How Manufacturing Engineers in Food and Beverage Should Evaluate Condition Monitoring Solutions

Selecting a condition monitoring solution for a food and beverage processing plant is not the same as selecting one for a general industrial facility. The operating environment has specific hardware requirements that disqualify a significant portion of the general industrial monitoring market. The data requirements for failure mode identification are more specific than simple threshold alarming. And the regulatory environment means that how monitoring data is managed has implications beyond the reliability program.

A manufacturing engineer evaluating monitoring solutions for an F&B application needs a structured technical framework that evaluates hardware, data capability, and regulatory integration together, not in isolation. This guide provides that framework.

Hardware Evaluation: F&B-Specific Requirements

Ingress protection

The standard for food and beverage washdown environments is IP69K. This test standard specifies resistance to high-pressure, high-temperature steam cleaning: water jet pressure of 80 bar at a temperature of 80 degrees Celsius, applied from multiple directions at close range (typically 100 to 150 mm).

IP67 is not an equivalent substitute. IP67 specifies resistance to temporary immersion at 1 meter for 30 minutes. The physical mechanism of high-pressure spray is fundamentally different from slow hydrostatic pressure at depth. Seals and cable entry points that resist immersion may not resist repeated high-pressure spray impact.

Practical requirement: Specify IP69K for any sensor installed in a direct washdown zone. For sensors installed in areas with indirect washdown exposure (overhead mounting above equipment, for example), IP67 may be acceptable with a facility-specific assessment. Document the assessment basis in the specification FMEA.

Verify IP69K rating against the test report documentation, not a product family marketing claim. Some vendors list IP69K in product family literature when only specific models within the family have been tested to that standard.

Temperature range

F&B facilities expose monitoring equipment to temperatures across a wider range than most industrial environments:

CIP temperature. Hot water and alkaline cleaning solutions in dairy and ready-to-eat facilities typically run at 75 to 85 degrees Celsius. Sensors permanently installed on equipment that undergoes daily CIP will be exposed to these temperatures through heat conduction from the equipment surface, even if not directly sprayed with hot cleaning solution. The sensor must be rated for continuous operation at the maximum CIP temperature the installation location will experience.

Low-temperature environments. Cold storage and refrigeration system monitoring involves temperatures from 2 to -30 degrees Celsius depending on the storage type. Sensor adhesives, cable jackets, and electronics all require appropriate cold-temperature ratings.

Operating range specification: For most F&B monitoring applications, a rated operating range of -30 to +85 degrees Celsius covers both cold storage and CIP exposure requirements. Verify that the rated range applies to continuous operation, not just brief excursions.

Enclosure material for food contact proximity

Equipment in direct contact with food or in the immediate proximity of food contact surfaces must comply with the facility's sanitary design standards. For most F&B operations, this means:

• Stainless steel 316L for wet-zone installations
• EHEDG or 3-A hygienic design compliance for any element in the food splash zone
• No external fasteners, pockets, or crevices that cannot be cleaned to food contact standards
• Cable and conduit routing that does not create harborage points

Standard industrial sensor housings in painted steel or standard aluminum alloy are not appropriate for food contact zone installations. Verify the specific enclosure specification against the facility's sanitary design standard, not just a general food and beverage industry approval claim.

Sensor attachment method

The method used to attach a sensor to food contact equipment must be evaluated for sanitary design compliance:

Drilled-and-tapped studs on flat bearing housing surfaces are the standard industrial installation method. On food contact equipment, the stud must be hygienic design compliant (316L stainless, no threads exposed in food splash zone), and the area around the stud must be cleanable to sanitary standards.

Adhesive mounting on non-flat surfaces eliminates the need for drilling into the equipment but may create a bond that degrades in CIP environments. High-temperature epoxy adhesives are typically adequate for CIP exposure, but the adhesive bond must be tested for the specific temperature, chemical, and mechanical exposure of the installation location before deployment.

Magnetic mounting is appropriate for non-food-contact steel surfaces but should not be used on stainless steel food contact surfaces where magnetic attachment may not be reliable and where the magnetic base creates a potential harborage point.

Data Evaluation: What You Need for Failure Mode Identification

Vibration spectrum versus RMS threshold

RMS overall vibration level is a single aggregate number. When it exceeds a threshold, something is wrong. When it does not, nothing is flagged. There is no failure mode information in a single RMS number.

