Plant Manager Case Study: Reducing Maintenance Costs in Food and Beverage
Every plant manager in food and beverage who has moved from reactive to predictive maintenance says the same thing after the first prevented failure: the conversation inside the business changes immediately.
What changes it is not the operational data. It is the dollar figure. In F&B, that dollar figure is typically larger than anyone expected, because a single mid-run failure on a critical processing line carries production loss, product disposal, sanitation restart time, and emergency repair costs that rarely appear in the same report. When the team can point to a specific pump, a specific alert date, and a complete calculation of what that event would have cost across all four cost categories if it had been missed, the maintenance program becomes a financial argument that travels upward through the organization in ways that downtime percentages never do.
This article draws on real Tractian customer results from food and beverage operations. The outcomes below are documented and verifiable. Each case study is linked so you can read the full story. The goal of this guide is not to provide a general argument for predictive maintenance. It is to show specifically what F&B plant managers did, what they got, and what made the difference between a result that justified expansion and one that stalled.
What Most Plant Managers Get Wrong About Using Peer Results
They see the headline number ($1 million saved, 53% cost reduction) and attempt to replicate the technology. They skip the process that produced the result.
Ingredion's $1 million in savings at a single plant did not come from the sensor installation. It came from the structured alert-to-work-order process the team built around the data. Kraft Heinz's 53% reduction in corrective motor repair costs happened because one technician acted on an off-hours alert, which built team confidence in the system immediately. That confidence was not a byproduct of better technology. It was the result of deliberate early-win documentation and team-level follow-through.
Three patterns that separate the F&B plants that get results from those that stall:
They do not measure before they deploy. In food and beverage, a mid-run failure on a critical processing line carries four cost categories: production loss, product disposal, sanitation restart time, and emergency repair cost. Those four numbers almost never appear in the same report. Plant managers who build a complete cost picture before deployment have a precise before-and-after comparison that funds the next phase. Plant managers who skip this step have an operational improvement story, not a financial one.
They deploy on the wrong assets first. The highest-criticality assets in F&B are the ones with no backup, a long restart window, or a direct food safety consequence if they fail unplanned. Start with those. Ingredion's standout result came from a single DSM pump with a known three-day outage history and no spare. One prevented failure on that asset covered a significant portion of year-one program cost.
They underestimate the cultural element. Cintia P. at Kraft Heinz described the mindset shift as the real outcome, not just the cost savings. A maintenance team that trusts the data acts on alerts consistently. A team that does not trust the data lets alerts pile up unreviewed. The technical deployment is the easy part. Building team confidence in the first 30 to 60 days is the constraint.
The Challenge F&B Plants Share
The pattern is consistent across food and beverage, whether you run continuous process lines, batch operations, or high-growth scale-ups. The same assets fail repeatedly. Each failure in a continuous process line carries costs beyond lost production: product disposal, sanitation restarts, and compliance documentation that lands on the quality team. The maintenance team is skilled and hardworking, but they are permanently in emergency response mode.
The solution everyone agrees on in principle, getting ahead of the failures before they happen, has not had a practical path until now.
Ingredion: $1 Million Saved at a Single Plant
Company: Ingredion, a leading food ingredient manufacturer. Plant: North Kansas City.
The challenge: Hundreds of machines running around the clock across multiple facilities. At the North Kansas City plant, teams faced significant roadblocks that traditional maintenance tools could not address: hard-to-reach assets caused delays in inspections; no early warnings meant failures were caught too late; PM schedules missed subtle issues like alignment problems or bearing wear. In one case, a critical pump with no spare parts on hand failed, leading to a full three-day shutdown.
"There were some issues that I would say, if not for having Tractian, we would have never noticed. For example, a lubrication problem: we could go out and lubricate it and recheck it on Tractian platform and see that it fixed the problem. It was pretty impressive for that, the results we got early on."
Jacob Hoffine, Reliability Engineer, Ingredion
The approach: Real-time condition monitoring sensors deployed across key plants, giving the team early alerts on issues like unbalance, looseness, or lubrication problems before they escalate into stoppages. One standout example: a looseness defect was detected on a DSM pump, a machine with no backup and a known history of three-day outages. A work order was issued immediately, and a costly shutdown was avoided.
The result at one plant:
- $1,000,000 in production savings
- $223,000 in maintenance savings
- 168 hours of avoided downtime across critical equipment
- Clear, traceable ROI from condition-based alerts and faster issue resolution
Read the full case study: Ingredion Adopts AI to Detect Failures and Boost Machine Uptime
Kraft Heinz: 53% Reduction in Corrective Motor Repair Costs
Company: Kraft Heinz, a global food and beverage brand. Plant: key production hub with its own tomato processing operation.
The challenge: In 2023, the plant spent over $125,000 on corrective maintenance for electric motors alone. Breakdowns caused unplanned downtime, impacted asset availability, and increased logistics and repair costs. The team needed a way to anticipate failures without overloading technicians with additional manual inspection work.
A proof point from the field: On a weekend, one technician received a high-temperature alert (120 degrees C) from a 150 HP motor responsible for tomato concentration. Even though he was off duty, he notified the team immediately. Upon inspection, they found a loose fan and fixed it before damage occurred. A major failure avoided. Team confidence in the system built from that single event.
