Good, fast, and cheap: it’s the classic product management triangle. You can’t have all three at once, or can you? In the manufacturing industry, companies have long been under pressure to deliver goods at a competitive price point, to produce these goods as quickly and efficiently as possible, and to bring added value to their customers beyond just the product. Producing a good quickly and cheaply meant sacrificing value. Producing a good quickly and with high value meant a higher price point. Producing a high-value good at a low price point meant longer production times. Add in fluctuating supply chain and raw materials costs, and manufacturers seemed stuck between a rock and a hard place. Artificial intelligence (AI) is helping companies change this equation in their favor. While the initial upfront investment can be significant, AI may ultimately help manufacturers produce higher quality goods faster and more cheaply.

How Does Artificial Intelligence (AI) Work in Manufacturing?

Artificial intelligence (AI) is a loose collection of technologies that mimic human reasoning. AI can automate processes, run predictive analytics to better inform decision making, increase efficiency, and unlock new business value. Advancements in computing power and learning techniques, coupled with improvements in hardware and software sensors, now make it possible for computers to respond immediately to complex queries, delivering the precise information a decision-maker needs at the exact moment it’s needed.

4 Critical AI Benefits for Manufacturing

By 2035, AI could increase productivity by 40 percent or more, according to Accenture. For manufacturing companies, integrating AI technology can deliver significant cost, time, and process-related savings. Here’s how:

  1. Real-time data mining. Using AI for real-time Big Data insights can help manufacturers make faster, better decisions. When manufacturers introduce AI, the first thing they’ll be able to see is a clearer picture of their data. AI can then automate and prioritize routine decision-making processes. For example, when used with equipment sensors, AI can read data and alert the maintenance team to recalibrate or adjust a machine before it breaks. AI can also prioritize repair jobs so that the machine that needs urgent attention gets fixed first.
  2. Actionable insights. AI identifies and understands patterns within Big Data, such as information from customer orders. Using this data, these tools can predict future buying patterns and opportunities, as well as recommend courses of action that will help meet future customer demand.
  3. Intelligent automation. The combination of AI with automation is allowing systems to synthesize vast amounts of information, automating workflows that can learn and adapt as they go. For example, AI can complete rote tasks that otherwise would zap productivity, freeing employees to focus on higher-level work.
  4. Protect sensitive data. This may seem counterintuitive given that you’re introducing new technology. However, when you automate some tasks, you can eliminate human error that would otherwise open a door to attackers, as well as improve the output quality when you run reports.

Hiring the Right Technical Talent for AI

AI is not a replacement for humans. The human element is needed to make decisions, guide the AI engines, and ensure data quality. For example, while a machine may be great at detecting a supply chain disruption and offering choices to mitigate the problem, a human will still be needed to reroute the shipment or authorize the alternate provider.

Additionally, companies will want to identify processes that can be improved with AI before introducing it, as well as educate employees on how AI can help them do their jobs better. Right now, many employees may still think of AI in terms of something that will take over their jobs. A change management effort can introduce them to the idea that AI will help them be more productive and eliminate “busy work.”

As AI continues to move into manufacturing, we’ll see more automation, voice recognition, machine learning, and other technologies that will increase productivity and profitability. What manufacturers must do now is ensure they have the technical talent ready to make the most of AI.
Questions about sourcing the right technical talent or just want to hear about what’s happening in the market? Let us know and we will connect with you someone who can best answer your questions.


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