Why should SME manufacturers invest in AI and machine learning?

  • June 2, 2022

Ever since the Industrial Revolution, manufacturers have embraced technological innovation to increase output and deliver new products to customers. Today, artificial Intelligence (AI) and machine learning are just two of the latest technologies to grace the sector. But what do small and medium-sized enterprises (SMEs) in the manufacturing sphere need to know about AI and machine learning? Given the scope of both technologies and the fact that they are still evolving, their meaning can be broad, leaving SMEs uncertain about the benefits they provide.

Put simply, AI is the simulation of human intelligence processes by machines, especially computer systems. It focuses on building technology that can simulate human intelligence. Machine learning, on the other hand, is a subfield of AI, which can be defined as the capability of a machine to make decisions and predictions based on deep data analysis.

Given the events of the last 18 months and long-term disruption to global supply chains, it has become clear that AI and machine learning have a major role to play to ensure manufacturers continue to run as efficiently as possible, regardless of the challenges they face. Larger manufacturers have made some positive inroads as far as AI and machine learning are concerned, but progress in SMEs has not been as rapid.


Why aren’t more SMEs utilising AI and machine learning?

Research has shown that 92% of senior manufacturing executives see AI as an essential tool to increase their productivity. However, SMEs still have a lower rate of implementing AI and machine learning into their processes. Below, we examine why.

  1. Pricing is a major setback for many SMEs and with a limited budget, business leaders have to choose carefully what investments they make. 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 AI and machine learning strategies, SMEs in a lot of cases are only starting to implement the data capture technology that makes AI and machine learning possible. A business might have implemented some elements of AI or machine learning, but there is a big difference between having some basic functions in place and fully mastering the technology.
  2. Speed of deployment and integration is another hurdle for SMEs. 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. Organisations need to frequently bring in specialists to teach workers how to run, maintain and implement new solutions, which is often costly and time-consuming.
  3. There is a certain level of fear and suspicionaround the effects these technologies will have on job security. At the best of times, it’s not easy to change work practices and train the team to use new technology – and this is significantly exacerbated when suspicion prevails that jobs may be on the line. Often managers are hesitant to start the process due to the resistance they anticipate.


The benefits outweigh the drawbacks

While there are numerous challenges SMEs face when implementing and developing AI and machine learning, adoption can help drastically improve efficiency, production, and business agility in the long term.

Research from McKinsey has shown that when AI is used to monitor and analyse machines in the factory it can reduce machine downtime by half, because of its ability to quickly and thoroughly analyse a vast range of data points and leverage previous historical data to help staff identify potential issues. This data can then 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. The benefits this delivers to the business are numerous:

Removing bottlenecks and identifying new efficiencies: when fully integrated and given time to mature, AI and machine learning can be instrumental in locating where processes can be streamlined and identifying issues that human eyes are not able to discern. This can help save money and revolutionise the way the organisation operates in the long term.

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 machine learning enable organisations 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.

Better supply chain management: having too much stock at a location is wasteful, while too little can severely impact production and planning. AI and machine learning can help companies better respond to market demand by predicting long-term manufacturing requirements, which improves inventory planning and decreases supply chain management costs.

Meeting regulations and industry standards: as in most sectors, manufacturers need to constantly keep abreast with regulations governing areas such as worker safety and product quality. AI and machine learning make this task much easier, as they can be leveraged to instantly confirm that any new processes are fully compliant.


Invest in your company’s future

Like larger manufacturing organisations, SMEs should be in the race to embrace machine learning and AI as they will be pivotal in maintaining the ability to compete in the market. 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 machine learning integration is a gradual, iterative process. With the right strategy in place and a strong determination to succeed, SME manufacturers can vastly improve their current operations and profitability.


FactoryEye is a Manufacturing and Organizational Intelligence platform for mid-sized manufacturers – providing holistic organizational visibility to enable ongoing improvement and ensure manufacturers are functioning as efficiently as possible. It integrates data from across the organization, converts it into useful information and provides AI powered actionable insights.


Featured Blog Posts

Streamlining Operations: How Facnor and Sparcraft Enhanced Their IT Agility with Magic Software

Read Story

Elevating Data Dynamics: Viparis’ Strategic Integration of Magic xpi

Read Story
AI und IT Trends 2024

Navigating 2024: Essential IT Trends for SMEs

Read Story