Produce more and stop less, with your plant visible in real time
Lyna OPS combines AI-powered production monitoring and IIoT sensors to give you each machine's OEE in real time, log every stop automatically, and anticipate failures before they halt your line. A single number tells you whether your plant is doing well; a single alert tells you what to fix first.
87%
Plant OEE
real time · trending up
8,420 / 9,000
Shift output
93% of target
47 min
Unplanned downtime
today · lower is better
~5 days
Predicted failure
Line 2 motor · high risk
The platform
Your plant, live in the platform
The OPS module for production: one number tells you how it's going, one alert what to fix first.
Estimates · late reports · paper
Producing blind costs more than you think
When production is measured with manual entries, delayed reports, and end-of-shift estimates, the real causes of low efficiency stay hidden: you don't know how long each machine was stopped, how many parts came out per shift, or how fast each line is actually running. On top of that sits the most expensive risk of all: the unexpected failure that stops a whole line with no warning. That blind spot turns into waste, late deliveries, and costs no one sees until they've already happened.
Capabilities that transform your plant
Real-time OEE per machine
Automatically calculates availability, performance, and quality for each piece of equipment, so you know at a glance how your plant is doing and where to focus improvement first.
Real-time cycle counting
See production piece by piece as it happens, without relying on manual entries or spreadsheets at the end of the shift.
Automatic downtime logging
Every stop is recorded with timestamp, duration, and affected line, then ranked in a Pareto of causes that shows what to tackle first.
Predictive maintenance
The system learns each machine's normal behavior and warns you in advance when signs of deterioration appear, so you can intervene before a failure halts the line.
IIoT sensors for signal monitoring
Connect sensors of every kind (vibration, temperature, current, and more) to monitor the real condition of your machines live and correlate each signal with wear.
Real vs. theoretical speed and shift reports
Compare each line's actual speed against its theoretical target to uncover hidden performance losses, with automatic end-of-shift summaries for supervisors and management.
More output and fewer stops. Predict it before you regret it.
Stop operating blind: monitor, understand and decide in real time.
87%
Plant OEE · trending up
How we work
Assessment and critical lines
We map your lines, machines, and stop modes to size the solution and prioritize where monitoring delivers the greatest return.
IIoT instrumentation
We install non-invasive cycle and condition sensors (vibration, temperature, current) on your equipment, without modifying its operation.
OEE and maintenance rules
We configure OEE per machine, the downtime cause catalog, and the thresholds that trigger each predictive alert.
Integration and training
We connect to your ERP or MES and train your team so the plant runs on real data from day one.
Where it has the greatest impact
Food & beverage
Filling, packaging, and pasteurization lines monitored to reduce downtime and meet daily volume with no surprises.
Automotive
Assembly and stamping lines with piece-by-piece monitoring, cycle time control, and OEE visible at every station.
Pharmaceutical
Regulated rooms and lines where every batch counts: critical equipment monitoring, downtime logging, and process evidence for audits.
Plastics
Injection molding and extrusion machines with cycle counting, speed monitoring, and condition sensors to get the most out of every mold.
Critical rotating equipment
Motors, compressors, pumps, and fans watched through vibration and temperature to anticipate failure before the stop.
FAQ
Frequently asked questions
OEE (Overall Equipment Effectiveness) combines availability, performance, and quality into a single indicator. With that one figure a manager immediately knows whether the plant is doing well or badly and, once broken down, exactly which of the three factors is holding production back. Lyna OPS calculates it per machine and in real time.
IIoT sensors monitor each machine's real condition (vibration, temperature, current) and the system learns its normal behavior. When an abnormal trend appears, it warns you in advance so you can plan the intervention before a failure halts the line. The idea is simple: predict it before you regret it.
Virtually any. Lyna OPS connects sensors of every kind for signal monitoring (vibration, temperature, current, cycle counting, and more) that adapt to almost any machine without modifying its operation. The exact set is defined during the assessment based on your equipment and process.
A typical implementation is operational within a few weeks: it includes sensor installation, OEE and downtime rule configuration, and team training. We usually start with a group of critical lines or machines to show value quickly and then scale.
Yes. Lyna OPS connects with major ERP and MES systems to synchronize production orders, report progress, and keep a single source of truth, with no double entry.
Measure to produce more and stop less
Schedule a free assessment and see how much efficiency you're leaving on the table and which failures you can start anticipating today.
