- Agility and scalability: Companies can respond quicker to changes in the market or customer demands due to AI’s ability to predict and sense changes in real time.
What is the best AI tool for manufacturing marketing?
WebFX created a platform, MarketingCloudFX for clients that use AI technology to analyze user behavior and other data insights. We also use AI to uncover SEO enrichment possibilities and optimize sales efficiency.
If you would like to see it in action, check out our successful manufacturing case study. Or, contact us today if you want to integrate AI-enhanced marketing platform forms into your set of tools!
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- 500+ experts in manufacturing
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Table of Contents
- 6 Changes AI is Used in Manufacturing
- #1 Inventory Management
- #2 Predictive Maintenance
- #3 Generative Designs
- #4 Cobots for Product Automation
- #5 Digital Twins Technology for Virtual Simulations
- #6 Project Management with Enhanced AI
- 4 AI Manufacturing Tools Available Right Now
- Are There Benefits to Using AI in Manufacturing?
- What is the Best AI Tool for Manufacturing Marketing?
We Drive Results for Manufacturing Companies
- 500+ experts in manufacturing
- You get a team dedicated to your success


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