A major steelmaking and mining group with an integrated steelworks in the CIS region.
Location: CISAutomatic identification and defect inspection gave the maintenance team a digital condition history for sinter pallets moving through an operating sintering machine.
The maintenance objective
The steelworks sought to reduce unplanned sintering-machine downtime and improve decisions about when individual pallets should be removed for repair. A useful inspection system had to recognise the pallet, identify a defect and keep the evidence attached to the correct equipment record.
Identification from both sides
Cameras on both sides read the pallet’s identification number as it passes. The workflow uses agreement between the two observations to improve confidence in the identification. Defects detected during the same passage are linked to the identified pallet.
The interface shows the pallet sequence schematically alongside live camera views. Each pallet has its own record with condition information, photographs and video evidence.
Eight defect categories
The inspection scope includes damaged or missing sidewall elements, missing grate-bar retaining pins, seized or missing running rollers, damaged or missing wheel covers, and missing sidewall fasteners. The source describes eight categories in the full defect taxonomy.
Condition findings are highlighted on a diagram of the pallet. The overview uses different colours to distinguish normal condition, non-critical defects and critical defects. A technologist can review and cancel a finding.
A repair history rather than isolated alarms
Inspection is repeated as pallets pass the cameras again. Findings and actions are retained in the history, supporting decisions on equipment withdrawal, planned repairs and review of completed work. Reports can be exported and sent by email.
Reported operating result
The prototype entered industrial operation. Reported detection accuracy was 95–98%, with event processing and notification taking no more than five seconds in the described deployment.
These figures apply to the project’s defect classes and evaluation conditions. They do not represent a universal inspection accuracy for other sintering lines.