What You Need To Know About The Role Of AI In Making Manufacturing Better

The manufacturing industry has come a long way since the industrial revolution began. From following manual processes, manufacturing companies have entered Industry 4.0, where technologies like automation and IoT are used to optimize, accelerate, and automate the manufacturing process. Today, the focus has shifted beyond just manufacturing products. Today, there’s a growing focus on making production smarter and aligned with go-to-market mandates to meet the increasing customer demands.

Industry 4.0 promises to make factories smart and improve productivity and efficiency on the floor through digitalization and intelligent automation. Modern manufacturing companies are technology-driven, and one of the technologies that promises the most impact is Artificial Intelligence (AI).

AI-based platforms are helping manufacturing companies reinvent the way they function. Take Bridgestone, for instance. The Japanese tire company uses AI to improve the quality of its tires. Their AI system measures each tire on 480 quality items and uses that data to ensure that each tire is developed with complete precision. It has helped them improve quality by 15% compared to their legacy manufacturing processes. Apart from the improved outcome, manufacturing companies have been able to minimize costs and maximize their efficiency.

But most importantly, AI is helping companies to solve common challenges such as supply chain management, cost management, inventory management, maintenance, reporting, and make manufacturing better.

How Can AI Make Manufacturing Better?

1) Supply chain management

The last year’s pandemic and Ever Green’s blocking at the Suez Canal show how countries are interconnected and interdependent on each other at the level of the supply chain. A single external incident like a pandemic or Suez Canal blockage wrought havoc in the world of supply chain management. Although manufacturing companies have for long used predictive analytics to manage their supply chain, incidents like these are unforeseen and could result in delivery delays. AI can learn about issues such as unexpected delivery delays or unexpected harsh weather conditions and respond to them accordingly. It can identify the vulnerabilities and address them effectively or create mitigation strategies in advance. In predictive conditions, AI can ensure hassle-free delivery without the need for human intervention. According to McKinsey’s research, 53% of respondents reported a direct increase in revenue after using AI in supply chains.

2) Cost management

McKinsey’s survey also reveals that 44% of companies that use AI have witnessed cost reduction. Manufacturing is a cost-intensive industry as companies must spend on labour, production, packaging, sales, delivery, etc. They must incur additional costs if there is unplanned downtime. There are various ways in which AI can help companies manage it’s costs. To begin with, AI makes better predictions about inventory, resource utilization, and even downtime. This helps manufacturers to plan manufacturing process accordingly. Apart from that, the cost of the human workforce reduces as companies invest more in AI systems that do the same work faster and more efficiently. Another area where manufacturers can cut costs is defects. Defects in materials or machinery could be an expensive expenditure for manufacturing companies. By reducing rework and maintaining operations, companies can optimize their costs and increase margins.

3) Inventory management

Much of the success of a manufacturing company is determined by how efficiently they have managed their inventory. Although manufacturing companies have a great appreciation of the art and science of predicting demand and manufacturing products, optimization is the need of the hour. It will help the company curb unnecessary costs and prevent wastage. AI is efficient in managing inventories. It can provide real-time insights into the inventory. It add cognitive value to the process by predicting demand, recommending actions, and even implementing them. AI can also determine which products must always be available during predictable situations, which ones should always be available in stock irrespective of the demand. This will help the company plan its production and manage its inventories efficiently without unnecessary expenditure.

4) Predictive maintenance

Unplanned downtime is a nightmare for every manufacturing company. It could delay the production process and lead to unnecessary losses. That’s why predictive maintenance has become so critical for the smooth operations of manufacturing companies. Manufacturing companies have started using AI to identify potential chances for downtimes or accidents and notify the relevant team to fix before it escalates and halts the production process. AI can identify which machines have to be fully shut down and which can be improved to leverage their full potential. According to a KPMG report, 41% of manufacturers have already started using AI for routine prediction and maintenance tasks. This will potentially help them to reduce costs on machine failure.

Conclusion

According to McKinsey, smart factories could generate $3.7 trillion of revenue in 2025. To become a smart factory, manufacturing companies have no choice but to leverage technology for manufacturing, billing, and other critical functions. AI has proved to be a game-changer for companies on this quest as it has helped them reduce costs, decrease downtime, improve productivity, and ramp up their decision-making and production processes. However, to become a smart factory, companies need to partner with experts who can implement AI in the manufacturing industry. At Veracitiz, we have helped in revamping the planning, budgeting, and reporting processes of manufacturing companies, so that they can work efficiently. We leverage our deep understanding of IBM’s powerful portfolio of solutions to help manufacturing companies deliver outstanding outcomes.

To know more, contact us.