Calculating Overall Equipment Effectiveness (OEE) is crucial for food and beverage manufacturers aiming to optimize their production processes. In the food and beverage industry, understanding OEE helps identify inefficiencies, improve product quality, and reduce operational costs.

Read on to learn how to accurately measure OEE and enhance your manufacturing performance.

The Importance of OEE in the Food and Beverage Industry

Overall Equipment Effectiveness is a critical metric that has become particularly valuable in the food and beverage manufacturing industry. This sector relies heavily on OEE measurement to monitor and enhance manufacturing efficiency and product yield due to its notoriously thin profit margins. By calculating OEE and measuring manufacturing productivity, food and beverage manufacturers can gain insightful data to improve their production processes, ensuring that they operate at peak efficiency.

Given the dual focus of OEE on efficiency and performance, it serves as an essential tool for manufacturers aiming to maintain the health and productivity of their operations. Therefore, regularly assessing OEE should be a standard practice for any food and beverage manufacturing business looking to stay competitive.

Calculating OEE in the Manufacturing Industry

Simple OEE Calculation

Overall Equipment Effectiveness can be determined by comparing the Fully Productive Duration to the Planned Production Duration. OEE takes into account all losses, resulting in a measure of truly productive manufacturing time. Essentially, this means manufacturing only good parts at the best possible speed (ideal cycle time) without any interruptions. The basic formula for calculating OEE is:

OEE = (Good Count × Ideal Cycle Time) / Planned Production Time

While this basic calculation provides a snapshot of productivity, it doesn’t account for key loss factors such as availability, production performance, and quality. A more comprehensive approach is often preferred. Dedicated OEE software, or a combination of a data historian and data visualization tools can be used to track and analyze production losses and calculate OEE.

Calculating Performance Score

To get a clearer picture of performance, it’s important to consider two types of losses: small stops and slow cycles. These factors can significantly impact the performance score, but they need to be clearly defined to avoid confusion.

Small Stops: These are brief interruptions such as clogged materials, quick adjustments, or blocked sensors. It’s crucial to distinguish small stops from planned or unplanned longer stops. For example, a company might decide that any stop under 5 minutes is a small stop, while anything over 5 minutes is categorized as a planned or unplanned stop.

Slow Cycles: This refers to periods when equipment operates slower than the optimal cycle due to planned production time. The ideal cycle time is theoretically the fastest time to produce one unit, and any deviation from this can indicate inefficiencies.

Performance is calculated as the ratio of Net Run Time to Run Time. In practice, it is calculated as:

Performance = (Ideal Cycle Time × Total Count) / Run Time

By accounting for these factors, manufacturers can gain more granular insights into their operations, allowing them to identify and address specific issues that impact overall efficiency. This comprehensive understanding of OEE not only helps in maximizing productivity but also in maintaining consistent product quality, ultimately leading to better operational performance and profitability for discrete manufacturers.

Calculating Availability Score

The availability of equipment impacts two types of losses: planned and unplanned stops. Planned stops include scheduled maintenance tasks or changeovers, whereas unplanned stops occur due to unexpected breakdowns, material shortages, or equipment failures. Understanding these distinctions is crucial for accurate measurement.

Availability is calculated using the following formula:

Availability = Run Time / Planned Production Time

By focusing on minimizing unplanned stops and efficiently managing planned stops, manufacturers can improve their Availability Scores, leading to better overall equipment effectiveness.

Common Issues in OEE Calculation

When calculating Overall Equipment Effectiveness, several common issues can arise that may affect the accuracy and reliability of the results. Understanding and addressing these underlying issues is crucial for obtaining meaningful insights into your manufacturing process.

