The next frontier

Artificial intelligence and machine learning for mid-sized manufacturers. By Terri Ghio


Since the first Industrial Revolution, all manufacturers have embraced technological innovation to improve overall equipment effectiveness, increase revenue, and to enhance customer satisfaction. Today, artificial intelligence (AI) and machine learning (ML) are just two of the latest technologies to grace the manufacturing sector. But what do mid-sized manufacturers need to know about AI and ML to increase their product output and quality? AI focuses on building technology that can simulate human intelligence while machine learning can be defined as the capability of a machine to make decisions and predictions based on real-time data analysis. Given the scope of both technologies and the fact that they are still evolving, many mid-sized manufacturers may be hesitant to introduce them on the production floor.

Given the events of the last two years and long-term disruption to global supply chains, it has become clear that AI and ML can help mid-sized manufacturers increase efficiency, regardless of the challenges. Larger manufacturers have been embracing Industry 4.0 ideals and technologies for some time; now is time for mid-sized manufacturers to incorporate these techniques.

Why aren’t more mid-sized manufacturers utilizing Artificial Intelligence and Machine Learning?

Research has shown that 92 percent of senior manufacturing executives see AI as an essential tool to increase productivity. However, mid-sized manufacturers still have a lower rate of implementing AI and ML into standard production in 2022. This is due to reasons like:

1. High costs are a major setback for many mid-sized manufacturers and with a limited budget, business leaders have to carefully choose the most valuable investments. The cost of implementing complete AI solutions varies, but is often at least $20,000 and can go as high as $1,000,000. Further still, while many larger manufacturers are upscaling their smart manufacturing technology, mid-sized manufacturers are only starting to implement the data capture technology that make AI and ML possible. With an Industry 4.0 solution that installs smart sensors on legacy equipment, mid-sized manufacturers can save money while keeping up with the competition.

2. Speed of deployment and integration is another hurdle for mid-sized manufacturers. While the rapid evolution of technology is good for the manufacturing sector as a whole, smaller firms might struggle to keep up with the pace. To help alleviate this concern, mid-sized manufacturers should implement Industry 4.0 in short sprints, implementing slices of the project rather than the entire pie.

3. There is a certain level of fear and suspicion around the effects these technologies will have on job security but embracing Industry 4.0 can improve industry relevance and longevity. It is not easy to train a team to use new technology – and employees may be concerned that their job is being replaced by automated solutions. However, smart manufacturing can increase employee satisfaction by filling labor gaps with technology while creating more fulfilling jobs in production.

Less risk, greater reward
While there are numerous challenges mid-sized manufacturers face when implementing and developing AI and ML, embracing Industry 4.0 can drastically improve decision making, thus resulting in in a leaner, smarter, and more agile business in the long term.

Research from McKinsey has shown that when AI is used to monitor and analyze machines in the factory, it can reduce machine downtime by half because due to its ability to quickly and thoroughly analyze real-time data while leveraging previous historical data to help staff identify potential issues. Then, this data can be used to predict service requirements and ensure machines are fixed before they even break. Not only does this reduce downtime, but it also increases machine life expectancy. The same report expects worldwide savings from predictive maintenance to be around $500 billion!

AI is specifically able to detect patterns and draw conclusions with precision, and at a rate that humans wouldn’t be able to match. This allows department specialists to choose which manufacturing processes they would like to change for improved productivity. The benefits this delivers to the business include:

1. Removing bottlenecks and identifying new efficiencies: When fully integrated and given time to mature, AI and ML can be instrumental in locating where processes can be streamlined by identifying issues that human eyes cannot discern. This can help save money and revolutionize the way the organization operates in the long term.

2. More accurate root cause analysis: Getting to the very source of a manufacturing issue and moving beyond a short-term approach of ad-hoc fixes is crucial. AI and ML enable organizations to delve deeper into their data than ever before, providing an effective way to diagnose problems at their source that doesn’t take hundreds of hours of manpower to achieve.

3. Better supply chain management: Having too much stock at a location is wasteful, while having too little can severely impact production and planning. AI and ML allows companies to better respond to market demand by predicting long-term manufacturing requirements, improving inventory planning and decreasing supply chain management costs.

4. Meeting regulations and industry standards: As in most sectors, mid-sized manufacturers need to constantly keep up to date with regulations governing areas such as worker safety and product quality. AI and ML make this task much easier as they can be leveraged to instantly confirm that new processes are fully compliant.

Invest in your company’s future
Like the larger manufacturing organizations, mid-sized manufacturers should be in the race to embrace ML and AI as these Industry 4.0 processes will be pivotal for staying competitive. There are some hurdles to overcome, but the rewards are very much worth the time and investment. Success won’t happen overnight, but it doesn’t have to, as AI and ML integration is a gradual process. With the right strategy and partner in place, plus a strong determination to succeed, mid-sized manufacturers can vastly improve their current operations and profitability.

For a list of the sources used in this article, please contact the editor.

Terri Ghio
Terri Ghio is President of N.A. Operations for FactoryEye. Based in Irvine, California, FactoryEye North America is a division of Magic Software Enterprises Ltd., a global provider of business integration and decision support solutions. FactoryEye powered by Magic Software’s IoT platform is the solution that medium-size manufacturers turn to on their path to Industry 4.0. FactoryEye’s unique solution is intuitive, designed for rapid implementation that doesn’t require changing existing systems and infrastructure. FactoryEye gives global manufacturers unparalleled visibility into their operations, which enables them to make continuous improvements in the production process.
www.magicsoftware.com/factoryeye