The application of artificial intelligence in manufacturing contexts is making tremendous progress, thanks to recent AI innovations in cloud computing and an abundance of data storage and analysis. Additionally, AI provides managers with crucial data so they can make better business decisions.

Automated manufacturing creates higher-quality products faster and more efficiently while giving managers crucial data to make better business decisions. Nevertheless, there are still a few obstacles to overcome: Businesses are cautious about disclosing critical production processes.

Ways To Boost Productivity

Here are five ways that artificial intelligence (AI) can help manufacturing become more productive.

  • Demand Forecasting With Greater Accuracy

With AI innovations and machine learning, hundreds of mathematical models of possible production and outcome can be tested. They can also be more precise in their analysis while responding to new product releases, supply chain disruptions, or sudden demand shifts. Overall inventory reductions of 20% to 50% are conceivable, according to consultancy company McKinsey.

Even simple tasks like collecting physical inventory can be made more efficient with AI. Using sophisticated drones that fly through the warehouse, scan products, and check for misplaced items, a work that takes Walmart personnel one month to accomplish may be finished in 24 hours.

  • Predictive Maintenance

Predictive maintenance solutions are beginning to be acknowledged by organizations as a worthwhile investment since it is a sure-fire way to increase operational efficiency and, consequently, directly affects the bottom line. Predictive maintenance uses sensors to watch equipment status and analyze the data continuously, allowing companies to service equipment when needed rather than when scheduled for maintenance, reducing downtime.

Taking predictive maintenance a step further, algorithms based on big data can predict future equipment failures. Machines can even diagnose their conditions, order replacement parts, and schedule field technicians on their own as needed. According to McKinsey, AI-enhanced predictive maintenance of industrial equipment can reduce maintenance costs by 10%, reduce downtime by 20%, and reduce inspection costs by 25%.

  • Highly Customized Manufacturing

Companies can now take personalization to the next level by creating products and services that are highly relevant to specific customers because of advances in AI innovations and software intelligence. Personalization sells; therefore, this is crucial. Recent surveys indicate that 20% of consumers are willing to pay a 20% premium for personalized products or services. And brands that customize products can gain greater trust from their customers. According to Accenture, 83% of consumers trust brands that customize products.

  • Optimizing Manufacturing Processes

By the end of the year, it’s projected that a variety of machine types will be powered by AI engines running machine learning algorithms capable of enhancing manufacturing processes independently. To optimize production operations, artificial intelligence systems will monitor quantities consumed, cycle times, temperatures, lead times, faults, and downtime.

The first phase of AI implementation will be an “operator help” mode, in which AI will run in the background and provide replies to the operator. AI systems will use the operators’ final decisions to learn how the human mind works to be deployed in an “operator replace” mode. With AI, we will turn data into intelligence in vendor-neutral environments, where all machines will speak the same language, improving production efficiency throughout the shop floor.

  • Automated Material Procurement

Everything, even the first phases of quoting and building the supply chain, will be recorded and critiqued using analytics and machine learning. Machine learning, according to McKinsey, will reduce supply chain forecasting mistakes by 50% and expenditures associated with transportation and warehousing and supply chain administration by 5% to 10% and 25% to 40%, respectively. Honeywell’s procurement, strategic sourcing, and cost management processes are already incorporating AI innovations and machine-learning algorithms.

Conclusion

As a powerful technology, AI may benefit businesses in various industries by optimizing operational processes, enhancing customer experience, and lowering person-hours spent.

By extending human skills, AI technology makes businesses more productive and cost-effective and gives them insight into human behavior, preferences, and ambitions. Companies that have already begun to reap the benefits of AI innovations are increasing their productivity and ensuring their long-term viability and growth.

So, if you wish to make artificial intelligence innovations in your business contact the ONPASSIVE team.