1. Inconsistent Data Collection: Inaccurate or inconsistent data collection practices can lead to flawed OEE calculations. Standardizing data collection methods across all equipment and shifts is essential to ensure reliability.
2. Misclassification of Stops: Differentiating between small stops, planned stops, and unplanned stops can be challenging. Clear definitions and guidelines should be established to avoid misclassification, which can distort the availability and performance scores.
3. Ignoring Minor Stoppages: Small stoppages, such as brief pauses or minor adjustments, often go unrecorded but can cumulatively have a significant impact on OEE. All stoppages, regardless of duration, should be documented to provide a complete picture.
4. Overlooking Quality Losses: Focusing solely on availability and performance while neglecting quality losses can give an incomplete view of OEE. Including data on defects, rework, and scrap is necessary for a comprehensive assessment.
5. Incorrect Calculation Methods: Using simplified or incorrect formulas for OEE components can lead to inaccurate results. It’s important to use standardized and validated calculation methods for availability, performance, and quality.
6. Lack of Real-Time Monitoring: Without real-time monitoring systems in place, identifying and addressing issues promptly becomes difficult. Implementing real-time data tracking can enhance the accuracy and timeliness of OEE calculations.
7. Failure to Consider External Factors: External factors such as supply chain disruptions, operator skill levels, and environmental conditions can affect OEE. These factors should be taken into account to understand their impact on equipment effectiveness.

Factors that Affect OEE in the Food and Beverage Industry

Food ingredients can vary greatly in their physical attributes depending on the source of the raw materials. Factors such as weight, shape, density, moisture content, stickiness, and viscosity can differ significantly from one batch to another. This variability can cause machinery and processes, which are designed for specific physical properties, to struggle with efficiency and quality when faced with unexpected changes.

In the food and beverage industry, downtime not only means lost production but also potential quality loss and product waste, as food is perishable. Exposure to incorrect temperatures, high humidity, or other adverse environmental conditions can quickly degrade product quality, leading to increased waste and costs.

Food processing machinery, including baggers, filling machines, and labelers, is particularly prone to issues caused by processing variations. These machines often require constant monitoring and frequent adjustments to clear jams and restart operations. This susceptibility to variations highlights the need for continuous improvement of robust and adaptable equipment in the industry.

How Manufacturers can Maximize their Value in the Food and Beverage Industry with OEE

Optimizing Availability

One of the key components of Overall Equipment Effectiveness is availability, which is heavily influenced by downtime in production lines, equipment, and manufacturing plants. Downtime can stem from various sources, including equipment and process failures and operational inefficiencies. Reducing downtime is crucial as it directly impacts availability and profitability. Even if a facility doesn’t formally calculate its OEE, it’s widely understood that minimizing downtime can significantly enhance productivity. However, accurately calculating machine downtime can be challenging and requires meticulous tracking and analysis.

Optimizing Quality

Food manufacturers place a strong emphasis on quality when calculating OEE. The complexity of the food manufacturing and production process often arises from the high variability of products. This challenge is intensified by the industry’s shift towards smaller lot sizes and more customized products to cater to evolving consumer demands. Today’s consumers expect a wide range of products, from diet-specific items to various packaged foods. Maintaining high quality across such a diverse product lineup requires rigorous attention to detail and robust quality control measures. By focusing on optimizing quality, manufacturers can ensure consistent product standards, reduce waste, and meet consumer expectations, thereby maximizing their value in the market.

Why Monitoring OEE is Crucial for Improving Productivity

Monitoring Overall Equipment Effectiveness is crucial for improving manufacturing productivity because it provides real-time insights into how well your production processes are performing. By continuously tracking OEE, you can:

• Identify Bottlenecks: Quickly pinpoint areas where production is slowing down, allowing you to address issues before they escalate.
• Reduce Downtime: Detect and respond to equipment failures or maintenance needs promptly, minimizing unplanned downtime.
• Enhance Quality: Monitor quality metrics in real time to ensure products meet standards and reduce waste.
• Optimize Performance: Analyze performance trends to find opportunities for process improvements and efficiency gains.
• Make Data-Driven Decisions: Use accurate, up-to-date data to drive informed decisions that enhance overall operational effectiveness.

