01
Assessment and Prioritization
Not every machine needs predictive maintenance. Start where ROI is highest.
AI Services / Build
Every manufacturer knows what unplanned downtime costs. We help you see how predictable failures are once you are looking at the right data.
01 / Close to the work
Reactive maintenance is expensive. Scheduled maintenance is wasteful. Predictive maintenance uses your operational data to tell you when a machine will need attention, what will fail, and how long you have to plan.
How we build it
A system your people can use on a Tuesday night shift.
02
Data Integration and Sensor Strategy
Connect historians, PLCs, SCADA, quality databases, maintenance records. Legacy equipment can be retrofitted with sensors where the data is missing.
03
Digital Twin and Model Development
Digital representations of critical assets. Digital twins are one tool alongside statistical process control, ML models, and physics-based simulations.
04
Dashboard and Alert Design
Designed for operators, maintenance techs, and plant managers, not executives who visit quarterly. No false alarm fatigue.
05
Change Management and Training
Getting your maintenance team to trust the data and change 20 years of habits.
Production intelligence
See what your data already knows.
Quality Pattern Detection
Catch drift before scrap
Throughput Optimization
Find the real bottleneck
Energy and Material Efficiency
Reduce hidden waste
Cross-Plant Benchmarking
Understand performance differences
Experience
Maintenance is a process. We improve it like one.
Predictive tools only pay off when the planning, scheduling, and daily habits around them improve too. We work on the whole maintenance process and the people in it, so savings show up in EBITDA, not just on a dashboard.
Equipment experience: Fischer/EBM, Nissei/ISBM, Sidel/RHBP, Aoki, and more.
Clients: Coca-Cola, Amcor, Kohler, Microsoft, WS Connelly, Dominion Manufacturing.
03 / People and process
Legacy equipment
Make old machines smart, not fragile.
30-year-old machines still run production and generate revenue. Sensor retrofits, protocol bridges, and edge computing can make old machines smart without making them fragile.
Training meets the work
The system has to fit operators and technicians, not ask them to fit the system. See how IBS trains teams for adoption.
The landscape
Start with the operation.
Vendor-Led
Start with platform, work backward to justify
Big Consulting
200-page maturity assessment, never calibrated a sensor
IBS
Start with your operation. What breaks? What costs money? Then solve that specific problem.
+ / A practical next step
A practical next step
Ready to stop guessing and start predicting?
Find the predictive maintenance work that can have the biggest impact in your operation.