When it comes to AI in manufacturing, one thing is critical: strong data. You’ve likely heard the phrase, “Garbage in, garbage out,” before. Without well-structured data, and lots of it, AI is less effective.
That can sound very intimidating. However, we have some great news. You have more data than you think.
After all, every production run, every quality check you perform, and even every maintenance log, is packed with valuable information. The real problem is that your data is scattered over different systems and hidden in printed reports and mental notes. What if you could see it all in one place, in real time?
AI-powered KPI dashboards aren’t just a fancy screen. They’re your window into uniting that data and seeing exactly what’s happening on your shop floor.
Do I Really Need a Manufacturing Dashboard?
Most manufacturers are already tracking their basics, including production numbers and downtime hours. Some of you may even have systems implemented to track quality metrics.
But what do those numbers communicate? And can you put the puzzle pieces of individual data together for real, meaningful insights about your factory floor?
Mostly, the data is coming from different sources, and often compiled manually, which stops you getting the full picture quickly. Sure, you hear about looming issues, eventually. This leaves you reacting to issues, instead of preventing them.
Think about your last quality problem. How long did it take to identify? Could you have caught it sooner if you had real-time visibility into your processes?
Digital transformation doesn’t have to mean investing in a whole new set of infrastructure. It can start with seeing what you have with greater clarity. And that’s where AI-powered KPI dashboards come in.
What Real-Time Dashboards Actually Do
Modern smart manufacturing dashboards bring together all that data. Then show it to you in ways that turn numbers and patterns into real information for greater operational efficiency.
Naturally, dashboards vary by purpose and manufacturer, but will typically show you:
Production flow
- Current production rates vs. targets
- Bottlenecks developing (in real time)
- Equipment efficiency across shifts or time periods
- Material usage and waste patterns
Quality metrics
- Defect rates by product line
- Rework costs and trends over time
- First-pass yield percentages
- Customer complaint patterns
Equipment health
- Predictive maintenance alerts (before failures)
- Energy consumption by machine
- Overall equipment effectiveness
- Maintenance cost trends
Workforce performance
- Productivity by shift and operator
- Training needs identification
- Safety incident tracking
- Labor allocation optimization
The visibility is a real plus. But the secret lies in the fact that many AI-powered dashboards analyze data in real-time. You can see problems as they develop, not after they’ve cost you hard-earned cash.
Getting Started with AI-Powered Dashboards
Dashboards open up new insights and visibility. Let’s look more closely at getting started with them.
Remember, you don’t need to create a full smart manufacturing facility in a single day. As we advised in our pilot AI projects article, consider using AI in the area where you have the most headaches. For most manufacturers, that’s equipment downtime.
A basic predictive maintenance dashboard might track:
- Vibration patterns from critical machines
- Temperature fluctuations
- Run times and cycle counts
- Maintenance schedules vs. actual needs
All of these are early warning signs that a machine needs some TLC. However, without a single source bringing that information together clearly (and fast), crucial information can be missed or delayed until it’s too late to act on.
With a predictive maintenance dashboard, however, you will get alerts the moment something is detected. You can schedule maintenance during planned downtime, often saving more than the system itself costs in major breakdowns avoided.
With this sort of additional visibility, you can look forward to:
- Faster problem resolution
- Better use of your resources and time
- Smarter decision-making, with data to back it
- Improved customer service with greater accuracy
Addressing Common Digital Dashboard Concerns
Understanding everything AI in manufacturing can offer can be intimidating. But many common concerns are not deal-breakers for your digital transformation.
We don’t have the right data
As we noted in the opening, you have a lot more data than you think. Most modern manufacturing equipment already generates tons of useful information. And you can retrofit sensors surprisingly easily, offering insight into temperature, vibration, and cycle times.
It won’t work with our systems
Most modern digital dashboards for manufacturing have thought ahead. Using handy tools like modular APIs and even the cloud, they can pull data from different sources. You probably don’t have to replace what you have. Just get them talking to each other.
We don’t have IT expertise
Luckily, digital dashboards are designed for you, the manufacturing team, not the IT department. Most need minimal technical savvy to set up and offer ongoing support.
The cost seems high
Smaller manufacturers have tight budgets to respect. However, digital transformation is inevitable. Compare the initial dashboard cost to one unplanned breakdown, or the hidden costs of quality issues. Most dashboards pay back their costs within months.
How to Get Started with Digital Dashboards in Manufacturing
If you’re ready to turn your data into better decisions, here’s how to start:
- Identify your biggest pain point: What problem costs you the most money or causes the most stress?
- Document what data you already have: Production logs, quality reports, maintenance records: all your data has value. Make sure you know what you have.
- Define success metrics: What would “better” look like? Reduced downtime? Fewer defects? Improved delivery times? Set clear metrics for success, so you have a benchmark to work toward.
- Start with one area: Pick a single process or machine to monitor first. This lets you prove the concept, and start seeing some ROI, before expanding your efforts.
- Get expert guidance: You don’t have to do this alone. Organizations like IMEC specialize in helping manufacturers implement these solutions successfully, and you will find plenty of AI implementation consultants to help you get the right tech for your needs, the right way.
AI in manufacturing doesn’t replace human judgment and experience. It gives you more (and better) information to make those judgments. When you have clear visibility into what’s happening, as it happens, you can make that crucial shift from reactive to proactive management.
The good news? You don’t need massive budgets or months of disruption to get started. You just need to take the first step toward seeing your operation more clearly. It’s time to explore digital dashboards for your manufacturing business. Soon, you’ll wonder how you ever worked without them.
Ready to explore what’s possible? IMEC is here to help you review your options and find the right solutions for your needs. Feel free to reach out to us for help or guidance.
*This article was developed through the combined expertise of contributors from IMEC and Goodman Lantern.
