At our recent Latin America PartnerNetwork™ conference, we reflected on how data and AI (Artificial Intelligence) might continue to shape how we run our operations and manufacture things. We spoke about an emerging idea in manufacturing called "Data Contextualization." So, what's this about, and why is it important?
Let's think of data as more than just numbers and facts. Data Contextualization looks to find out not just "what" is happening in the production environment but also "why" and "how." Connecting data sources and looking at them from different perspectives helps get a deeper story, allowing businesses to make better decisions.
Data and AI could help in several significant ways:
- Data-Driven Energy Management in Manufacturing: Utilizing data and AI together, manufacturers can pinpoint areas of energy waste or excessive resource usage. This data-driven approach promotes eco-friendly practices and optimizes energy management, making manufacturing greener and more efficient.
- Saving Money: AI can suggest optimal machine settings and predict when parts might fail. On the plant floor, you notice that a conveyor belt is lagging. What if you could determine that a specific motor's wear is causing the slowdown and predict when it will need replacement? This foresight helps in reducing unexpected costs and improving efficiency.
- Staying Ahead in the Market: Today's business world changes quickly. With the enhanced contextualized data and AI's predictive capabilities, companies can adapt more dynamically to external factors and what their customers want. This gives them an advantage over other businesses because they're always a step ahead. How might we consider complex economic variables to develop better demand forecasts and predictions? By analyzing contextualized data dynamically and learning adaptively, AI models and tools can quickly offer solutions, making the whole process faster and smarter.
Looking ahead
Data and AI are becoming very valuable in our world. Using them strategically, like Data Contextualization, businesses can aim to operate better, be green, and stay competitive. As companies extract value from this data and find use cases for integrating AI into their operations, our manufacturing world will become brighter, more efficient and more sustainable.
Some resources to get started with your data contextualization journey: https://www.rockwellautomation.com/en-us/products/software/factorytalk/datamosaix.html
