8 Key Performance Indicators for Improving Efficiency in the Food Manufacturing Industry

In today’s competitive food manufacturing industry, efficiency is no longer just an option – it’s a necessity. With tight margins, complex regulations, and consumer demand for high quality at low costs, food manufacturers need to constantly optimize their operations. An efficient production process translates directly into higher profitability and a competitive advantage.

One of the best ways to improve efficiency is by monitoring key performance indicators (KPIs). KPIs provide measurable values that allow you to gauge the effectiveness of your manufacturing operations. By tracking KPIs, you gain crucial insights that help you identify problems, reduce waste, and boost productivity.

In this blog post, we will examine the 8 most important KPIs for the food manufacturing industry. You will learn the definition and significance of each metric, how to accurately calculate it, and most importantly – how to leverage it to enhance efficiency in your production process. With the help of these KPIs, you can make data-driven decisions that lead to streamlined operations, lower costs, and maximum output.

1. Overall Equipment Effectiveness (OEE)

Overall Equipment Effectiveness (OEE) offers a comprehensive way to measure the performance of production equipment. It is one of the most important metrics for gauging efficiency in food manufacturing. OEE takes into account all factors that can undermine the productivity of equipment – breakdowns, changeovers, small stops, quality defects, and reduced speed.

The formula for calculating OEE is:

OEE = Availability x Performance x Quality

Where:

Availability = Uptime / (Uptime + Downtime)

Performance = Ideal Cycle Time / Actual Cycle Time

Quality = Good Units Produced / Total Units Produced

Targeting an OEE score of 85% is considered world-class for manufacturing. An OEE of 60% is fairly average, while 40% is inefficient. By splitting OEE into three components, you can identify the specific areas for improvement. For example, is equipment availability being affected by frequent breakdowns? Is performance impacted by long changeover times? Or is quality poor due to adjustments and defects?

The benefits of improving OEE in food manufacturing are:

• Increased capacity through higher machine utilization
• Reduced downtime from breakdowns and changeovers
• Faster production rates ensure on-time delivery
• Less scrap and rework resulting in material cost savings
• Improved quality through defect reduction

2. Yield

Yield is an important efficiency indicator that measures the ratio between the actual output of a production process compared to the theoretical maximum output. In food manufacturing, yield metrics provide insights into how well resources are being converted into sellable products.

The formula for calculating yield is:

Yield = (Actual Output / Theoretical Maximum Output) x 100

For example, if 800 kg of tomato paste is produced from 1,000 kg of tomatoes, the yield rate is:

(800 kg / 1,000 kg) x 100 = 80%

Some key benefits of improving yield are:

• Reduced raw material costs due to better utilization of ingredients
• Less waste generation, leading to environmental and disposal benefits
• Increased production capacity through higher yields from the same resources
• Ability to meet customer demand with lower resource requirements

By tracking yield over time, you can identify problems like machine wear and tear, measurement inaccuracies, variability in raw materials, inefficient process parameters, and inadequate quality control. Addressing these issues can help continuously improve the yield rate.

Setting yield improvement targets and comparing yields across different products, batches, and machines will provide insights into best practices that you can standardize across your production line.

3. Throughput

In manufacturing, throughput measures the rate of production as units produced per unit of time. Improving throughput is a key efficiency objective for food manufacturers.

The formula for throughput is:

Throughput = Total Units Produced / Total Time

For example, if a confectionery produced 300,000 chocolate bars in a month working 20 days x 8 hours per day = 160 hours, the throughput is:

300,000 bars / 160 hours = 1,875 bars per hour

Here are some benefits of improving throughput:

• Increased production capacity by producing more within the same timeframe
• Ability to meet higher demand without expanding operations
• Reduced idle time since higher output is achieved in less time
• Faster delivery times and better customer service due to faster production
• Lower costs through better asset utilization – producing more with existing equipment

To improve throughput, food manufacturers can:

• Optimize staffing to avoid bottlenecks
• Streamline changeover and cleaning procedures
• Invest in faster equipment and production lines
• Improve maintenance practices to reduce downtime
• Upgrade processes to add automation where possible

Comparing throughput over time and across product lines highlights areas for focus. This allows you to replicate positive practices that drive higher throughput.

4. First Pass Yield

First pass yield (FPY) measures the percentage of units produced correctly without requiring any rework or scrap. It is a metric of production quality and efficiency. Maximizing FPY has direct cost benefits for food manufacturers.

