How to Reduce Downtime with Automation Analysis: The Essential Method

Why Downtime Keeps Rising in Production Environments

In most factories, unplanned downtime costs 5% to 20% of total capacity, depending on the industry. Yet most of these losses could be prevented through better use of automation data coming from PLCs, sensors, field networks, and control systems.

The issue is simple:

• the data exists,

• but it’s not analyzed,

• or it’s analyzed too late.

This is where automation analysis becomes a real competitive advantage.

Industrial production line displaying real-time automation data used to analyze machine performance and detect potential downtime.

What Is Automation Analysis?

Automation analysis consists of collecting, structuring, and analyzing data from:

• PLCs (Programmable Logic Controllers)

• field sensors

• fieldbus networks

• SCADA systems

• drives, robots, and I/O modules

The goal is to gain real-time visibility into:

• machine conditions,

• execution cycles,

• recurring faults,

• abnormal behaviors,

• performance drift.

  

  Automation engineer reviewing PLC diagnostics on a laptop to identify faults and improve machine reliability on a production line.

How Automation Analysis Reduces Downtime

1. Early Detection of Anomalies

PLCs capture every millisecond of machine activity.A structured analysis helps detect:

• abnormal response times,

• sensor drift,

• intermittent errors,

• thresholds approaching failure.

→ Unplanned downtime is prevented before it occurs.

2. Identifying Bottlenecks

Cycle times extracted from PLCs show precisely:

• where the line slows down,

• which station creates accumulation,

• which machine affects throughput.

→ Result: higher availability without investing in new equipment.

3. Eliminating Recurrent Faults

Analyzing alarm histories and PLC fault logs removes:

• recurring errors,

• restart issues,

• downtime caused by misadjusted sensors or actuators.

→ A single corrective action can save hours of downtime each month.

4. Optimizing Maintenance Operations

Automation analysis highlights abnormal behavior long before:

• a bearing fails,

• a motor overheats,

• a sensor drifts out of range.

→ Maintenance shifts from reactive to predictive and planned.

5. Standardizing Best Practices

By comparing data between lines or shifts:

• optimal machine settings emerge,

• cycle times can be harmonized,

• operational deviations become visible.

→ The result: stable production and reduced downtime.

Industrial analytics dashboard showing downtime reduction metrics and OEE improvement using automation data analysis.

Proven Results in Plants Using Automation Analysis

Industries applying this approach typically observe:

• 30–50% reduction in unplanned downtime

• 5–15% increase in machine availability (OEE)

• lighter, more efficient maintenance workload

• teams empowered with reliable, actionable data

Why Production Managers Should Take Action Now

As a production manager, you gain:

• clear visibility on machine health,

• control over unplanned downtime,

• decision-making supported by real data, not assumptions.

Engineer monitoring predictive maintenance data from industrial machines using automation sensors and real-time analytics.

By adopting automation analysis, you turn your production line into a predictable and high-performance system.

If you want to reduce downtime and improve machine reliability, Request a automation analysis to uncover your first quick wins.

Request a automation analysis