Vibration spectrum analysis decomposes the vibration signal into its frequency components. For rotating equipment, the critical frequencies are:

Bearing defect frequencies are calculated from bearing geometry: ball pass frequency outer race (BPFO), ball pass frequency inner race (BPFI), ball spin frequency (BSF), and fundamental train frequency (FTF). These frequencies are known from the bearing manufacturer's data. Early-stage bearing defects appear as energy peaks at these specific frequencies, at levels that do not significantly affect overall RMS. A monitoring platform that resolves the full frequency spectrum with sufficient resolution to detect these early-stage peaks gives Stage 1 and Stage 2 detection. RMS threshold monitoring gives Stage 3 or Stage 4 detection.

Gear mesh frequencies appear at the product of shaft rotation speed and number of gear teeth, with harmonics. Gear mesh wear or damage produces energy increases at these frequencies and at sidebands. Distinguishing gear mesh wear from bearing wear requires frequency spectrum resolution.

Cavitation signatures appear as broadband high-frequency energy increases, typically above 5 kHz. This spectral region is different from the bearing defect frequency region for most process pump bearings, so the two failure modes are distinguishable from the spectrum.

Minimum specification: The monitoring platform must collect full frequency spectra (not just RMS or ISO band values) and must apply failure mode identification that maps spectral peaks to specific failure mechanisms. The manufacturing engineer needs the failure mode identification output for RCA, not just an alert that overall vibration has increased.

Continuous versus periodic collection

Periodic condition monitoring (manual routes or periodic automated sampling) collects a snapshot at the scheduled time. Continuous monitoring collects trend data throughout the operating period.

In F&B, the specific advantage of continuous over periodic collection is transient event capture. F&B processing equipment experiences transient operating conditions that produce temporary degradation signals not visible in scheduled periodic measurements:

• A centrifugal pump that experiences cavitation during a brief production rate spike will show the cavitation signature for minutes or hours, then return to normal. A monthly manual route will not capture this event.
• A filling line drive that experiences a momentary mechanical overload during a product changeover may show a brief vibration spike associated with torque overload. Continuous monitoring captures this as an event with timestamp. Periodic monitoring misses it entirely.
• A refrigeration compressor that shows temperature increases during peak ambient conditions (summer) may trend toward a threshold only during the warmest parts of the day. Continuous monitoring captures the diurnal pattern. Periodic monitoring may be taken at a time of day when the pattern is not active.

Specification: For Tier 1 critical assets (those whose failure stops the line or triggers a food safety response), specify continuous trend data collection with sufficient sample rate to capture transient events. For Tier 2 assets (important but with some redundancy or shorter restart time), periodic automated collection at appropriate intervals may be acceptable.

Data export capability

The monitoring platform must make raw data accessible for RCA and FMEA workflows:

Waveform or spectrum export: For any alert event, the manufacturing engineer must be able to retrieve the full frequency spectrum or raw vibration waveform at the time of the alert and for the period preceding it. This is the data that enables failure mode identification and RCA timeline reconstruction.

Trend data export: Time-series trend data (RMS, frequency band values, temperature) must be exportable in a standard format (CSV, JSON, or API) for integration with the manufacturing engineer's existing analysis tools.

Event record export: Alert events, acknowledgments, and corrective actions must be exportable with timestamps for HACCP documentation and audit records.

Regulatory Considerations: HACCP Documentation and Monitoring

Does condition monitoring create HACCP documentation requirements?

Condition monitoring data does not inherently create new HACCP documentation requirements. The HACCP plan defines what monitoring activities are required at each critical control point and critical limit, with defined monitoring frequency and corrective action procedures.

If the monitoring platform is cited as a detection control or monitoring method in the HACCP plan for a CCP, then the monitoring records for that CCP-related asset become part of the HACCP evidence base and must be retained according to the facility's record retention policy.

Practical guidance for manufacturing engineers:

If you are adding condition monitoring to an asset at or supporting a HACCP CCP, evaluate whether the monitoring data will be cited in the HACCP plan as a detection control. If yes, establish the record retention and alert response procedure before deployment. If the monitoring data is supplementary (used for RCA and maintenance planning but not cited in the HACCP plan as a CCP monitoring method), standard record retention practices apply.