The result:
- 53% reduction in corrective maintenance spending on electric motors
- More than 1,000 hours of downtime avoided
- 100% uptime for all monitored critical motors
- The savings funded a new internal motor rewinding room
"We have seen a real change in our daily routine. It is not just about having access to reliable insights. What really stands out is the mindset shift. Our team now sees technology as a partner in decision-making, not just a tool for the future."
Cintia P., Maintenance Manager, Kraft Heinz
Read the full case study: Kraft Heinz Cuts Corrective Motor Repair Costs by 53%
Lyka: From Reactive to Proactive in a High-Growth F&B Operation
Company: Lyka, an Australian scale-up producing gently cooked dog food. Targeting 5x expansion in three years.
The challenge: Maintenance workflows were reactive and inconsistent. Information was buried in binders or spread across spreadsheets and whiteboards. Finding the right document, let alone identifying a problem before it escalated, could take hours. At the scale they were growing, scattered processes and over-reliance on tribal knowledge were not sustainable.
The approach: Tractian CMMS became the single source of truth for maintenance operations, centralizing equipment manuals, SOPs, drawings, and PM checklists. Integration with Oracle NetSuite synced asset and maintenance data with financials. Then Lyka expanded into condition monitoring sensors, deployed by Tractian's customer success team on site. The impact was immediate: tracking down a part in the warehouse dropped from 22 minutes to 22 seconds.
The result: Critical equipment failures detected within days of deploying Tractian vibration sensors. Maintenance moved from reactive and inconsistent to structured and proactive. Operations now scale predictably across production sites without dependence on any single technician's knowledge.
Read the full case study: From CMMS to Condition Monitoring: How Lyka Built a Proactive Operation
What Plant Managers in F&B Say After 12 Months
Three patterns repeat across every one of these implementations:
The first prevented failure changes the internal conversation. When the team can point to a specific alert, a specific asset, and a specific cost that was avoided, the business case stops being theoretical. At Ingredion, it was a DSM pump with a known three-day outage history. At Kraft Heinz, it was a 150 HP motor that a technician caught on a weekend. Each of those moments built team confidence that no amount of management messaging could create.
The mindset shift is as valuable as the cost savings. Cintia P. at Kraft Heinz put it directly: the team now sees technology as a partner in decision-making. That cultural shift, from reactive response to proactive monitoring, has compounding value that does not show up fully in a year-one ROI calculation.
Starting small and proving the model is the right sequence. None of these plants deployed sensors across their entire facility on day one. They started with their highest-criticality assets, built confidence in the data, and expanded from there. That is the pattern. At Ingredion, the DSM pump was the first standout result. At Kraft Heinz, it was the 150 HP tomato concentration motor. Each plant had a specific asset with a specific known risk. Starting there, rather than deploying broadly with diluted attention, is what produced a result sharp enough to justify expansion in year one.
How Tractian Supports Food and Beverage Plant Managers
F&B plants present specific deployment challenges: washdown environments, HACCP compliance, high-humidity processing areas, and assets that cannot be taken offline for extended installation windows. Tractian sensors are designed to handle those conditions: rated for harsh industrial environments, wireless, and installable during routine sanitation or scheduled downtime windows without IT involvement.
The platform surfaces failure modes relevant to F&B processing equipment: centrifugal pump bearing wear, compressor valve degradation, conveyor drive motor vibration, and freezer unit motor health. Each alert includes the asset, the failure mode, and the recommended action, not raw data for analysts to interpret.
For plant managers who need to document program value, every prevented failure is recorded automatically: asset, alert date, fault type, corrective action, and estimated cost avoided. That record becomes the financial narrative for program expansion, budget justification, and the business case conversations that move reliability investment forward.
Ingredion, Kraft Heinz, and Lyka each followed that path: a focused deployment on critical assets, a documented first result, and expansion from there. The outcomes are in the case studies above.
See Tractian F&B Customer Results
Tractian continuously monitors equipment health in real time, detecting faults early and preventing unplanned downtime.
Explore the PlatformWhat results have food and beverage plants achieved with Tractian condition monitoring?
Documented results include: $1 million in production savings and $223,000 in maintenance savings at Ingredion's North Kansas City plant; a 53% reduction in corrective motor repair costs and over 1,000 hours of downtime avoided at Kraft Heinz; and critical equipment failures detected within days of deployment at Lyka. All case studies are available at tractian.com/en/case-studies.
How did these F&B plant managers overcome resistance to condition monitoring adoption?
At Kraft Heinz, a single weekend alert that prevented a 150 HP motor failure converted the maintenance team from skeptical to engaged. At Ingredion, catching a lubrication issue on the platform and seeing the fix confirmed in real time built immediate credibility. Early, documented wins are the most effective change management tool available.
What should a plant manager track to measure the success of a condition monitoring program?
Four metrics are sufficient: unplanned downtime hours on monitored assets before and after deployment, planned versus unplanned maintenance ratio, number of failures detected and repaired in advance, and total cost avoidance. The Ingredion and Kraft Heinz results above show what that measurement looks like in practice.
Where can I read the full F&B case studies?
All case studies are available at tractian.com/en/case-studies. The Ingredion, Kraft Heinz, and Lyka stories referenced above are linked directly in each section.