Real-time AI insight and quick team collaboration avoids downtime and lost product
Industry – Pharmaceutical //
Machine – Tablet press //
Fault Type – Bearing wear due to fluting //
Outcome – $82K in savings, including 20 hours of avoided downtime and 4.8M tablets saved
This global pharmaceutical manufacturer has been partnering with Augury for Machine Health Solutions since 2020, using end-to-end prescriptive maintenance insights to monitor production, packaging, and utility assets.
The story
One of the many production assets being monitored is a tablet press operating in a clean room. One day last fall, Augury AI updated the machine’s health status from “monitor” to “danger” due to possible fluting in the motor bearings (damage caused by electrical discharge). Following Augury’s recommendation, the pharma company’s on-site maintenance team and vibration analyst inspected the motor and verified the issue. They determined that the machine could continue running until the next scheduled downtime period.
Image 1:
Augury’s algorithms analyze over 840 unique feature sets. This image depicts the velocity RMS, showing a sudden increase and rapid-cliff detection in the motor velocity trends due to a possible fluting issue.
During that downtime, about four weeks following the alert, the maintenance team removed the existing motor and replaced it with an on-hand spare. Once the Augury sensors were reinstalled and the tablet press was realigned for baseline, Machine Health data confirmed that the motor was functioning normally and the data confirmed a healthy status.
A third-party inspection confirmed Augury’s findings: the bearings were fluted due to shaft voltage, which would require repair on the opposite end drive and a new resolver.
The Outcome
Thanks to early detection of the motor bearing issue, which allowed the team to plan repair during a scheduled maintenance window, the company saved $82K in avoided downtime and lost product, which would have reached 4.8 million tablets.
Eager to understand the details behind the savings, the pharma company’s leadership, finance, operations, and maintenance teams worked together to quantify the benefits of this Machine Health win. Here is how they came up with the figure:
- Cost of downtime per hour: $4,100
- Product loss per hour of downtime: 240K tablets
- Total hours of work: 20
- Hours to remove tooling and clean room: 8
- Hours to install spare (if available): 6
- Hours to clean and set up after maintenance: 6
- Total: $82K and 4.8 million tablets
While this was a significant win for the manufacturer, the savings and benefits extend beyond the bottom-line numbers. Although not quantified, other avoided downsides include:
- Per-hour labor costs
- Lost profit margin on unproduced product
- Additional lines/sites used to make up for lost product
- Cost of acquiring new motor if no spare was available ($10k-15k est.)
- Production time lost to acquiring new motor (6 weeks est.) or expedited part costs
- Time spent on investigation, RCAs, and CAPAs
- Quality issues and/or raw material losses
- Product deviation costs (e.g., batch yield % is too low or metal shavings)
- Deviation labor hours (16-24 hrs @ $70/hr, est)
- Safety risks/injury
- Additional clean-room sterilization costs
- Other collateral impacts
Keys to success
Many factors contribute to Machine Health wins, and this success story is no different. Beyond the real-time AI data itself, the following played vital roles in making this win possible:
- High engagement and communication within the Augury platform between onsite teams and Augury Vibration Analysts
- Collaboration between internal customer teams
- Fast root-cause-analysis by Augury’s AI and Vibration Analysts
- Timely, expert action by the customer’s maintenance and reliability teams
Even more good news: Machine wins like this help with solution adoption rates, improve long term maintenance strategy, and boost team and company morale.
Learn more about how we’re helping pharmaceutical manufacturers cut downtime, improve product quality, and achieve fast value and high ROI.
