IoT & Artificial Intelligence
Predictive maintenance and energy optimization pilots for manufacturing SMEs
A focused 4–8 week pilot on one machine or production area, designed to prove value before scaling across the plant. MARKNA helps manufacturers use telemetry, IoT, and AI to detect failure risks, understand energy patterns, and improve operational decisions under real factory constraints.
Two practical pilot tracks
Detect early failure signals, reduce unplanned downtime, and support better maintenance scheduling.
Identify abnormal energy consumption, idle-time patterns, inefficient operating windows, and opportunities to reduce waste.
Estimate your downtime and energy savings opportunity
Use this simple estimator to explore whether a focused IoT and AI pilot may be worth investigating. The result is indicative only and does not guarantee savings, ROI, uptime improvement, or energy reduction. Actual outcomes depend on equipment, operating conditions, data quality, and implementation scope. After a short technical assessment, MARKNA can provide a more accurate estimate based on your environment, equipment, and available data.
Inputs
Scope
Predictive Maintenance estimate
Energy Optimization estimate
Limits are included to keep the estimate realistic for SME manufacturing scenarios.
Results
Example estimate based on editable assumptionsValues are calculated only from the assumptions entered above. MARKNA validates assumptions during discovery before giving any pilot recommendation or commercial estimate.
This calculator provides an indicative estimate only. It does not guarantee savings, ROI, uptime improvement, or energy reduction. Actual outcomes depend on equipment, operating conditions, data quality, and implementation scope.
What affects pilot cost?
The cost of a predictive maintenance or energy optimization pilot depends on the current digital maturity of the machine, available data sources, and the industrial environment. Main cost factors include:
- Whether the machine already exposes data through PLC, SCADA, OPC-UA, Modbus, or an energy meter
- Whether additional sensors are needed, such as vibration, temperature, current, or power meters
- Whether the pilot uses a simple edge gateway, an industrial gateway, or an existing factory system
- Whether the deployment is edge-only, cloud-connected, or hybrid
- Number of machines included in the first phase
- Dashboard, alerting, reporting, and integration requirements
- Site-access, installation, and testing requirements
MARKNA usually recommends starting with one critical machine or one production area before estimating a wider rollout.
A short technical discovery is usually needed before giving a reliable pilot estimate.
We start with a short technical workshop — no long-term commitment required.
Book a discovery callPilot structure
How a predictive maintenance pilot runs
We follow a clear, time-boxed sequence so you get a working pilot and a concrete decision point at the end — not an open-ended research project.
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Workshop with operations and maintenance to choose the right machine, failure modes, and success criteria.
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Pragmatic choice of sensors and edge hardware that fit the equipment and environment.
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Time-boxed pilot scoped around one machine and one operational outcome.
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Reliable ingestion of time-series data into a clean, queryable pipeline.
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Initial model tuned to your equipment, validated against real events where possible.
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Operator-friendly view with alerts your maintenance team can actually use.
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Written report with results, limitations, and a clear recommendation for rollout.
Outcomes we aim for
Every pilot is scoped around measurable operational outcomes — not technology for its own sake.
- Lower unplanned downtime on the pilot machine
- Earlier detection of failure precursors
- Better-informed maintenance scheduling
- Operational data your team can trust and reuse
- Better visibility into machine energy consumption
- Detection of abnormal energy patterns
- Identification of idle-time or inefficient operating periods
- Practical recommendations for reducing energy waste
Factory Visibility
See MARKNA Factory Visibility in action
MARKNA Factory Visibility is a practical dashboard for manufacturers who want better visibility into machine status, downtime, energy use, OEE, and critical maintenance alerts.
The demo shows how a factory manager or maintenance lead can receive a critical machine alert on a phone, open the dashboard, and acknowledge or resolve the alert.
The current demo uses sample factory data and is intended for private walkthroughs, pilot discussions, and one-machine assessment planning.
The demo uses sample data. Real factory pilots require a short assessment and safe read-only integration planning.
Have a downtime or energy-efficiency challenge we should look at?
We start with a short technical workshop — no long-term commitment required.