Talk of AI for manufacturing may be everywhere, but there's one big problem to overcome when it comes to putting the technology to work in the real world: Before AI can deliver on its potential, organizations must be able to unlock the data AI needs in order to generate meaningful, actionable insights and drive real efficiency gains.
Building a unified, accessible data foundation is the first step to scaling AI for manufacturing. This means:
- Bringing together data that’s scattered across different systems and formats
- Breaking down silos between departments and technologies
- Ensuring data quality and consistency across all sources
- Labeling and organizing it in a way that's useful for AI
- Enabling real-time access for faster, more responsive applications
But those aren’t easy jobs in today’s world, where the volume of enterprise data is exploding. Most plants can no longer claim “data lakes.” Instead, they’re dealing with “data oceans.” In other words, the scale and complexity of information is overwhelming. Data is being created faster than ever before, and it’s coming from more sources than organizations and their teams can manage. This data is also often scattered across different systems, trapped in silos and moving through networks that weren’t designed to support real-time analytics.
This fragmentation and complexity make building a data foundation for AI in manufacturing even more difficult.
Steps to prepare your data for AI success
To deploy and scale AI for manufacturing, you must be able to identify, connect and prepare the right data.
Here’s how to make it happen.
Determine what data matters
Assess your operations to decide which data sources have the greatest impact on efficiency, quality and business outcomes. That’s the information you need if you want to optimize processes, drive informed decision-making and achieve measurable improvements in productivity, throughput and quality.
Find and connect that data
Modern operations depend on seamless communication between people, devices and processes. But if you don’t know where your data is coming from, or if it’s managed independently in disconnected systems, then it’s useless to you and your AI models.
To address this, you must identify and connect valuable data from every corner of your plant, breaking down silos between systems and departments. For example, connecting information from production lines, quality control, maintenance logs and IoT sensors can enable real-time monitoring, predictive maintenance and process optimization.
Bring all your data together
Once you’ve identified and connected key data, it’s time to bring this information together, even though it’s coming from a wide range of sources, relying on different protocols and existing across legacy and modern systems.
By uniting disparate systems and breaking down technology silos, you can improve data flow across your organization to power more accurate AI-driven insights.
Clean and contextualize the data
Once your data is collected and unified, it needs to be clean, contextualized and structured in a way that AI models can use to generate valuable insights that can be applied in the real world.
Enrich the data
Make this data accessible in an easy-to-access dashboard so teams can use it to monitor operations, identify trends and make decisions.
Complete connection solutions power real AI results
Of course, all this progress depends on having the right network infrastructure in place.
A unified, secure and high-performance data backbone can handle the demands of today’s applications and tomorrow’s innovations.
Companies that want to get the most from their AI—and unlock data’s full value, as we just described—need to invest in their data foundation. That means:
- Building strong connectivity and resilient network infrastructure
- Prioritizing data quality, governance and security
- Creating workflows that make data accessible and actionable
Belden’s complete connection solutions address data issues at the source, delivering the resilient infrastructure required to make your data AI-ready.
We can help you find and connect your data, regardless of how many systems or devices are deployed, and bridge the gaps between old and new equipment to ensure seamless data flow. You’ll be able to turn unstructured information from various sources into a unified, structured format that your AI models can use.
Belden makes sure your data is always connected, always available and always ready to inform decision-making. When your groundwork is solid, AI can deliver the business value you expect, turning data chaos into clarity to unlock new possibilities: optimizing operations, minimizing downtime or improving quality.
Have questions about building a data foundation for AI in manufacturing? Send us a note.