The Impact Of Artificial Intelligence In Manufacturing

by John Clemons

Artificial intelligence (AI) is everywhere these days. Everyone has seen it in the news, and almost everyone has used it. It’s in our football games and our internet searches. It’s becoming ubiquitous and is already having a big impact on our daily lives.

What you might not know is that AI is also having a big impact on the manufacturing world. It’s one of the key technologies that’s transforming manufacturing back into an economic powerhouse. AI is helping manufacturers reduce costs, increase productivity and provide exciting new capabilities for their companies and customers.

Manufacturing Is Challenging

Manufacturing in the 21st century is very challenging. Many challenges are simply inherent to the manufacturing industry and to the global marketplace. The need to increase revenues, reduce costs, increase productivity and deliver to the customer are challenges common to all manufacturing companies.

1. Downtime: When operations are down, time and money are wasted due to lost capacity, reduced productivity and late orders, ultimately costing customers who are unable to receive their products on time.
2. Quality: Poor quality incurs costs in lost capacity and reduced productivity. It also costs money due to wasted materials, excess scrap, downgrades and the need for rework.
3. Energy: Despite many years of work to improve energy management and become more energy efficient, many manufacturing operations still have a long way to go—energy costs remain a high percentage of operating and product costs.
4. Productivity: Manufacturing operations face ongoing challenges in labor, capacity and materials. They must achieve more with fewer resources—less equipment, fewer people and reduced materials. As a result, improving productivity has become a primary focus for many operations.

AI In Manufacturing

AI can help manufacturing operations provide intelligent and real-time orchestration and optimization of their processes—not just inside the four walls of an individual manufacturing facility but across the entire supply chain.

AI can be applied to manufacturing challenges and can make significant improvements in operations:

1. Quality: Improve quality assurance and quality control (QA/QC) testing and inspection processes, rationalize the number of QA/QC tests conducted, provide better insight into the root causes of failures, and increase the overall throughput and accuracy of these processes.
2. Process Optimization: Enhance manufacturing processes from individual processes to the entire production line and facility, optimizing throughput and maximizing quality and productivity while minimizing material costs and labor costs.
3. Sustainability And Energy: Support sustainability efforts by reducing energy usage, emissions, waste, water usage and wastewater generation, all ultimately leading to truly sustainable manufacturing.
4. Supply Chain: Extend the notion of the smart factory to a smart supply chain, optimizing all aspects of the smart factory and smart supply chain, such as inventory management, transportation, and just-in-time manufacturing and supply chain management.

Success Criteria

Simply talking about AI and investing money in it doesn’t guarantee success. Manufacturing companies must successfully implement it. They must be strategic in transforming their operations and in how they use AI technologies. AI is not a silver bullet; it requires careful planning and careful implementation, all while making sure that the results are achieved.

Here are some key success criteria for AI:

1. Cost-Effective: AI can be expensive. While you often get what you pay for, it’s easy to spend a lot of money without achieving the desired results. An AI investment must be cost-effective and generate a significant return on that investment.
2. People And Culture: Ultimately, the success of AI solutions relies on people. Effective change management, training, communication and retraining are essential elements to any AI endeavor. Without these elements, achieving success and cost-effectiveness is unlikely.
3. Integration: Rarely is there an opportunity to fully replace outdated solutions with new AI technologies. Instead, AI solutions must work side by side with legacy systems to be successful in manufacturing.
4. Scalability: It’s easy to bite off more than you can chew with an AI project or, on the flip side, get stuck in a continuous mode of running pilot programs. AI should be piloted, but once the pilots are proven successful and are delivering the benefits, they must be scaled up quickly.

Real-World Results

AI is only valuable if it delivers tangible business results. Even though AI is impressive technology, it’s meaningless without real, measurable business benefits for the bottom line.

Here are some ways AI is providing real-world advantages in the manufacturing industries:

1. Productivity: AI agents and copilots are helping manufacturing operations perform tasks faster and easier than ever before. AI agents are performing autonomous tasks in the background, while AI copilots are helping shop-floor operators accomplish tasks quicker and with less labor.
2. Quality: AI copilots are helping manufacturing operations improve their first-pass quality. Operators collaborate with copilots to quickly and accurately set up and perform quality tests and inspections. Operators can then also efficiently conduct additional testing and other activities when test results are ambiguous or fail.
3. Sustainability: AI agents are helping manufacturers reduce their energy consumption, emissions and waste footprint. AI agents are also helping companies quickly and easily generate the required documentation for the various regulatory and compliance agencies.
4. Error-Proofing: Shop-floor operators and QA/QC personnel work with AI copilots to execute even the most difficult tasks. They make sure the tasks are performed accurately and completely, with all necessary documentation completed. At the same time, they help execute these tasks efficiently, keeping production on schedule and minimizing costs.

Conclusion

Manufacturing companies are continuously facing challenges, which are inherent to the industry and the global marketplace. These challenges, however, can be tackled head-on with the help of new technologies like AI.

AI is a powerful technology that helps manufacturing industries reduce costs, increase productivity and provide exciting new capabilities to companies and their customers.

New AI developments are helping manufacturing industries solve difficult challenges. These AI applications are generating tangible bottom-line benefits to operations. The next article in this series will discuss some of the key benefits of AI and how it’s helping transform manufacturing back into an economic powerhouse.