In the food processing industry, using assets effectively and efficiently is an essential prerequisite for food manufacturers to stay competitive. Optimizing asset use in the food processing industry leads to increased productivity, reduced costs and waste (which also diminishes environmental impact), and an overall boost in business performance. Listed below are six steps to improve asset usage in the food processing.

1) Conduct an Asset Inventory

The first step in improving asset utilization is a comprehensive inventory of all assets. An asset inventory can be used to collect data on the age, usage, maintenance history, location, spare parts, and other relevant asset and equipment information. Some of this information can help manufacturers estimate the mean time between failure (MTBF), a metric that measures the reliability of machines and components and helps plan maintenance accordingly. Food manufacturers can also use asset inventories to:

  • Plan different production strategies based on their resources.
  • Identify underutilized or unnecessary assets that can be either disposed of or used more effectively.
  • Determine asset criticality. This refers to the degree to which an asset or piece of equipment is important for the production process. It is measured by taking into account the consequences of a failure or loss of the asset, including safety risks, production downtime, financial losses, and impact on product quality. 

2) Measure Asset Utilization

Asset utilization is another important metric. It measures the effectiveness of assets in generating revenue and is calculated by dividing the actual production output of an asset by its maximum potential output. This metric allows food plant managers to identify areas for improving asset performance and optimizing food processing.

Some other metrics for measuring asset utilization include: 

  • Overall equipment effectiveness (OEE):  It measures how effectively an asset is being used during a scheduled time by multiplying three factors: availability, performance, and quality.
  • Production yield: The percentage of products that are produced correctly and meet quality standards. It is a measure of how effectively a food manufacturing process is producing salable food products. This metric helps identify equipment malfunctions, quality control problems, and other issues that impact food processing.
  • Asset uptime: The percentage of time an asset is available for production. If an asset is not available due to maintenance, breakdowns, or other reasons, this can affect asset utilization negatively. 
  • Unplanned downtime: Instances where an asset is scheduled for production but is not operating due to unexpected events. Unplanned downtime can have a negative impact on asset utilization because it reduces the amount of time an asset is available for production, resulting in lower production output and revenue loss. By tracking unplanned downtime as part of their asset utilization metrics, food plant owners can identify its causes and take corrective actions for prevention or reduction.

3) Monitor Equipment Performance

Food manufacturers can use IoT sensors to collect real-time data, such as pressure, temperature, electrical currents and vibrations, on the performance of food processing equipment. By analyzing this data, food plant managers can remotely monitor their assets and identify potential issues before they cause downtime or equipment failure. They can also receive an alert if a failure occurs. IoT sensors provide sufficient data to let food processing workers make quick and informed decisions that prevent or minimize downtime. 

Additionally, IoT sensors are compatible with enterprise asset management (EAM) software, which provides visibility into asset performance analytics by collecting and analyzing data from multiple sources. EAM software allows food manufacturers to track key performance indicators (KPIs), such as asset uptime, maintenance costs and production yield. This way, they can identify trends and make data-driven decisions to optimize their asset utilization.

4) Implement Asset Tracking Software

Asset tracking can help food manufacturers track asset location and condition. If the assets are equipped with a GPS tracking system, a barcode scanner or a radio-frequency identification (RFID), manufacturers can add asset tracking software to the equation and gain visibility into their assets.

Asset tracking software enables food manufacturers to:

  • Keep track of the quantity, value, location and status of assets—all in one place.
  • Track which assets are being used, by whom and for how long.
  • Record their assets’ movement and receive an alert if unexpected movement is detected.
  • Schedule and track asset maintenance activities.
  • Get insights into asset usage and performance, which helps them make data-driven decisions and optimize assets and asset utilization.

Asset tracking software systems can be installed locally on the food plant’s computers and servers, or they can be cloud-based. Most modern asset tracking software systems are cloud-based. The cloud provides food manufacturers with a centralized location to store and access asset data from any device with an internet connection. This allows them to monitor the location and status of their assets in real time, even if they’re not physically in the food plant. 

5) Develop a Maintenance Plan

Proper maintenance is essential to ensure that assets are operating at peak efficiency. Maintenance also helps extend equipment lifecycles, avoid unplanned downtime, and preserve food safety and regulatory compliance.

Apart from regular upkeep, food manufacturers can resort to predictive maintenance. This is an advanced approach to maintenance that uses technology to identify potential equipment failures before they occur. Manufacturers around the world are taking advantage of it. In fact, the predictive maintenance market is expected to be worth about $15.9 billion by 2026.

Predictive maintenance help manufacturers prevent downtime, reduce maintenance costs, and optimize asset utilization and performance via several technology solutions:

  • IoT sensors and Artificial Intelligence (AI): IoT sensors monitor equipment performance and collect data. Then, AI in the form of machine learning algorithms can detect patterns in the data and predict when a failure is likely to occur. This way, IoT sensors and AI/ML enable maintenance teams to take corrective action before the equipment fails.
  • Computerized maintenance management system (CMMS) software: CMMS software allows manufacturers to manage and streamline maintenance operations through a centralized database. CMMS software can track asset performance and maintenance history, enabling maintenance teams to identify trends and patterns and proactively schedule maintenance tasks before a failure occurs.
    When integrated with sensors, CMMS software can monitor equipment condition and help maintenance teams identify changes in performance that suggest potential issues. When combined with predictive algorithms, CMMS software can also forecast future equipment failures based on historical data, trends and patterns. This information can be used to prioritize maintenance tasks, schedule downtime and find replacement parts in advance.
  • EAM software: EAM software monitors asset performance and records the maintenance history of each piece of equipment. It can then use predictive analytics to anticipate failures. Additionally, it allows food manufacturers to plan maintenance operations, assign resources and track progress.
  • Connected worker technology: Connected worker platforms use smart devices to provide and share real-time data on asset performance, streamlining communication between workers and maintenance teams and enabling faster response times to potential issues.

6) Optimize Workflow

Workflow optimization involves analyzing and streamlining processes to improve efficiency and reduce costs. One way to achieve this is automating processes to reduce manual labor and improve asset utilization—e.g.,using robotics.

In the food processing industry, robots can take over repetitive tasks that humans can’t always do with the same level of accuracy and efficiency, such as cutting, sorting, and packing. They can reduce the risk of errors and waste and improve product quality without the need for rework. And since they don’t need to rest, they improve asset utilization by simply utilizing assets for longer periods of time. Additionally, robots can be equipped with sensors that collect asset performance data and take part in predictive maintenance, increasing uptime even more.

Data analytics and digital technologies can provide valuable insights into asset performance and help identify areas for improvement, enabling food manufacturers to plan the best asset utilization. With these steps and strategies, food manufacturers can optimize their production processes and reduce costs while increasing productivity and competitiveness.