In short, regular OEE monitoring helps you maintain a smooth, efficient production line, ultimately boosting your productivity and profitability.

Common Challenges of Measuring OEE in the Food and Beverage Industry

Measuring OEE in the food and beverage industry comes with unique challenges due to the nature of production processes and product variability. Here are some common challenges:

• Product Variability: The inherent variability in food ingredients can affect equipment performance and quality metrics, making it difficult to maintain consistent OEE measurements.
• Short Production Runs: The trend towards smaller, customized batches to meet diverse consumer demands means frequent changeovers and increased downtime, complicating the measurement of OEE.
• Perishability: The perishable nature of food products amplifies the impact of downtime and quality issues, as any delays or defects can result in significant waste.
• Stringent Quality Standards: Maintaining high standards in a highly regulated industry adds complexity to measuring quality, one of the key components of OEE.
• Complex Supply Chains: The complexity of supply chains in the food and beverage industry can lead to disruptions that affect production schedules and equipment availability.
• Manual Processes: Many food and beverage plants still rely on manual processes and record-keeping, which can lead to inaccuracies and inefficiencies in OEE tracking.
• Seasonal Variations: Seasonal changes and demand fluctuations can impact production efficiency, further complicating the measurement of OEE.

Addressing these challenges requires robust data collection systems, real-time monitoring, and a proactive approach to managing production processes. By doing so, food and beverage manufacturers can achieve more accurate OEE measurements and drive improvements in productivity and efficiency.

What You Should Do Next

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Now that you know more on how to calculate OEE in the food and beverage industry, why not check out our other blog posts? It’s full of useful articles, professional advice, and updates on the latest trends that can help keep your operations up-to-date. Take a look and find out more about what’s happening in your industry. Read More

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OEE Food FAQs

What is a Good OEE Score?

A perfect OEE score is 100%. Most businesses can easily achieve the highest score of 100% in production processes. What is the best method of measuring business performance? A score of 85% is commonly thought to be considered world class- by many discrete companies. It’s important to consider these results as long-term goals for manufacturing processes. In general, OEE scores below 65 are unacceptable in manufacturing. A score below 70% of all the manufacturing operations can be considered normal.

What is the OEE Formula?

The OEE (Overall Equipment Effectiveness) formula is calculated by multiplying three factors – Availability, Performance, and Quality. The formula is:

OEE = Availability x Performance x Quality

Where:

Availability = Operating Time / Planned Production Time

Performance = (Ideal Cycle Time x Total Count) / Operating Time

Quality = Good Count / Total Count

This formula measures how effectively a manufacturing operation is utilized compared to its full potential, taking into account losses from unplanned downtime (Availability), slow cycles (Performance), and quality defects (Quality).

How to Calculate OEE in Excel?

To calculate OEE in Excel, you need to follow these steps:

Calculating OEE in Excel involves setting up a spreadsheet to compute Availability, Performance, and Quality, and then multiplying these factors to get the OEE percentage. Here’s a step-by-step guide:

Set Up your Spreadsheet:

In one row, label the columns: Scheduled Production Time, Operating Time, Total Count, Good Count, Ideal Cycle Time.

Input Data:

Enter your actual data under each corresponding column.

Calculate Availability:

In a new column labeled Availability, enter the formula:

[ = \text{Operating Time} / \text{Scheduled Production Time} ]

Calculate Performance:

In a new column labeled Performance, enter the formula:

[ = (\text{Ideal Cycle Time} * \text{Total Count}) / \text{Operating Time} ]

Calculate Quality:

In a new column labeled Quality, enter the formula:

[ = \text{Good Count} / \text{Total Count} ]

Calculate OEE:

In a final column labeled OEE, multiply the total units by three factors:

[ = \text{Availability} \text{Performance} \text{Quality} ]

Here’s an example layout for the formulas in cell references:

By following these steps, you can easily calculate OEE in Excel and monitor the efficiency and productivity of your manufacturing processes.