Case study 2 min read
A global industrial machinery manufacturer
$1.2M saved a year with predictive maintenance and a multi-plant ERP
An industrial machinery manufacturer was losing $1.8M a year to unplanned downtime. Its three plants also had no shared view of orders or inventory. Infoloop delivered one ERP across all three plants, with predictive maintenance that flags equipment failures in advance.
- Industry
- Manufacturing
- Services
- Custom software development, Legacy modernization
- Timeline
- Results measured within six months
Introduction
The goal: one ERP for three plants, with early warning of equipment failures
The client manufactures heavy machinery for the construction, mining and agriculture sectors. It operates three plants, serves 1,200+ B2B clients and generates $350M+ in annual revenue.
The objective was a single ERP for orders, inventory, production jobs and suppliers, replacing five separate tools. Deployment could not interrupt a single shift. The platform also had to predict equipment failures before they caused downtime.
The challenge
Those operations depended on five separate legacy applications, and none of them shared data.
- Machines ran until they failed, and every breakdown pulled staff off planned work. The result was about 12 hours of unplanned downtime a month and $1.8M lost a year
- Orders were tracked manually, so every customer status request meant a walk to the production floor
- Supplier performance was judged on memory and goodwill, not on delivery data
- Each plant kept its own figures, so any cross-site question required a round of phone calls
- Head office managed three plants without a consolidated view of operations
The business needed one ERP across all three plants, deployed without stopping a single shift.
Five tools, three plants, no shared view
Each machine ran until it failed, and every breakdown pulled staff off planned work. The cost was about 12 hours of unplanned downtime a month and $1.8M a year.
The business needed one ERP across all three plants, put in without stopping a single shift.
Our approach
The equipment came from several manufacturers, and each machine reported data in its own format. We first brought every machine into one shared data model. We also involved operators and supervisors early, because shop floor adoption decides whether an ERP succeeds.
Predictive maintenance alerts
IoT sensors on each machine report its workload. Predictive analytics flag a likely failure 10 to 14 days ahead, so maintenance can be scheduled.
Centralized order management
Every production job is scheduled, tracked and dispatched in one place. Alerts warn planners before an order runs late, not after.
Supplier performance dashboard
Scores each supplier on delivery reliability, tracks inbound materials and raises routine purchase orders automatically.
Shared operational data across three plants
Head office sees available capacity at one site and a growing backlog at another.
The results
Three plants now operate on one ERP, with advance warning of equipment failures. Maintenance shifted from emergency repairs to planned work, and the savings appeared within two quarters.
-72%
unplanned downtime
$1.2M
saved each year
98%
order fulfillment accuracy
-65%
supplier delays
Technology used
A quick look at what runs behind this build.
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| What we did |
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Connect every plant to one ERP
One ERP for orders, inventory, production and suppliers across every plant, deployed one site at a time. A written quote before work starts, and support after launch.