FAILURE MODE A
Unplanned downtime costs far more than the repair itself.
Idle operators, missed dispatches, expedited freight and scrap from a stop mid-cycle. The bearing is the cheapest line on the bill.
Simulated line view6 assets4 linked SKUsPredictive maintenance + spare parts
AI equipment maintenance & spare parts management
Catch the wear pattern
before the machine stops.
Indussbz watches equipment health signals, flags maintenance before failure, and keeps the right spare parts in stock, so unplanned downtime stops being the norm.
M1VMC-01
CNC machining centre
96Healthy
M2HP-02
Hydraulic press
91Healthy
M3AC-03
Screw compressor
79Watch
M4CD-04
Conveyor drive
93Healthy
M5PU-05
Coolant pump
94Healthy
M6IM-06
Injection moulder
89Healthy
Spare parts store - Line 24 SKUs linked
- Bearing 6205-2RS CD-047 / min 8
- V-belt B-42 CD-0414 / min 6
- Seal kit, ram cylinder HP-025 / min 3
- Air filter element AC-039 / min 4
Alert feedScoring
01
Where downtime comes from
Breakdowns are rarely random. They are unread patterns.
Most plants already hold the signals: runtime hours, operator complaints, the last three times that motor was opened up. They just sit in logbooks, spreadsheets and memory, disconnected from the parts store.
FAILURE MODE B
Spare parts run out exactly when you need them most.
Stock is counted against last year's consumption, not against the machines that are visibly wearing out this month.
FAILURE MODE C
Schedules are built on calendars, not actual wear.
A pump that runs two shifts and one that runs three get the same PM interval. One is over-serviced. The other fails early.
02
How it works
One loop. Signal to shelf to work order.
Each step feeds the next, so a detected wear pattern does not stop at an alert. It ends with the part in hand and the job on the schedule.
STEP 01
Monitor
Runtime hours, reported symptoms, meter readings and maintenance history feed a continuous health score for every machine.
Health score 0-100STEP 02
Predict
Developing wear patterns are flagged before they become failures, each with a stated confidence level and a likely time window.
Confidence shownSTEP 03
Stock
Flagged needs are checked against spare-parts stock. If a part would drop below minimum, a reorder suggestion is raised.
Reorder triggersSTEP 04
Schedule
The repair is slotted into the next planned stop, alongside routine PMs, instead of waiting for the machine to choose the time.
Condition-based
What the AI actually does
Three jobs, done continuously.
- 01
Scores equipment health
Every asset gets a live score from the operating and maintenance data you already have. No sensors required to start; sensor feeds sharpen it.
- 02
Flags wear before breakdown
Patterns like rising vibration complaints, shortening intervals between repairs or abnormal runtime are surfaced with a confidence level, not a guess dressed as certainty.
- 03
Ties alerts to the parts store
Each flagged need is matched to the parts it will consume. Stock that would fall below minimum triggers a reorder suggestion.
What it does not do
Not a marketplace. Not an exchange.
Indussbz is a single-company maintenance and inventory tool. Your data, your plant, your suppliers.
- Does not connect you to third-party sellers
- Does not handle procurement transactions between companies
- Does not place orders without your approval
- Does not override a technician's call on the floor
Reorder suggestions route to your own approved vendor list and wait for sign-off from the people you choose.
03
What feeds the health score
Start with the data you already log.
Health scoring works from day one on records most plants keep. Add sensor data later when it makes sense for a specific asset.
IN-01
Runtime hours
Shift logs or hour meters per asset
IN-02
Symptom reports
Noise, heat, leaks, vibration noted by operators
IN-03
Repair history
Past breakdowns, parts replaced, time to repair
IN-04
Meter readings
Temperature, pressure, current taken on rounds
IN-05
Sensor feeds
Optional CSV or API import from existing sensors
04
The maintenance engine
Five modules. One shared record per machine.
MOD-01
CD-04 Conveyor drive38
AC-03 Screw compressor79
HP-02 Hydraulic press91
Predictive Alerts
Health scores and wear-pattern detection with stated confidence
MOD-02
Spare Parts Inventory
Stock levels tied to the failures you can see coming
MOD-03
Maintenance Scheduling
Condition-based work orders alongside routine PMs
MOD-04
Downtime Tracking
Every stoppage logged, coded and costed
MOD-05
Vendor & Reorder
Your approved vendors, your approval chain
0
Integrated modules
Alerts, inventory, scheduling, downtime and reorders on one machine record
0
Alert severity levels
Watch, high and critical, each with a stated confidence
0/7
Health scoring
Scores update whenever new runtime, readings or reports land
0
Third-party sellers
Reorders go only to vendors you have approved
05
Built for both ends of the plant
One record. Two very different views.
Plant Managers
See what downtime is costing, by line and by month.
- Plant-wide health dashboard across every asset
- Downtime cost by cause, line and shift
- Maintenance spend planned, not discovered
Maintenance Teams
Start every shift knowing what to fix first.
- Prioritised task list ranked by risk
- Part availability shown on each job
- Fewer 2 a.m. callouts, more planned work
Predict before you repair
A failure you saw coming is a planned job. A failure you did not is a crisis.
Your vendors, your decisions
The platform suggests. Purchasing and maintenance calls stay with your team.
Built for the plant floor
Clear screens for technicians on a tablet, not a spreadsheet dressed as software.