Cement & Construction

Kohat Cement

From manual logs to AI-powered predictive maintenance across 8 cement manufacturing plants

8+
Manufacturing Plants
75%
Maintenance Efficiency
₹6.8Cr
Annual Savings
Back to Customer Stories
The Manual System

Paper logs and reactive breakdowns

Kohat Cement operated 8 manufacturing plants with hundreds of critical machines. Equipment maintenance was managed through paper logs, Excel sheets, and phone calls. When machines broke down, production stopped until technicians could diagnose and fix issues.

Plant managers tracked maintenance schedules manually, often missing preventive service windows. Technicians carried physical manuals for different equipment types. Finding spare parts meant searching through inventory logs. Each breakdown cost millions in lost production.

The team knew they needed a predictive maintenance system, but configuring one seemed impossible without months of IT work to map equipment hierarchies, maintenance protocols, and spare parts databases.

Why Generic Tools Failed

Cement plants aren't one-size-fits-all

Kohat tried generic CMMS platforms. The implementations failed because cement manufacturing has unique requirements. Each plant had different equipment configurations. Maintenance protocols varied by machine age and production load. Spare parts had complex interdependencies.

Setting up equipment hierarchies for 8 plants would take 6 months. Configuring maintenance schedules for different machine types required constant IT changes. Creating part replacement workflows needed extensive customization. Every time equipment was upgraded, the whole system needed reconfiguration.

The operations team needed a system that understood cement plant operations, not a blank database they had to configure manually.

AI learned their cement plant operations

Fieldproxy's AI analyzed 5 years of maintenance logs, equipment specifications, and breakdown patterns. It automatically configured workflows specific to their manufacturing environment.

Equipment-Specific Protocols

AI generated maintenance checklists for each machine type - kilns, crushers, conveyors, mills - with timing based on production hours and wear patterns

Predictive Scheduling

AI analyzed breakdown history to predict maintenance windows, automatically scheduling preventive service before failures occurred

Smart Parts Management

AI matched equipment issues with spare parts inventory, auto-creating procurement requests when stock levels dropped below safety thresholds

Self-Optimizing Workflows

As technicians completed maintenance, AI refined schedules and protocols, automatically adjusting based on actual equipment performance data

The Transformation

Manual Maintenance Management

Paper logs for equipment tracking

Reactive breakdown response

6 months to configure CMMS

Manual maintenance scheduling

Physical equipment manuals

Excel-based parts inventory

AI-Configured Predictive System

Equipment auto-tracked by AI

Predictive maintenance alerts

5 days for AI configuration

AI-optimized scheduling

Digital protocols by machine

Smart inventory management

Results

From reactive chaos to predictive efficiency

75%
Maintenance efficiency improvement

AI-optimized scheduling reduced maintenance time while increasing equipment uptime across all plants

82%
Reduction in breakdowns

Predictive maintenance caught issues before failures, dramatically reducing emergency repairs

5 days
To configure entire system

AI configured all 8 plants vs 6 months for manual CMMS setup

₹6.8Cr
Annual savings

Reduced downtime and optimized maintenance costs across manufacturing operations

AI configuration changed everything

Kohat Cement's transformation shows how AI eliminates the setup barrier. Instead of spending 6 months configuring equipment hierarchies and maintenance protocols, AI learned their operations from existing data and configured everything in 5 days. Now when equipment is upgraded or processes change, AI adapts automatically - no IT work needed. That's the power of AI configuration.