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Enhancing Productivity Using Time Study

Updated: Nov 15, 2023

When you work in the manufacturing industry of any kind, your enterprise's duty is to ensure every work is done as quickly and efficiently as possible. Well, is there a way to measure every work like this? Can enterprises really identify the best way to do something, and if so, how do they do it?

Apparently, there are ways to quantify production methods to determine which one is the best. One of the best ways to find the most efficient and productive production method is by performing time studies.

Ever heard of a time study before? It’s quite simple and is much like what the name suggests.

A time study in manufacturing basically examines every step in the manufacturing process and determines how long they all take on an average basis. Time study is one of the useful ways to measure how much time employees spend on each part of a process, and for processes that involve sequences of actions that repeat in a cycle.

Then, by carefully examining how long each step in the process takes, it is possible to identify where the most important times are lost and how they can be improved, shortened, and made more efficient.

Another type of study that you can do with a time study or as its own separate entity is a motion study. A motion study follows the same basic concept but applies to motions rather than time. The exact movements of workers in the production process are recorded and then analyzed so that enterprises can identify which actions are inefficient or can be improved.

Enhancement of productivity is an important factor for the manufacturing industry to survive and breakthrough. With the idea of such process observations in the manufacturing industry, they can achieve the most productive and efficient method possible by analyzing the finer details of the manufacturing process, thus tailoring the process to make it as ideal as possible.

The Importance of Time Study in Manufacturing

For over a century, time study has been an essential method for gathering data on manufacturing processes. Frederick Taylor began time studies in the 1880s to determine the duration of particular tasks occurring under specific conditions. The time study was a component of the scientific management theory. Taylor's approach focused on reducing time waste for maximum efficiency, therefore manufacturers have started to use time studies to optimize their operations.

In order to understand time in manufacturing, it is important to consider time-sensitive tasks and their impact on operational excellence. To give an example, how long will it take you to achieve X and what will be the transitive Y value of this time?

Where does time play a significant role in your manufacturing operations? How should it be measured? And what does the value in a time study represent? Here are the main ways time can be spent in the manufacturing industry:

Production time: Production time is measured from the moment the raw materials enter the production process to the moment the finished products leave the assembly line. Reducing production time by eliminating non-value-adding activities helps to reduce costs.

Maintenance time: Maintenance time is the time that takes to service a machine back to an operational standard Since maintenance time is equal to downtime, reducing it helps save money and increase profits.

Takt time: Takt time is a calculation of the available production time divided by customer demand. The purpose of takt time is to precisely match production with demand. If takt time matches with the actual production rate, it means reduced bottlenecks and eliminated areas of inefficiency.

How Are New Technologies Changing Time Study?

One of the defining traits of the Industry 4.0 factory is increased connectivity. Especially, IoT connections and cloud computing started to allow for the creation and storage of data on an outstanding scale. With the help of AI, computer vision, and no-code applications, it has become easier to gather data from manual work.

Now it's possible to analyze manufacturing lines through cameras in an automated way, AI-based algorithms automatically understand the actions of a worker and gather time study data. Because of the data collection is automated, it eliminates human bias from the model. And also AI can find patterns in data that humans alone can not (because AI gets better over time) predictive maintenance is an attainable goal.

As Khenda, we help companies to achieve operational excellence through various advanced engineering tools including time study, line balancing, root cause analysis and many more.

We hope in your work with time studies, you can find many ways to improve your manufacturing process with Khenda to achieve maximum efficiency and productivity.

For more information, you can reach out to us at



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