Role of AI in Manufacturing industry: Top Use Cases, Benefits, and More!

Undoubtedly, to compete in the current global market, manufacturing businesses must streamline every aspect of their operational procedures, from order management and supply chain to designing, planning, and logistics.   

Because of this, manufacturers are investing in cutting-edge technologies like artificial intelligence. Thanks to much data, manufacturing ecosystems are redefining how commodities, small firms, and supply chains are connected. 

You won't believe it if we tell you that, 

As per the research, the market for artificial intelligence in manufacturing was valued at USD 1.82 billion in 2019 and will grow to USD 9.89 billion by 2027, with a CAGR of 24.2 percent. 

Huge! Isn't it?

But, what's the driving force behind the popularity of AI in the manufacturing industry? Let's find out!

In this blog, we'll look at how AI is transforming the manufacturing industry and becoming a highly desired technology for both the present and the future.

So, without any further ado, let's get started! 

What is the importance of AI in the Manufacturing industry? 

The tremendous complexity of today's products and the extremely tight market deadlines make it difficult for manufacturing businesses to maintain adequate quality following established standards and laws. Artificial intelligence in the manufacturing industry enables producers to produce things of the highest caliber.

According to the Manufacturer's Annual Manufacturing Report 2018, 92 percent of top manufacturing executives feel that digital "Smart Factory" technology, such as AI, would help businesses boost productivity and give employees the tools they need to perform more effectively.   

AI crunches massive datasets to identify patterns and trends, which are used to create predictive models for the future. Plants can foresee changes in demand and supply, determine the ideal intervals for scheduling maintenance, and identify anomalies early on, thanks to Artificial Intelligence (AI).              

Moving forward, with the aid of AI, manufacturing businesses can:

• Know the alterations and trends in the market.
• Boost the product quality.
• Find and fix production-process bottlenecks.
• Increased awareness of distribution and supply chains.
• Boost supply chain and distribution network visibility.
• Find anomalies or early warning indicators of failure to reduce downtime and repair.
• To enhance processes, perform more precise root cause analyses.
• Enhance the lifecycle of the equipment. 
• Improve safety, adhere to industry norms and laws, and lessen environmental impact. 
• Reduce waste and seek out new efficiencies to save money.

Benefits of Using AI in the Manufacturing industry!

Below, we've listed some of the significant benefits of AI in manufacturing. So, take a look! 

#1. Optimizing supply chains

The manual and time-consuming process of gathering all the orders, purchases, and resources required for production can be automated and accelerated by AI. Manufacturing businesses may manage their supply chains more effectively by adding AI. This includes monitoring materials and completed products all the way from the production line to delivery.       

#2. Demand forecasting

Manufacturers use AI and machine learning to forecast future buying trends and evaluate consumer behavior. The teams in charge of the manufacturing process are then given the intelligence so they can raise or decrease production. 

#3. Quality assurance

AI-powered visual inspection tools identify flaws in production lines. The technologies can quickly and precisely identify problems with machine vision cameras. Better than the human eye, in fact. 

#4. Round-the-clock production

Robots can work all day and night since the same human limits do not constrain them from human workers. Robots' limitlessness enables businesses to significantly increase their production capacity, allowing them to grow and serve larger customer bases.

#5. Preventative maintenance

Preventive maintenance is another benefit of Artificial Intelligence. You may spot problems before they arise and ensure that production won't have to stop due to equipment failure when the AI platform can predict which components need to be repaired before an outage occurs. If you also want to reap the benefits of AI in your manufacturing business, then you need to hire AI programmers who can turn your idea into reality.  

As you've seen the benefits and market potential of AI in the manufacturing industry, now it's time to check the real deal of this blog! Which is;

What Role Does AI Play in Manufacturing? Top Use Cases!

To exemplify how manufacturers can use AI to their advantage and put these ideas into practice, we've listed some of the top use cases of AI in the manufacturing industry. Take a look!

#1. Predictive maintenance

Many manufacturers nowadays are embedding sensors into their gear in an effort to attain excellence throughout the manufacturing process, producing performance and workload data in real-time. This makes it simpler to identify problems and foresee the need for equipment maintenance. Poor maintenance could lead to a manufacturer's machine breaking down, costing the company money. 

