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4 Helpful Ways To Measure Productivity In Manufacturing Processes



4 Helpful Ways To Measure Productivity In Manufacturing Processes

Manufacturing processes are the set of sequential operations that transform raw materials into finished goods. Productivity is a measure of how efficiently these manufacturing processes are carried out. In other words, productivity measures how much output is generated per unit of input (labor, capital, or land). It is often expressed as a ratio or percentage. Measuring productivity in manufacturing processes is crucial because it can provide insights into how well a company uses its resources. Companies can use productivity measures to set goals, compare performance across factories or plants, and identify areas for improvement. There are many different ways to measure productivity in manufacturing processes. This article will discuss the helpful ways to measure productivity in manufacturing processes.

Use Overall Equipment Effectiveness

Overall equipment effectiveness is one of the most important metrics for measuring productivity in manufacturing processes. It takes into account three factors: availability, performance, and quality. OEE is a great metric to use because it provides a holistic view of productivity and helps identify areas for improvement. It is also helpful for benchmarking purposes. The overall equipment effectiveness (OEE) metric makes it easy to compare the productivity of different manufacturing processes. Though OEE is easy to compute, there are some disadvantages. overall equipment effectiveness cannot be used to compare the productivity of two factories with different-sized factories. Also, OEE does not take into account the quality of the product being produced.

Cycle Time

Cycle time is the amount of time it takes to complete one cycle of a process. In manufacturing, cycle time is often used to measure the efficiency of a production line. The shorter the cycle time, the more productive the line is. Cycle time can be measured in several ways, but the most common method is to simply time how long it takes to complete one cycle of the process. It’s important to note that cycle time doesn’t just include the time it takes to produce a product physically. It also consists of any time spent on quality control, setup, or other activities related to the production process. Theoretical cycle time is the minimum time it should take to complete a process and is often used as a benchmark to measure productivity. In practice, cycle time is usually longer due to downtime and quality control.


Throughput is a measure of how many products or parts are produced over some time. In manufacturing, throughput is often used as a measure of productivity. The higher the throughput, the more productive the line is. Throughput can be affected by many things, such as the efficiency of the machines, the quality of the raw materials, and the workers’ skills. It is important to monitor throughput so that you can identify any problems in the manufacturing process and take steps to improve productivity. Though, it is worth noting that throughput is not the only measure of productivity. Many other factors, such as quality and safety, are also important. It is important to monitor all of these factors to ensure that your manufacturing process is as efficient and effective as possible.

Output Per Hour

This is the most basic measure of productivity and simply involves dividing the number of products produced by the number of hours worked. It’s a good starting point, but it doesn’t consider factors such as labor intensity or machine utilization. The main advantage of this measure is that it’s easy to calculate. Though, it can be improved by also considering the number of workers. Many businesses use this measure in conjunction with others to get a more accurate picture of productivity. At times, it may be necessary to use a daily or weekly output measure rather than an hourly one. However, to avoid distortion, care should be taken to ensure that the hours worked are consistent across the workforce. This measure is also sometimes referred to as labor productivity.

Value Added

This is a measure of the economic value that a business adds through its manufacturing processes. It’s calculated by subtracting the cost of raw materials from the sales value of the finished product. While it doesn’t consider all aspects of productivity, it does provide a good indication of how much value is generated by the manufacturing process. It’s also an excellent way to compare the productivity of different manufacturing processes. The higher the value added, the more productive the process.

Manufacturing Cycle Efficiency

This measures the time spent actively manufacturing products compared to the total time it takes to complete a manufacturing cycle. It’s an excellent way to assess the manufacturing process’s efficiency and identify areas where improvements can be made. It is usually expressed as a percentage. The formula for calculating it is: ( manufacturing time / total production cycle time) x 100. It is important to note that this does not include time spent on Quality Control or setup, as these are not considered part of the manufacturing process. Many factors can affect MCE, such as the number of workers on the production line, the manufacturing product’s complexity, and the availability of raw materials.

Operating Expense Ratio

This tells you how much it costs to produce one unit of product. It’s a valuable metric for understanding the profitability of a product and can also help to identify areas where cost savings can be made. It’s calculated by taking the total operating expenses for some time and dividing it by the number of units produced during that same period. The lower the ratio, the more efficient your manufacturing process is. It’s important to remember, however, that this metric doesn’t consider the cost of raw materials or other factors beyond your control. This is just a measure of your manufacturing process itself.

In conclusion, there are many helpful ways to measure productivity in manufacturing processes. By using data gathered from machines and workers and analyzing trends over time, companies can make informed decisions about how to improve their productivity. Regular benchmarking against other companies can also help identify areas where improvement is needed. Finally, new technology and data-gathering techniques can also help improve the accuracy of productivity measurements. By taking these steps, companies can ensure that they are making the most efficient use of their resources and maximizing their output.