Machine Monitoring Software
Understand what your machines produced, when they stopped and where the next investigation should begin. Bharat AI Automation connects supported machine and sensor data to live production and OEE dashboards, downtime tracking and shift reports, helping manufacturing teams discuss output and maintenance using a shared record of the shop floor.
Illustrative interface with sample data. Select the image to explore it at full size.
A better fit for your daily work.
Output becomes visible after the shift
A tally collected at the end of the day cannot explain a developing production shortfall.
Downtime discussions rely on memory
Short interruptions are easily forgotten when staff reconstruct a shift later.
Machine comparisons use different assumptions
Production measures become misleading when each team defines operating time or good output differently.
Everything your team needs, connected.
Machine data collection
Acquire agreed machine signals through supported interfaces and sensors. The technical assessment identifies what can be measured reliably, which signals already exist and what additional equipment may be required.
Live production dashboard
See current production information for the monitored equipment in one view. Supervisors can focus attention on a changed condition and then ask the floor team for the operational context.
Machine status and downtime
Track available running and stopped states and review interruption periods. Agree how downtime context is captured so the team can distinguish operational causes from a missing or unreliable signal.
OEE reporting
Present overall equipment effectiveness using the agreed availability, performance and quality inputs. The setup must define planned time, reference rates and good counts before comparisons can be trusted.
Shift and alarm records
Review production and recorded alarms by shift. This creates a consistent conversation between supervisors and maintenance teams when the same interruption appears across several production periods.
ERP production connection
Connect the agreed production data with Bharat AI ERP requirements. Define which records move between systems and how the team checks mismatches before treating machine totals as business transactions.
From the first task to a clearer daily picture.
Select the monitoring questions
Start with the decisions managers need to make: output gaps, recurring stops or machine utilisation. These questions guide signal selection and prevent collecting readings that nobody uses.
Validate machine signals
Compare captured counts and states with observations made by responsible plant personnel. Check the meaning of each signal before displaying the resulting production measure to supervisors.
Watch the shift
Use the live dashboard to see current machine conditions and output. Staff investigate unusual changes through the agreed shop-floor process rather than assuming every change indicates a fault.
Explain losses
Review downtime and production differences with the operators involved. The recorded timeline supports the discussion, while people provide context about changeovers, materials and other events.
Plan the next improvement
Use shift evidence and advisory alerts to choose a focused investigation. Follow the result across later periods using the same calculation definitions and comparable production conditions.
Useful insights. Your team in control.
Use forecasts and alerts to guide your review, with people making the final decisions.
Predictive maintenance guidance
Analyse suitable machine history for patterns that may indicate developing problems. Maintenance personnel review these advisory alerts with equipment condition and inspections; they are not guaranteed predictions of failure.
Output forecasting
Estimate likely production from recorded performance patterns. The supervisor should interpret the estimate alongside scheduled changeovers, product mix and material availability before committing to a delivery expectation.
Supervisor notifications
Route configured alerts to supervisors on WhatsApp so relevant changes receive attention. Agree recipients and event criteria during setup to keep the messages useful rather than generating constant interruptions.
A clear view of what matters.
Production by shift
Compare recorded output for selected machines and shifts.
Downtime history
Inspect interruption periods to identify repeated loss patterns.
OEE components
Look at availability, performance and quality separately before interpreting the combined figure.
Maintenance alert review
Bring advisory alerts into regular maintenance discussions.
Made to work with the right tools.
Bring your existing equipment details. We’ll review compatibility, connectivity and the modules needed for your installation.
- Machine interfaces and existing PLC signals assessed individually
- Industrial sensors for the agreed monitoring points
- Suitable gateways and supported communication equipment
- Shop-floor display or supervisor workstation
A practical plan for moving forward.
Choose a focused pilot
Identify representative machines and a small set of production questions. Agree success criteria around data quality and useful reporting before expanding the number of monitored assets.
Define calculations
Agree machine states, planned time, reference rates and quality inputs. Document the assumptions behind each metric so operators and managers interpret the dashboard consistently.
Verify against the floor
Compare collected information with real production observations across representative conditions. Resolve missing counts or ambiguous states before using the reports for operational decisions.
Train and expand
Train production and maintenance teams to interpret dashboards and advisory alerts. Extend the rollout after the pilot confirms useful data, clear responsibilities and an agreed support process.
Before you choose your software.
Can older machines be monitored?
Some machines can be monitored using available signals or additional sensors, but this needs an equipment assessment. Machine age alone does not establish compatibility or the measurements that will be possible.
What is OEE measuring?
OEE combines availability, performance and quality into one production measure. Its usefulness depends on agreed definitions and reliable inputs, so the individual components should also be reviewed.
Will the dashboard explain every stoppage automatically?
Machine states can identify that a stop occurred, but the underlying reason may require operator or maintenance context. Discuss the intended downtime classification process during the demo.
Can supervisors receive WhatsApp alerts?
Yes, supervisor alerts are part of the Automation offering. The agreed scope should define which events trigger messages, who receives them and how staff follow up.
Do predictive alerts control the machines?
Predictive guidance is advisory in this monitoring workflow. Trained personnel retain responsibility for maintenance and critical controls; any separate control integration requires its own engineering scope.
See your workflow in action.
Bring your real tasks and questions. We’ll use them to discuss the right configuration, equipment and rollout.
- Representative machine list
- Current production and downtime reports
- Shift calendar and planned operating time
- Available count, state and quality signals
- Priority maintenance and output questions
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