Manufacturing is all about efficiency. Companies need to constantly improve to make more products in shorter timeframes, while also becoming more cost-effective and using fewer materials.
Making these changes in manufacturing can be tough, considering the big trends pushing companies to transform. But generative AI can be the key that unlocks this transformation.
Challenges such as global supply chain disruptions are severely impacting financial bottom lines, with McKinsey & Company predicting these disruptions will cost the average manufacturer 45% of one year’s profits over a decade. Domestically, organizations are struggling to hire enough people, with the U.S. Chamber of Commerce estimating that 616,000 manufacturing jobs still need to be filled.
These challenges call for new solutions, and generative AI has the potential to overcome them. The time is now for AI in manufacturing.
To tackle the challenges of production, costs, and more, manufacturers are embracing AI technology. These versatile algorithms can optimize everything from inventory management to quality control, even predicting future trends and preventing equipment failures.
With its ability to consume and analyze massive amounts of data in all formats, generative AI can be used in optimizing nearly every facet of manufacturing. Here are three areas we believe are prime starting points for AI in manufacturing.
Document Search and Analysis: Machine manuals can be notoriously complex and difficult to consume for shop floor technicians and engineers. And problems with silos of information create another hurdle in even just locating the necessary documentation. With generative AI, manuals can be found in a flash and the bots can summarize key information based on questions asked in natural language. This approach enables faster repairs, reduces machine downtime, and bridges the gap between more experienced and newer engineers.
Supply Chain: As mentioned above, global supply chain problems are eating into corporate profits. Besides disruptions, organizations are facing increasing pressure to source ethical and sustainable materials. Generative AI can provide visibility across entire supply chains and make recommendations on partners best suited for a purchase based on factors such as sustainability, BOM specifications, and delivery schedules, for starters.
Predictive Maintenance Monitoring: Shop floor automation is growing rapidly. Maintaining these assets in peak condition limits downtime and pushes operations forward. Even recently, maintenance schedules were based on estimates of a machine or part’s lifetime and projected time to failure or based on suggestions from that machine’s manufacturer. By combining the power of people, sensor data, and AI, any manufacturer can analyze machine data and maintenance recommendations from the models. The recommendations can even be prioritized, to further optimize the way the human engineers do their work.
We are just scratching the surface of AI applications in manufacturing that create market differentiation. The ability to harness the power of AI can create a competitive advantage that places you in the sphere of digital and transformational leaders.
If you are interested in implementing AI solutions in these or additional areas of your organization, please contact us to request a meeting with LRS.