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Scenario · Operations & productionAn alarm at 2:14, resolved by 2:31
The production incident, end-to-end
The night shift does not have to wait for morning. An agent diagnoses the alarm on machine data, raises the ticket, reserves the part and wakes the right person on Teams only when a decision is needed.
Executive summary
Line alarms get lost between shifts; response depends on who is around and what they know.
The agent diagnoses on MES/CMMS data, launches the procedure and involves people only for decisions.
Shorter MTTR, less downtime, every failure with a complete history.
MES, CMMS, spare-parts store, Teams; UiPath agents + robots, Maestro™ orchestration.
A three-shift plant, 350 alarms a month
The 2:14 alarm lands on a panel nobody watches continuously. The operator finishes the round, comes back, classifies it. If it is beyond the shift, it waits for the morning briefing.
By morning it turns out the part should have been ordered overnight, and maintenance is the last to know. MTTR grows mainly because information arrives too late.
The current reality
- SystemThe alarm appears in the MES
- WaitingWaits until someone notices it between tasks
- HumanThe operator classifies from experience
- HumanPhone calls: foreman, maintenance, parts store
- Error riskKnowledge of similar failures lives only in heads
- WaitingThe part is ordered only in the morning
- HumanThe failure report written after the fact, or not at all
The hidden cost of the current process
Costs beyond the downtime itself
- 105 hours a month of human alarm triage, 60% of it on noise.
- Every MTTR hour on a bottleneck line means an unrecovered plan and weekend overtime.
- Failure history is scattered, so the same problems return because nobody sees the pattern.
The cost of doing nothing
You pay for the automation once; the manual process costs you again every month.
The process after automation
- AutomationThe agent reads the alarm and machine data in a second
- AutomationMatches against history: known cause, known procedure
- AutomationRaises the CMMS ticket and reserves the part
- HumanWakes the technician on Teams when a decision is needed
- AutomationTracks SLA to closure and writes the failure report
What the automation handles
- Round-the-clock triage of every alarm
- Procedures: ticket, part, notifications, escalations
- Automatic history and report for every failure
When a human decides
- Line-stop decisions
- Novel failures with no pattern in history
- Priorities when resources conflict
Before
After
Value model: example assumptions
Business benefits
- MTTR in minutes where today it is hours
- Night shifts with the same support as day shifts
- Repeat failures caught as a pattern
- Maintenance works from system data
Board-level KPIs affected
MTTR · OEE · unplanned downtime · maintenance backlog
What management gains
- One live picture of failure rates across lines
- Hard data for overhaul and capex decisions
- Procedures followed the same way every time
Estimate it for your organisation
An illustrative estimate based on your inputs. It models released capacity and is not a savings promise.
Systems in this scenario
Inputs
- MES / SCADA
- CMMS
- Parts store
Mientha agentic layer
- UiPath Agent Builder
- UiPath robots
- Maestro™ · Action Center
Core systems
- CMMS
- ERP (parts orders)
- Teams
Human approval: Teams / Action Center
What we deliver
- Analysis of alarm logs and failure history
- A diagnosis agent with a known-cause base
- Automated procedures: ticket, part, escalation
- Teams notifications and decisions for the shifts
- MES/CMMS/ERP integrations
- A monthly failure report and pattern review
What we need to start
- Alarm logs from 1-3 months
- Response procedures (even if only in foremen's heads)
- CMMS access and the critical-parts list
- A shift foreman for 2 workshops
Implementation roadmap
Discovery
We map the process, data and exceptions with process owners.
Design
Target flow, business rules, approval thresholds.
Build
Agents, robots and integrations in your environment.
Validate
Tests on real cases, exception handling.
Go-live
Controlled rollout with human oversight.
Optimise
Monitoring, reporting and continuous improvement.
Duration depends on the number of systems and rules; a single process usually takes a few weeks.
Risk and controls
Autonomy under control
- The agent never controls machines; it works on information and procedures
- Stops and safety decisions always belong to people
- Every action logged: who, what, when, on what basis
- OT-network access only via existing, approved interfaces
Why now
- Night-shift staffing gaps will not disappear, so the night shift needs support
- Each month ~140 alarms are handled slower than necessary
- You already have the machine data, but nobody reads it at night
Why this matters to:
Less unplanned downtime and a predictable production plan.
The night shift gets the same support as the day shift.
The team arrives with a diagnosis and the part.
Questions we usually hear
That is why the agent never touches control systems: it organises the information and procedures around the machines. The OT layer stays unchanged.
They do, and the agent captures that knowledge in procedures. It stays in the plant when a foreman retires.
We start with one, the most expensive to stop. Its patterns and integrations halve the rollout time on the next lines.
When this may not be the right solution
- Only a dozen alarms a month, all of them novel
- No CMMS or failure history at all: start collecting it first
- Machine data unavailable outside the control room
A question for your next board meeting
Which of last quarter's failures would have ended differently if the response had started one second after the alarm?
Solutions in the library
The same process as an implementation plan
The scenario shows the process with an AI agent on an example company. Library solutions describe the same or a neighbouring process with a value model and an implementation plan.
The tool records what happened. Finding owners, chasing updates and reading nothing on Friday is done by people.
See the solution Operations & productionThe daily production report without the 6 a.m. spreadsheetProduction controllers retype MES numbers into a spreadsheet the meeting does not trust.
See the solution Operations & productionPreventive maintenance that runs to planWork orders are released by printer, and the completion reports are typed back a week later.
See the solutionWe deliver it through our service AI agents on Microsoft Teams.
The example company in this scenario works in Manufacturing & industry.
What does one hour of downtime on your key line cost?
One month of alarm logs is enough. We will show which alarms the agent would handle on its own and which would need a human decision.
Let us talk about your plant