Depending on forecasts, AI–powered techniques will be able to boost employee performance by up to 45% more than in 15 industry sectors—including production—by 2035. AI will operate industrial production and quality control, decrease development time and waste, enhance product reusability, conduct preventive maintenance works, and perform other tasks. It is already changing production in various ways. Let’s look at some use cases of producers using AI technology, who needs it, and what benefits it can bring.
Which Businesses Require Artificial Intelligence
AI in production can be used in almost all business verticals and at all levels:
- In design: to increase the efficiency of new product development, process automation of selecting suppliers, and assessment, when evaluating specifications for spare parts and components.
- In production: to enhance business operations and coordination (orchestration) of various production systems. The usage of intelligent assistants helps reduce the number of staff mistakes, makes production operations easier, and decreases downtime during the restructuring of technical procedures. Image recognition functions can track staff and mobile equipment moves—thereby increasing the level of security in the enterprise, and they are also used for quality control and analysis of the condition of the equipment.
- In logistics: optimize transport route planning, decrease raw material shipping times, and ensure their predictability, as well as track deliveries and the entire distribution processes. Using AI, it will become probable to anticipate the volatility of shipping amounts. Interactive communication also helps to build interaction with customers and suppliers.
- At the promotion level: predicting the amount of maintenance and assistance services, cost management, and evaluation of client satisfaction with product quality are all examples of tasks that fall under the purview of pricing management.
What are the Benefits of Artificial Intelligence in Production?
The introduction of AI does not require a sharp restructuring of the business processes of the company. The solutions currently available on the market are good because they allow you to achieve a new level of quality by optimizing the operation of existing systems. You can gradually introduce all new elements of production processes into the monitoring and control loop and coordinate them, increasing the degree of manageability of processes. So what benefits can it bring?
Quality Assurance
Some imperfections are too little to detect with the human eye, even if the staff is highly skilled. Machines, on the other hand, can be outfitted with cameras that have sensitivity hundreds of times greater compared to our eyes, letting them identify even the most insignificant flaws. Machine vision enables computers to “see” goods on the assembly line and detect flaws. The following logical point would be to share photos with these flaws with a human expert, but this is no longer required because the process can be completely automated.
Failure Mode Forecast
When we take into account items and procedures, we may reach incorrect outcomes. Irrespective of visual examination, goods can perform poorly in numerous ways. Even if a product appears to be flawless, it may fail soon after its initial use. Correspondingly, a product that appears to be flawed can still perform flawlessly. AI in the manufacturing industry can define spheres that require more attention throughout testing by using a massive amount of information on how goods are tested and also how they function.
Forecasting Maintenance
Rather than making guesses or conducting preventive maintenance activities, smart upkeep enables businesses to foresee when machines require technical service with high precision. With ML, it prevents unscheduled downtime. Detectors and progressive analytical tools embedded in industrial machinery enable maintenance work, react to cautions, and eliminate machine issues. Using data analysis, AI systems can infer the equipment status and find malfunctions to proceed with the proper preventive maintenance.
Conceptual Design
Conceptual design is a process in which software creates a set of outcomes that meet predefined parameters. Developers or engineers enter design objectives and criteria—such as components, manufacturing techniques, and cost limitations—into software architecture to discover design possibilities. The solution employs ML techniques to identify what performs well and what does not work with each iterative process. Digitalization of this magnitude can alter how a business provides value to its clients while also improving operational efficiency.
Environmental Effects
Producing different goods, such as electronics, is continuing to cause environmental harm. In which way? The extraction of raw materials for batteries, enlarged plastic manufacturing, massive energy usage, and so on are just a few examples. AI can assist in changing production by lowering or even eliminating its ecological consequences. AI can aid in the creation of new environmentally friendly components and also help in the improvement of energy effectiveness.
Data Consumption
There are numerous applications for big data in production. Producers gather massive amounts of information about operational procedures and other concerns—and when merged with analysis tools like plant data software—this data can give beneficial info for business advancement. Logistics management, risk assessment, and sales forecasting are just a few illustrations of how big data can help producers. This form of AI can provide access to earlier inaccessible concepts.
Price Projections
To produce something, you must first acquire the needed assets, which can sometimes be more expensive than anticipated. If you purchase stainless steel, for instance, its cost is affected by a combination of aspects. Due to quick price movements, it may be challenging to determine when is the best time to purchase materials.
Businesses must also be aware of the costs of raw materials to calculate the cost of the final goods as soon as it is prepared to leave the production plant. Let’s use stainless steel as an illustration: costs vary based on the latest listings, such as nickel or ferrochrome price increases.
Customer Care
What sectors come to mind when we think of customer support? The tourist industry, sales, finance? They interact directly with their clients, so customer support is an important component of their business.
Customer relations are frequently ignored in production, and it is a major error because lost clients can lead to thousands of funds in lost sales. AI technologies can evaluate buyer behavior, spot patterns, and forecast future outcomes. Businesses can more effectively meet their client’s needs by monitoring their current behavior.
So far, not many industrial companies are using artificial intelligence in their business processes. However, the advantages of AI encourage its implementation in various fields of activity of the largest organizations in various branches of the industrial sector. Judging by what technologies are already being used, the prospects for the development of artificial intelligence in the industry are wide and promising.
Be the first to comment