The formula for First Pass Yield is:

FPY = (Units Produced without Defects / Total Units Produced) x 100

For example, a bakery produces 800 pizzas in a shift. 10 pizzas are rejected for being the wrong size. The FPY is:

(800 – 10) / 800 x 100 = 98.75%

The advantages of improving FPY are:

• Reduced waste by minimizing scrap and rework
• Lower labor costs by avoiding unnecessary processing of defective units
• More efficient use of raw materials as less is discarded
• Reduced quality control expenses needed for reinspections
• Higher overall equipment effectiveness as quality rate improves

Food manufacturers can boost FPY by:

• Upgrading equipment to improve process capability
• Implementing statistical process control to identify issues
• Improving training to reduce human errors
• Standardizing production processes for consistency
• Inspecting and certifying raw materials from suppliers

By breaking down FPY performance by product type, production line, shift, and other variables, you can zero in on problem areas and replicate successes across the plant.

5. Scrap Rate

The scrap rate KPI measures the percentage of raw materials, ingredients, packaging materials, and finished goods that are discarded during production. High scrap rates directly reduce efficiency and increase costs.

The formula for scrap rate is:

Scrap Rate = (Quantity of Scrap / Total Production Quantity) x 100

For example, if a plant produced 10,000 kg of cookies last month, and 150 kg were discarded as scrap, the scrap rate is:

(150 kg / 10,000 kg) x 100 = 1.5%

Strategies to reduce the scrap rate include:

• Improving inventory management to minimize ingredients expiration
• Optimizing production processes to minimize giveaway and trim waste
• Investing in advanced equipment to improve precision and reduce defects
• Enhancing quality control and inspections to detect issues early
• Standardizing recipes and procedures to minimize formulation errors

By analyzing scrap data by shift, line, operator, and product variety, you can find the root causes of scrap generation and address them.

6. Labor Efficiency

Labor efficiency indicates how productively working time is utilized in manufacturing. It is calculated by comparing actual output to the expected output based on number of employees and time worked.

The formula is:

Labor Efficiency = (Actual Output / (Number of Employees x Working Hours))

For example, if a plant with 50 employees working 8 hour shifts produced 96,000 cans of soup in a month with 20 working days, the labor efficiency is:

(96,000 cans / (50 employees x 8 hours x 20 days) = 12 cans/hour/employee

Improving labor efficiency can drive significant cost savings through:

• Increased capacity and output with the same headcount
• Reduced need to increase labor despite rising production volumes
• Lower unit costs by producing more with less labor input
• Better understanding of optimal staffing needs

Food manufacturers can improve labor efficiency by:

• Standardizing operating procedures to reduce variability
• Implementing training programs focused on productivity
• Incorporating automation to reduce manual work
• Line balancing to avoid bottlenecks and idle time
• Designing ergonomic workstations to improve comfort and output

7. Machine Downtime

Machine downtime measures the total time equipment is not operating due to breakdowns, changeovers, planned maintenance or other stoppages. High downtime directly reduces production capacity.

Downtime is calculated as:

Downtime = Total Downtime / Total Available Time

For example, if a packing line has 50 hours of downtime last month, with total available hours of 740 hours in the month, the downtime percentage is:

50 hours / 740 hours = 6.8% downtime

Strategies to reduce downtime include:

• Preventive maintenance to avoid unplanned breakdowns
• Autonomous maintenance with operator driven care and maintenance
• Reducing changeover times through SMED techniques
• Benchmarking downtime by machine to focus improvements
• Monitoring peak downtime periods to identify underlying causes

The goal is to achieve less than 10% downtime for critical equipment to maximize production capacity.

8. Inventory Turnover

The inventory turnover ratio measures how efficiently inventory is managed by comparing cost of goods sold to average inventory investment. Higher ratios indicate better efficiency and inventory management.

Inventory Turnover = Cost of Goods Sold / Average Inventory

For example, a company with $3,000,000 annual cost of goods sold and an average inventory of $600,000 has an inventory turnover of:

$3,000,000 / $600,000 = 5 times

Improving inventory turnover can positively impact cash flow, reduce waste from expired or excess stock, and lower warehousing costs. Strategies include:

• Demand forecasting to better align inventory levels with sales
• Inventory optimization models to determine optimal reorder points
• Lead time reduction to decrease required safety stock
• Supplier managed inventory where suppliers replenish as needed

Comparing inventory turnover for different products and raw materials provides insights into items where more stock is being held than ideal. Addressing these issues improves overall efficiency.

Conclusion

Optimizing efficiency is critical for food manufacturers to stay competitive and profitable. The 8 KPIs discussed in this post offer a well-rounded view of the overall equipment effectiveness, productivity, quality, downtime, labor, and inventory aspects of an efficient operation.

While these KPIs provide invaluable performance metrics, the key is to act on the insights gained from regularly monitoring them. By setting targets for improvement and using data analytics to drill down into the drivers behind the numbers, food manufacturers can develop strategies for enhancing efficiency across the board.

The journey of continuous improvement never ends. But with focus, persistence, and commitment to efficiency, food companies can progress from being average to achieving best-in-class status.