Why 'One more dashboard' won't fix your CIP process

Every few months, another vendor arrives at the plant with impressive analytics, beautiful visualizations, and detailed dashboards showing exactly what's happening in your processes. The demos look compelling. The insights seem valuable. And then you ask the critical question: "How does this integrate with our existing automation system?"

That's when the conversation gets complicated.

The dashboard trap

The industrial software market has developed a pattern: collect data, visualize it beautifully, present it to operators and engineers in a dashboard, and assume that better information automatically translates to better performance.

This works to a point. Dashboards help with analysis, troubleshooting, and understanding process patterns. They're valuable for engineers trying to optimize operations or quality teams investigating variations.

But dashboards don't run your plant, PLCs do.

When CIP cycles need to be shortened, when product transitions need to be detected in real-time, when cleaning effectiveness needs to be verified before resuming production—these decisions happen at the automation layer, not in a monitoring dashboard.

The industry shift: From insights to integration

Dashboard-based analytics delivered value for process understanding and troubleshooting, but the gap between identifying opportunities and implementing them operationally drove an industry evolution. Process monitoring vendors are developing automation connectivity—signals to PLCs rather than just insights to operators—and manufacturers are increasingly specifying this as a requirement rather than a nice-to-have feature.

What's emerging in automation-connected monitoring

Several technology providers are now offering process monitoring with direct PLC integration, though approaches vary significantly:

Some provide basic signal outputs that plants integrate themselves. Others offer more comprehensive integration support including protocol compatibility with major PLC platforms. A few have developed pre-built integration modules for common applications like CIP optimization.

Collo's Real-Time Process Control is one solution that addresses both the monitoring and automation connectivity requirements, combining RF-based liquid process intelligence with direct signal output to automation systems.

For facilities evaluating process monitoring technology, this shift represents a major opportunity, but not without complexity. As automation integration is becoming available, it's not yet standardized. Implementation approaches differ substantially, and each facility needs to determine what level of integration support they require versus what they can handle internally.

What makes automation integration complex

The reason automation-connected process monitoring is emerging gradually is that both vendors and facilities face genuine technical challenges.

From the vendor side: Process monitoring companies have expertise in sensors, data analysis, and industrial software. PLC integration requires different expertise—understanding automation platforms, programming industrial controllers, designing fail-safe systems, validating safety-critical applications. Building this capability requires either developing internal automation engineering teams or partnering with automation specialists. Both paths take time and investment.

From the facility side: Plants often identify clear optimization opportunities, but their automation infrastructure wasn't built to receive new signal types from external systems. The optimization value is evident, but capturing it requires integration work that may not have been planned or budgeted. This is the "our current tech stack does not allow us to optimize" problem—where the barrier isn't understanding what to improve, but connecting new monitoring capability to existing automation infrastructure.

Additionally, each facility has unique automation infrastructure. A monitoring system proven on Siemens PLCs might need adaptation for Rockwell. Integration validated in European dairy might need modification for North American beverage. Repeatable, scalable automation integration requires testing across multiple platforms and applications.

The phased deployment pattern

As automation-connected monitoring has developed, a common deployment pattern has emerged across early adopters—not because it's mandated, but because it reflects how organizations build confidence in new control approaches.

Initial phase: Advisory operation. The monitoring system runs parallel to existing procedures. It generates recommendations, but automation continues as programmed. This phase validates that technology detects what it claims in actual production conditions. Duration is typically 2-3 months, ending when operations and quality teams agree signals are reliable enough to consider acting on them.

Validation phase: Supervised automation. Monitoring can influence some automation decisions, with enhanced verification and easy fallback to standard procedures. This validates both optimization effectiveness and the ability to safely handle edge cases. Duration varies—2-4 months is common, extending longer for safety-critical applications.

Production phase: Routine automated operation. The system regularly controls process parameters within defined boundaries. Human oversight shifts from approving each optimization to monitoring overall performance and handling exceptions.

The complete timeline from initial deployment to routine automated operation typically spans 6-12 months. This reflects not just technical implementation but the organizational learning required to trust new control approaches.

Some monitoring vendors are working to compress these timelines through better validation protocols, more robust integration, and improved operator interfaces. But the fundamental pattern—build confidence progressively—persists because it addresses human factors as much as technical ones.

Why facilities are prioritizing automation integration now

The shift toward automation-connected monitoring is accelerating because of converging operational pressures:

Corporate sustainability mandates. Water reduction targets of 20-30% by 2030 require systematic, continuous optimization—not periodic improvement projects that deliver one-time gains.

Tighter margins. Facilities can no longer accept 3-5% operational inefficiency as the cost of conservative procedures. The difference between identifying losses and automatically minimizing them has become material to financial performance.

Stretched operations teams. Nobody has capacity to continuously monitor dashboards and manually optimize. Automation that implements improvements consistently, across all shifts, is increasingly necessary.

Real deployments demonstrate the impact: a European beverage manufacturer achieved 23% CIP cycle time reduction, translating to substantial water and energy savings alongside recovered production capacity.

This is why operations directors are specifically asking about automation connectivity. The industry has moved beyond "help us understand our processes" to "help us optimize our processes automatically."

There's nothing wrong with dashboards. They serve important functions—analysis, reporting, troubleshooting, trend visualization. But when process optimization depends on real-time response, dashboards are insufficient.

The vendors who've solved integration aren't necessarily the ones with the most impressive dashboards. They're the ones who understand that in food and beverage manufacturing, optimization only happens when better information reaches the systems that control production—directly, reliably, and without creating an integration project every time you want to deploy it on another line.

What this means for process improvement projects

If your facility has aggressive efficiency targets—water reduction, waste minimization, capacity optimization—and you're evaluating monitoring systems to help achieve them, prioritize integration capability early in the evaluation process.

Can the system deliver signals your automation can use? Does it work with your existing protocols? What's required to go from pilot deployment to production operation across multiple lines? How much ongoing IT and automation support does it need?

These questions determine whether a monitoring project delivers operational improvements. Successful deployments typically involve vendors who provide genuine integration support and facilities that commit appropriate automation resources.

Ready to bring real-time process control to your automation systems? Contact us to discuss deployment options for your facility.