AI in Manufacturing: Top Use Cases and Examples

Is AI in manufacturing, transforming the future factories? As manufacturers globally continue seeking for ways to streamline their manufacturing production and other day-to-day operations, Artificial Intelligence has emerged as a game changer. Artificial Intelligence has quickly spread from consumers to businesses, boosting productivity to strengthening processes.

But the question is “How AI Is Impacting the Manufacturing Industry?”

The simple answer to this question is, “it brings a noticeable change in manufacturing with its transformative capabilities”. And leading factories and businesses have already recognized the upside benefits of this technology. 

But, its power is not just limited to them. Even small to mid-level of businesses need to realize how easy it is to leverage the capabilities of AI to enhance efficiency, operational accuracy, and production across various processes. 

According to the reports, the manufacturing industries inventing into GenAI are expected to generate “additional revenues with a significant spike of $4.4 billion from 2026 to 2029. GenAI in manufacturing will reach $10.5 billion. 

The straight question arises here, what exactly is the role of “GenAI in Manufacturing” to make it rise like a rocket?

The top reasons cited by manufacturers using GenAI are that it helps identify the root cause of production issues faster than our usual procedure of diagnosing the problems. Moreover, it provides a “faster creation of work instruction” and “improved workforce coding skills”. 

Another report from Deloitte says that the manufacturing industry is at the forefront of using AI capabilities such as predictive maintenance, supply chain optimization, and quality control. Moreover, it offers a transformative approach to handling traditional processes.

So if you’re into manufacturing and trying hard to drive growth, then embracing AI in manufacturing operations to analyze the amount of data generated in the sector to unlock new business opportunities. 

Impact of AI in Manufacturing on the Manufacturing Industry

Though we read a lot about Artificial Intelligence in Manufacturing, let’s quickly talk about the major benefits of implementing AI in manufacturing… 

• Did you know, the company’s production capacity drops between 5 to 20% due to poor equipment maintenance? Unplanned downtimes can cost an estimated $1 trillion every year. This is where AI-powered systems can go a few miles extra in analyzing machine data to predict maintenance needs, reducing downtime and preventing costly breakdowns. 

• The mobile apps developed dedicated to larger factories or business units are integrated with “Computer Vision” features that quickly detect defects in products in production and minimize the risk of human error. Overall, with AI-integrated solutions, quality controls become easily manageable in manufacturing units. 

• Supply chain optimization is one of the most challenging tasks in manufacturing, but AI can help you forecast the bigger picture of your supply chain. It enhances demand forecasting by constantly monitoring the production flow, helping in inventory management and logistics, and ensuring smoother and more efficient supply chains.

• With the adoption of AI in manufacturing, automate repetitive tasks with AI-driven robots. It greatly helps in increasing efficiency and reducing operational costs. But to make it work rightly you need to hire a mobile app developer using a proven strategy. 

• Next, AI helps in optimizing production schedules by analyzing workflows, demand, and resources to minimize delays and maximize output.

• Custom product designing becomes easier with AI in manufacturing. AI shortens the design process by generating customer-specific designs and prototypes and allowing for rapid production iteration. 

Before you get straight to hire an artificial intelligence app development company to incorporate all these benefits into your business system, keep in mind that there is a huge difference between expectations and implementation. 

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Is Implementing Artificial Intelligence in Manufacturing Works?

Well, Artificial Intelligence is ensuring various benefits to industry across verticals and manufacturing is not an exception. But it all depends on the process of implementation.

There are several Chinese Manufacturers, who considered implementing AI in Manufacturing, but 91% of these AI projects failed to meet expectations in terms of their benefits and time invested into it. 

So the worth of implementing AI in manufacturing can be affected greatly due to;

• Traditional workflows that are resistant to change, can slow down the AI adoption and integration.

• Infrastructure limitations and inadequate IT infrastructure with outdated machinery may hinder the implementation of AI-driven systems.

• Poor data quality or insufficient data collection can limit AI’s ability to generate accurate insights into manufacturing.

• Hiring an AI app developer with inappropriate skills can delay AI deployment and optimization. 

In a nutshell, coming to the other side, 83% of companies have realized that AI has made or will make a practical and visible impact. In addition to this, 27% of big manufacturers have already brought value to their companies, and 56% think that their project will bring value in 2-5 years. 

Moreover, 66% of manufacturers incorporate AI into their daily operations reporting and their growing dependence on this GenAI technology, highlighting an accelerating trend toward AI adoption in the manufacturing sector. 

