The food manufacturing industry is often slow to adopt new technologies because of health and hygiene regulations, but the advantages of Industry 4.0 are proving to be too significant to be ignored.

Drops in the cost of hardware (sensors, gateway devices, connectivity solutions, and cloud computing) along with improved software tools, have created a compelling case for implementing Industrial IoT (IIoT). And with proven business benefits of smart factory technology already delivered in the food and beverage industry – through Condition Monitoring and Digital Twinning – there is mounting pressure on food manufacturers to keep up with the competition.  


The Unique Challenges of Food Processing

Since the end-product is always intended for human consumption, food manufacturers face numerous unavoidable and significant costs including pest control, microbial testing, hygiene consultation and other services.

Ongoing compliance with food and beverage safety regulations demands that sanitation equipment be constantly modified. The importance of cleanliness results in production zones becoming wet environments with moisture levels high enough to damage equipment.

Food manufacturing processes are extremely elaborate and incorporate numerous stages from mincing, liquefaction and emulsification to cooking, pasteurization, and packaging. These processes demand machinery that is highly complex, making efficient maintenance a real challenge.

Condition Based Monitoring Dashboards - Food Processing Industry

Condition-Based Maintenance in Food Processing

To combat the complexity and cost of asset maintenance in food production, Condition Monitoring is used to regularly deliver a large part of the necessary data to perform Condition-Based Maintenance.

The data is captured by sensors placed on machinery that constantly capture a variety of data sets that can be used to monitor the health of an asset.

Common Condition Monitoring techniques in the food industry include vibration analysis, oil analysis, and thermal imaging.   


Predictive Maintenance in the Food Production Industry

The data collected through Condition Monitoring, combined with historic and ERP data about the various machines, can be aggregated, forming the basis for Predictive Maintenance.

Detecting deviations and performing analysis on the data using Machine Learning results in the ability to formulate predictions regarding equipment failure. In this way, preventive maintenance schedules become redundant since maintenance is only carried out when necessary, cutting significant costs in labor and minimizing unplanned downtime.


5 Major Benefits of Industrial IoT in Food Production

Food Safety

One of the most important parameters to monitor in food safety is temperature, but that’s not always a simple task considering the variety of processes and environments food is exposed to before it reaches its final point-of-sale.

The latest sensors designed for IIoT use are accurate, reliable and inexpensive, making temperature tracking extremely simple, regardless of which step of the process the product is in.

Track & Trace

IIoT enables real-time inventory tracking and detailed monitoring of the arrival and processing of raw materials, transport activities within the plant, and product distribution.

Plant conditions can be continually monitored to ensure employee safety and that of prepared food items and raw materials.

Remote Monitoring

A smart factory can be monitored remotely and grants management the ability to view an operation from a micro-to-macro viewpoint.

Beyond the evaluation of a single machine, process or facility, Remote Monitoring offers the ability to log, track and compare various processes across various facilities, and can provide valuable insights on how to optimize these processes.

Access to Data Insights

The wealth of data collected from Condition-Based Monitoring is useful because of how it can be leveraged to cut maintenance costs, but another significant advantage is that the information can be accessed by authorized personnel in a range of professions.

This makes transferring tasks much more efficient since the data on any asset is available anytime, anywhere. Also, because this detailed information is shared with employees with a variety of skill sets, it can be leveraged across the company to make changes that will directly impact the bottom line from different angles.


Performing maintenance using a data-driven approach offers a host of advantages for the food processing industry. Machinery can be closely tracked for Overall Equipment Efficiency (OEE) preventing wastage and food safety issues while unplanned downtime is dramatically reduced since maintenance tasks are only performed when necessary.


Taking Food Processing to the Next Level with IIoT

Industrial IoT is already having a significant impact on the food processing industry, with a growing number of companies implementing the solutions mentioned above.

And the future is bright – there’s still a lot more unchartered territory with regards to how this technology can be used in the food processing sector to further reduce downtime, increase throughput, and improve product quality.

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