Using AI and IoT to Reduce Maintenance Costs: A Case Study

Why It Matters

• High-impact cost savings: One lab site was spending over 10x more on repairs than another due to differences in usage patterns
• Preventable downtime: Inconsistent preventive maintenance led to unnecessary instrument downtime and costly repairs
• Scalable solution: Elemental Machines demonstrates how IoT and AI analytics can transform maintenance strategies across multiple lab sites—without disrupting operations

What’s Inside

• The challenge: Identifying why three labs with identical flow cytometers had drastically different repair and downtime costs
• The approach: Deploying Elemental Machines’ Element-U devices to noninvasively capture utilization data from every cytometer
• The outcome: Laboratory operational cost savings and improved flow cytometer performance – download to find out how

Proof Points

• Standardizing maintenance schedules across all sites yielded potential, impactful savings
• Elemenal Machines’ device captured continuous power data without unplugging or downtime