Manufacturing companies may rapidly identify key cause elements like weather, temperature, etc., with the help of AI-enabled predictive maintenance, greatly enhancing their capacity to manage equipment breakdown. 

#2. Digital twins

A factory, product, or service's virtual replica is called a "digital twin." Through the use of sensors, the representation is accurate in terms of its physical characteristics compared to its real-world counterpart. 

The first step in making digital twins function is integrating innovative components that collect information about the current state, location, or condition of physical objects. The parts are linked to a cloud-based platform that receives and processes all the data. 

#3. Supply chain management

Manufacturing businesses should plan for numerous contingencies in addition to monitoring changes in supply chains or order deadlines to maintain production optimization. 

Manufacturers have been grossly underestimating the potential of simulation, as the epidemic has demonstrated. Due to a lack of planning, many businesses collapsed along with the market. The factories can simulate countless possibilities and prepare for such events thanks to modern advanced planning and scheduling technologies. 

#4. Generative designs 

In the generative design process, several outputs are built by a system to satisfy predetermined criteria. To investigate design options, designers or engineers enter design goals and parameters into generative design tools, such as materials, manufacturing processes, and cost limitations. Smart AI solutions are used in the solution to determine what functions well and poorly after each iteration. 

Artificial intelligence can complete the task quickly while allowing the human expert to select from a variety of possibilities. Such digital transformation can alter how a business provides customer value and increase process efficiency. 

#5. Quality checks

Equipment internal flaws can be hard to find. By examining how items perform, specialists occasionally cannot find their shortcomings. However, this can be accomplished effectively using artificial intelligence (AI) technology. AI systems, tools, and applications can also be used to quickly and accurately identify minor defects in machines. 

AI in the manufacturing sector hence offers quality control. Smart AI solutions track machine productivity, identify problems, raise output, and lower maintenance costs. Because of this, the majority of manufacturing businesses automate production processes using AI. 

#6. Warehouse & Logistics management

Applications and technologies powered by artificial intelligence may intelligently and efficiently optimize warehouse management and logistical processes. Everything can be carefully tracked, arranged, and analyzed with AI, from production to delivery. Equipment and tools with AI capabilities that effectively control and monitor fleet operations. 

#7. Smart inventory management

Smart AI solutions can forecast and plan supply, which allows them to predict outcomes more precisely. By scheduling when products need to be restocked, firms will be able to manage their inventory and provide more precise delivery timings for commodities. Based on current inventory data, AI may also develop models to anticipate future demand. 

#8. Visual inspection

The most effective approach for manufacturers to monitor quality is through visual inspection, which they may do with the use of AI solutions. Rapid advancements in computer vision have already made it possible to make advanced flaw identification without adding more production and quality engineers. 

The image is sent from the sensing device to an interpreting device, where it is examined by AI algorithms that have been trained on datasets with examples of defects and pictures of products with and without flaws. With the aid of computer vision technology, defects like holes and unwanted shapes can be found. 

With its assistance, factories may increase product quality and longevity, enhance customer satisfaction, and cut waste. Additionally, visual inspection enabled by machine learning algorithms can monitor if manufacturing floor workers are complying with safety requirements and wearing appropriate protective gear. If not, they can raise the alarm or communicate with a supervisor. 

Bonus - Strengthen customer service

The importance of customer service in the manufacturing industry is often overlooked. This is a misunderstanding. If a customer leaves, your manufacturer will suffer a loss in reputation, revenue, profits, and ROI. By forecasting outcomes and seeing recurring patterns in consumer behavior, AI solutions can analyze consumer behavior.

Manufacturing businesses are better able to meet the needs of their customers by studying actual customer behavior. Service providers, IT companies, and engineering firms may constantly give outstanding and individualized customer experiences thanks to the capabilities of the manufacturing unit that AI empowers. 

Conclusion: Future of AI in Manufacturing

Applying AI to the manufacturing sector is no longer a possibility. In addition to greater lean inventories, decreased production failures, reduced costs, unscheduled downtime, and more productivity, next-generation industries powered by AI will also lead in these outcomes. 

Businesses can achieve their top- and bottom-line goals by using smart AI solutions to identify chances for enhancing operations and to influence future success.