FMEA documentation of monitoring as a detection control

When condition monitoring is used as the detection control for a high-severity failure mode in the equipment FMEA, the monitoring specification must be documented in the FMEA:

• Sensor type and location
• Collection method (continuous or periodic) and sample rate
• Alert threshold and failure mode identification method
• Alert response procedure and timing

This documentation is what makes the detection rating in the FMEA defensible. A detection rating of 2 or 3 (very likely to detect before consequence occurs) requires documentation of how the detection will occur, not just a claim that monitoring is in place.

Deployment Evaluation: F&B Installation Constraints

Existing equipment installation

Most F&B monitoring deployments are installed on existing equipment, not new equipment. This creates installation constraints that must be assessed before committing to a monitoring solution:

Bearing housing accessibility: Accelerometers must be installed at or near the bearing housing for effective bearing fault detection. In food-contact equipment designed for cleanability, the bearing housing may be enclosed in a sanitary design cover that limits access. Assess sensor mounting feasibility on each specific asset before specifying the monitoring solution.

Cable routing: Signal cables and power cables must be routed away from food contact zones and secured in a manner that does not create harborage points. In facilities with extensive CIP coverage, cable routing may require conduit installation or wireless sensors. Wireless sensors have their own power and data transmission constraints that must be evaluated.

Downtime for installation: Installing a monitoring sensor on a food contact pump typically requires a planned downtime window for sanitary design compliance inspection after installation. Factor this into the deployment timeline and coordinate with the maintenance and food safety teams.

New equipment specification

For new equipment, the installation constraints above can be designed out if monitoring-readiness is in the specification. The bearing housing access point, the cable routing path, and the sensor mounting location can all be specified in the equipment order when the manufacturing engineer identifies them as requirements during the specification FMEA.

Integration Evaluation: RCA and FMEA Workflow

A monitoring platform that generates alerts but cannot integrate its data into the manufacturing engineer's existing RCA and FMEA processes adds limited value beyond alerting. The integration requirements:

RCA integration: When an availability event occurs on a monitored asset, the manufacturing engineer must be able to retrieve the complete failure mode timeline from the monitoring platform: when the first degradation signal appeared, how it progressed, and what the operating conditions were at each stage. This data becomes the primary evidence in the RCA and is exported to the RCA format the facility uses.

FMEA integration: The monitoring platform's failure mode identification library must map to the failure mode nomenclature used in the facility's FMEA process. If the FMEA categorizes pump failures as "bearing wear," "seal failure," and "hydraulic failure," the monitoring platform's alert categories must be translatable to these FMEA failure modes. This mapping should be established during deployment configuration, not left to post-alert interpretation.

Work order integration: Alert-to-work-order workflow should be as direct as possible. An alert from the monitoring platform should be convertible to a work order in the CMMS with the failure mode, recommended corrective action, and urgency classification populated from the monitoring data. Manual transcription between systems creates documentation errors and delays the corrective action.

Evaluation Scorecard for F&B Condition Monitoring

OEE visibility and micro-stop detection in F&B operations: Evaluate whether the platform surfaces production data at cycle-time or fill-rate resolution, not just major downtime events, but brief stoppages, speed losses, and conveyor hesitations that operators clear without logging. In F&B continuous and semi-continuous processing, these micro-losses represent hidden OEE availability losses that are invisible without machine-level sensor data. Tractian's OEE solution provides automatic production tracking without relying on operator manual input, giving the Manufacturing Engineer the objective production record needed for CI projects.

Machine health to product quality and food safety correlation: Evaluate whether the platform allows correlation of machine health signals, vibration, temperature, power draw, with process quality data. A centrifugal pump with bearing wear producing pressure variation before failure creates fill weight inconsistency. A conveyor with a degrading drive producing intermittent hesitation creates packaging integrity issues. These quality consequences appear in the machine health signal before they appear in the quality record. Product that must be scrapped or reworked because a processing machine was running degraded, and the quality record only caught it after the batch was complete, is the cost that machine-health-to-quality correlation prevents. The Manufacturing Engineer who can correlate a vibration trend increase with a process parameter deviation has the data for a root cause analysis that protects both product quality and food safety compliance.

Objective sensor data for maintenance-production RCA: Evaluate whether the platform produces timestamped, sensor-driven machine state records exportable for RCA. The maintenance-versus-production blame cycle in F&B manufacturing delays both the reliability fix and, when food safety is implicated, the regulatory investigation. Objective machine health data covering the period of a stoppage or quality event gives the Manufacturing Engineer the sensor-driven truth rather than two conflicting operator and maintenance accounts.