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10 Manufacturing KPIs You Can Start Tracking Today with IIoT

So your company is growing, and you want to gain more control over your business operations by tracking and analyzing data. But you’re stuck at knowing what metrics to track, when to track them, and what they mean. You’ve come to the right place.

In this article, we’ll explain what KPIs in manufacturing are, what makes them useful, and offer up 10 manufacturing KPIs you can start using today.

 

What Are KPIs In Manufacturing?

Key Performance Indicators (KPIs) in manufacturing are measurable metrics that manufacturers use as benchmarks to evaluate how effectively your manufacturing company is achieving its business goals.

You can set KPIs to track overall business performance on a macro level or zoom in to measure the performance of various departments on a micro level. For example, you might set a goal to reach a predetermined amount of revenue for the year. Or, you can set goals for production capacity and track KPIs aligned with waste, downtime, and rework.

Manufacturing KPIs are important for identifying where your business is excelling or underperforming so your team can make informed decisions about how, where, and when to improve.

 

What Makes a Useful Manufacturing KPI?

You can track all the metrics in the world, but if they’re not tied to your bottom line, they’re not useful KPIs. A good way to determine whether you’re tracking the right KPIs is to use SMART goals. SMART stands for specific, measurable, achievable or actionable, relevant, and timely.

Therefore, a useful manufacturing KPI should be:

  1. Specific: You can clearly state what is being measured.
  2. Measurable: The metric is tangible and can be quantified.
  3. Achievable/Actionable: The goal is realistic and within your control.
  4. Relevant: The metric is tied to your business’s goals.
  5. Timely: You are tracking performance within a key timeframe (e.g. 90 days).

 

Top 10 Manufacturing KPIs to Track

These manufacturing KPIs will help your team make informed decisions. You may also want to learn about the types of manufacturing variances as they go hand-in-hand with these KPIs.

 

1. Overall Equipment Effectiveness (OEE)

Overall Equipment Effectiveness (OEE) is used to measure the efficiency of your production processes. It compares how well your manufacturing operation is actually used compared to its full potential. OEE is determined using three key components: Availability, Performance, and Quality.

The formula for OEE is:

  • OEE = (Availability x Performance x Quality) / 100

To calculate OEE, you’ll first need to calculate the three components. The formula for each is:

  • Availability = (Operating Time / Planned Production Time) x 100
  • Performance = (Ideal Cycle Time x Total Count) / Operating Time
  • Quality = (Good Count / Total Count) x 100

To break these formulae down a little further, you should know that:

  • Operating Time is the total amount of time the equipment is running.
  • Planned Production Time is the total amount of time the equipment is scheduled to operate.
  • Ideal Cycle Time is the fastest cycle time the equipment can produce a product.
  • Total Count is the total number of units produced, including defective units.
  • Good Count is the number of units produced that meet your industry’s quality standards.

Tracking OEE is important because it helps you identify losses due to downtime or other productivity losses.

 

2. Cycle Time

Cycle Time measures the total amount of time it takes to complete a production cycle. Tracking and measuring cycle time helps you understand and improve the efficiency of your production processes.

To calculate cycle time, you need to measure processing time, wait time, transfer time, and setup time. 

The formula for cycle time is:

  • Cycle Time = Total Production Time / Number of Units Produced

This will help you determine how many minutes it takes to produce a single unit.

Cycle time helps with production capacity planning, identifying bottlenecks, and measuring overall production efficiency. Faster cycle times lead to faster order fulfillment, giving you a competitive edge over manufacturers who don’t track cycle time and therefore cannot make improvements to their processes.

 

3. Downtime

There are two types of downtime in manufacturing: planned downtime and unplanned downtime. Both can and should be measured, whether they are due to scheduled maintenance, upgrades, changeovers, failure, material shortages, product quality control issues, or human error. Tracking downtime will offer your team actionable insights into overall productivity and recurring issues.

You can measure downtime in a few different ways:

  • Total Downtime = The sum of all downtime events over a specific time period.
  • Downtime Frequency = Number of downtime events / Time period
  • Mean Time Between Failures (MTBF) = Total operating time / Number of failures
  • Mean Time to Repair (MTTR) = Total repair time / Number of repairs

 

4. Production Yield

In manufacturing, production yield is the ratio of good quality units produced to the total number of units that started the production process. Production yield measures how efficient and effective your manufacturing process is when it comes to producing quality products.