If you’re ready to learn how AI in manufacturing is transforming the industry landscape, then delve into the various use cases and examples representing how integrating AI into manufacturing can turn your business into smart manufacturing. 

How AI In Manufacturing is Transforming The Industry Landscape: Use Cases and Examples

Have you ever imagined a world where machines and humans collaboratively work on the manufacturing floor? Artificial Intelligence has made it possible by scrutinizing mountains of data to help manufacturers prevent breakdowns before they occur. That’s not all, there are captivating realities that AI brings to manufacturing. 

Here are the use cases and examples of AI in Manufacturing:

1. Cobots or Autonomous Mobile Robots (AMR)

The popular use case of AI in manufacturing is using Collaborative Robots (Cobots) or AMRs that help in enhancing productivity by collaboratively working with the human workforce.  These are basically used at the fulfillment centers where product picking and packing are required. These Cobots work with humans, navigating intricate areas and identifying objects with the help of AI systems. 

The biggest example is Amazon, which has deployed over 750,000 robots working with employees, identifying and storing inventory at fulfillment centers up to 75% faster than companies are doing it today with manual processes. 

Implementing AI-driven Cobots has made Amazon improve its shipping predictability and increase the number of products that can be offered for same-day or next-day shipping.

2. Optimizing Supply Chain Management

Artificial Intelligence can be a game changer in optimizing supply chain management. But to harness the best power of AI for managing the supply chain, would require you to hire mobile app developer to improve efficiency, accuracy, and cost-effectiveness. 

It enables you to leverage predictive analytics, optimize inventory management, enhance demand forecasting, and streamline logistics in the supply chain. 

Now how does AI work in optimizing supply chain management?

AI-integrated mobile apps work with machine learning algorithms that analyze historical data, identify patterns, and accurately predict demand fluctuations. 

For example, if you are into automotive part manufacturing but not sure what parts would have increasing demand in the future. This is where using the ML model will help in forecasting demand for spare parts, allowing them to optimize inventory levels and reduce cost.

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3. Predictive Maintenance

Predictive Maintenance is going to be a major AI use case, that has already been tested by a handful of manufacturers, owing to the mobile app integrated with AI capabilities. 

Leveraging advanced predictive Analytics and machine learning algorithms could reduce maintenance costs by up to 30% and unplanned downtime by 45%, PWC.

AI in the manufacturing industry, allows manufacturers to proactively monitor and predict equipment failures, minimizing downtime and optimizing schedules. Using this advanced technology can help extend the equipment’s lifespan and reduce the risk of disrupting production. Therefore to make your entire process work flawlessly as you have envisioned, it is important to hire mobile app developers with the right strategy. 

Learn here how much it costs to hire mobile app developers in the USA.

4. Streamlining Purchase Cycles

To keep your manufacturing process running flawlessly, you must have a sufficient level of inventory. Keeping track of raw materials components in a warehouse with manual processes is always challenging. This is where Alcax enables you to hire remote AI developers in the USA to use AI capabilities to look at the historical data of how much raw material costs and orders in the past and can suggest the best time for rolling out the next order. 

AI can be used to streamline warehouse operations, ensuring the right levels of inventory and making sure that duplicate components are not being purchased.

5. Quality Assurance and Defect Detection 

Increasing operational efficiency is one thing but optimizing the quality of production is another challenge that manufacturers have to deal with. AI in manufacturing is revolutionizing the quality assurance and defect detection process by simply enabling real-time monitoring and analyzing the production lines.

Wondering, how exactly it work?

Well, our on-demand logistic app solutions are integrated with machine learning algorithms and computer vision technology, which allow AI systems to detect even the smallest defects in products, identify patterns in failures, and ensure consistent quality standards.

Conclusion

The impact of artificial intelligence technology is going to be stronger on various industries and manufacturing businesses are not an exception. As its highlighted above in the blog, the revolutionizing role of AI in manufacturing is an alarming time for manufacturers to take a steep look into adopting AI technology. From supply chain management to predictive maintenance, and using Cobots to detect defects, integrating AI in manufacturing can help greatly in improving efficiency and enhancing accuracy. 

To reap the best impact of artificial intelligence in manufacturing, you need to hire an AI app development company , that can handle the complex requirements and able to automate the process.

This is where Alcax stands as a top mobile app development company in USA that deeply diagnoses your business process identifies the scope of improvements and then builds a strategy to modernize the various aspects of your manufacturing business using AI capabilities.

If you are all set with your requirements, then choose our AI consulting services or contact us directly to discuss your project details and estimations further!

FAQs 

Here we have some frequently asked questions and answers that businesses might have regarding implementing AI in manufacturing systems.