If you’re seeing a high production yield, it means that your production process is doing well. A low yield means that there are issues with the production process that need to be solved.

The formula for production yield is:

  • Production Yield = (Good Units / Total Units Produced) x 100

 

5. Throughput

Throughput is a KPI in manufacturing that measures the rate at which a production system generates finished products. This KPI reveals the efficiency of a manufacturing process by determining how many units of a product are completed within a certain period.

A high throughput indicates high efficiency. A low throughput means you need to search for bottlenecks or inefficiencies in the production process.

The formula for throughput is:

  • Throughput = Total Production Output / Production Time

 

6. Scrap Rate

Scrap rate is the percentage of materials or products that are rejected due to defects or poor quality in general. If your scrap rate is high, your waste is high. You’ll need to figure out where errors and inefficiencies are happening in the manufacturing process and solve them.

The formula for scrap rate is:

  • Scrap Rate = (Scrap Units / Total Units Produced) x 100

 

7. Inventory Turnover

Inventory turnover is an important KPI for any manufacturing business. It is a financial metric that measures how frequently your inventory is sold and replaced over a predetermined period. If your inventory turnover is high, you likely have strong sales processes and are operating efficiently. If it’s low, you may be suffering from overstocking, obsolescence, or lack of sales.

The formula for inventory turnover is:

  • Inventory Turnover = Cost of Goods Sold (COGS) / Average Inventory

 

8. Cost Per Unit (CPU)

A standard metric for manufacturers to track, cost per unit (CPU) measures the cost to manufacture one unit. CPU is used to determine pricing, regulate costs, and analyze the profitability of a product. When calculating cost per unit, include all direct and indirect costs in the equation.

The formula for calculating CPU is:

  • CPU = Total Production Costs / Total Units Produced

 

9. On-Time Delivery (OTD)

On-time delivery measures just that: the percentage of deliveries delivered on or before the scheduled delivery date. OTD is a valuable KPI because it offers insights into customer satisfaction, supply chain efficiency, and the financial impact of lost and late deliveries.

The formula for calculating OTD is:

  • OTD% = (The number of on-time delivery / the total number of deliveries) x 100

 

10. First Pass Yield (FPY)

First pass yield measures the percentage of products that are manufactured correctly the first time without rework, defects, or modifications. Quality assurance teams use FPY to measure the efficiency and accuracy of your production process. Financial teams use FPY to identify areas your team can improve with regard to cost efficiency. A higher FPY percentage also translates to higher customer satisfaction because it means products are consistently and reliably produced to spec with fewer delays.

The formula for calculating FPY is:

  • FPY% = (The number of good units produced / the total number of units produced) x 100

 

How IIoT Platforms Make Tracking Manufacturing KPIs Easy

The Industrial Internet of Things (IIoT) automates and streamlines the processes required to effectively track manufacturing KPIs. Let’s be honest: successfully tracking KPIs requires capturing and processing a truly enormous amount of data. It’s unrealistic to do it manually.

IIoT platforms use sensors and smart devices to collect critical data automatically. You can apply IIoT devices to machinery, production lines, and even your workforce. Your team can even look at and analyze this data in the moment, or generate weekly, monthly, and quarterly reports automatically to review on a schedule.

With centralized data management, IIoT platforms store these massive volumes of data in one location. This keeps data clean and ensures your team is working off a golden source of truth.

In fact, each team or department can customize their dashboards to include up-to-date visualizations of data. For example, your logistics team can open their screens to find an automatically generated report of on-time delivery (OTD) data month-over-month. They can customize these reports in a myriad of ways using IIoT platform’s built-in advanced analytics.

Importantly, IIoT platforms integrate with ERP and MES systems so you can share data and insights across your entire organization. 

In other words, the benefits of IIoT in manufacturing greatly outnumber the costs.

 

Let Us Help You Set and Track KPIs for Manufacturing

Setting and tracking manufacturing KPIs is an on-going process. As your company grows, so will the importance of collecting and analyzing data. Minimize the amount of data tracking your workforce needs to do so they can focus on making data-backed decisions and innovations. Ask our experts about implementing an IIoT solution today.

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