How Engineers Obtain Valuable Insights Into the Fastening Process Through Torque Data on Assembly Lines

How Engineers Obtain Valuable Insights Into the Fastening Process Through Torque Data on Assembly Lines

Last Updated on February 29, 2024 by Ossian Muscad

Assembly line workers use torque tools to fasten parts together. These tools collect a wealth of data about the process, but what can engineers learn from it? With simple statistical analysis, engineers can obtain valuable and important insight into the fastening process.

No matter the tool’s accuracy, there will always be variations in the amount of torque applied to a fastener. A multitude of factors influence this process. Fortunately, statistical analysis can tell engineers when such variation is unacceptable.

This article will examine the importance of recording torque data on assembly lines and why it influences the assembly process. By understanding the torque data, engineers can improve the efficiency and quality of the assembled products.

 

What Engineers Can Learn From Torque Data

Torque data is essential for understanding how the assembly process works. By recording and analyzing torque data, engineers can improve the efficiency of the assembly line, the quality of the products being assembled, and the safety of the assembly process. Many factors can affect torque data, including:

  • The type of torque tool being used
  • The skill of the operator
  • The condition of the parts being assembled
  • The dimensions of the parts being assembled
  • Environmental factors, such as humidity and temperature
  • Friction, the difference in air pressure, part dimensions, and other factors 

 

Each of these factors can affect the torque data in different ways. For example, a skilled operator will likely produce more consistent torque data than an unskilled operator. In contrast, humidity can significantly affect torque data, as it can cause parts to expand.

With torque data, engineers can better prepare for these issues by understanding how they will affect the assembly process. Recording torque data guarantees engineers that they can improve the assembly process in many ways, including:

  • Determining the best torque tool for the job
  • Developing training programs for operators
  • Identifying and correcting issues with parts
  • Adjusting the assembly process to account for environmental factors

 

Finding the Standard Deviation

The goal of torque data analysis is to find the standard deviation of a torque tool. The standard deviation measures how much torque data varies from the mean or average torque. Engineers first need to find the mean torque to find the standard deviation.

Next, they need to subtract the mean torque from each torque reading. This difference is called the deviation. Finally, engineers need to square each deviation and add them all together to determine the sum of squares.

The standard deviation is found by taking the square root of the sum of squares and dividing it by the number of torque readings. This number gives engineers a measure of how much torque data varies from the mean torque.

 

Why Standard Deviation Matters

The standard deviation is important because it allows engineers to set limits on torque data. These limits help ensure that parts are fastened properly. Torque data that falls within limits is considered to be acceptable. Torque data that falls outside of the limits is considered to be unacceptable. Unacceptable torque data can be caused by many factors, including operator error, environmental factors, and issues with parts.

Engineers need to investigate the cause when torque data falls outside the limits. Doing so can determine if there is an issue with the torque tool, the operator, the environment, or the parts. Once the cause is determined, engineers can take steps to correct the issue and prevent it from happening again.

 

X-Bar and R-Charts

To analyze torque data effectively, engineers need to use X-bar and E-charts. X-bar charts help engineers track the mean torque over time. R-charts help engineers track the range of torque readings over time.

Both X-bar and R-charts are essential because they allow engineers to identify trends in torque data. These trends can be caused by many factors, including changes in the torque tool, the operator, the environment, or the parts.

By identifying trends in torque data, engineers can take steps to correct them. This helps ensure that parts are fastened correctly and consistently.

 

Creating an X-bar Chart

To create an X-bar chart, engineers need to follow these steps:

  • Collect torque data for a period of time.
  • Calculate the mean torque for each group of readings.
  • Plot the mean torque on the X-axis and the number of readings on the Y-axis.

 

Creating an R-Chart

To create an R-chart, engineers need to follow these steps:

  • Collect torque data for a period of time.
  • Calculate the range of torque readings for each group of readings.
  • Plot the range of torque readings on the x-axis and the number of readings on the y-axis.

 

Interpreting X-Bar and R-Charts

Once X-bar and R-charts are created, engineers need to interpret them. To do this, they need to compare the charts to control limits. Engineers set control limits and indicate the acceptable range of torque readings. When torque data falls outside the control limits, it is considered unacceptable.

 

Frequently Asked Questions (FAQs)

Q1: How often should torque data be collected on assembly lines?

Torque data should be collected continuously during the assembly process. This ensures that engineers have a comprehensive dataset to analyze for improving the efficiency and quality of the assembly line.

Q2: Can torque data vary between identical tools used in the same conditions?

Yes, even identical torque tools can produce slightly different torque data due to minor variations in manufacturing, wear and tear, and calibration differences. When analyzing torque data, it’s important to use the same tool for consistency. That’s why it’s recommended to have a designated torque tool for each assembly line.

Q3: How do engineers decide on the control limits for torque data?

Control limits are determined based on historical torque data, manufacturer’s specifications, and the criticality of the fastening process. They are set to ensure that all fastenings are within a range that guarantees product safety and integrity.

Q4: What’s the impact of tool calibration on torque data?

Regular calibration of torque tools is crucial to maintain the accuracy and reliability of torque data. Improperly calibrated tools can lead to incorrect torque applications, resulting in either over-tightened or under-tightened fasteners.

Q5: How does temperature affect torque measurements and the fastening process?

Temperature variations can affect both the torque tool and the materials being fastened. High temperatures may cause materials to expand, inaccurately influencing torque measurements. Engineers must consider temperature effects when analyzing torque data and setting control limits.

Q6: What steps should be taken if a consistent trend of unacceptable torque data is observed?

If a consistent trend of unacceptable torque data is observed, engineers should first verify the calibration and condition of the torque tools. Following that, a review of the assembly process, operator training, and environmental conditions should be conducted to identify and correct the underlying causes.

 

Measure Torque with DATAMYTE

DATAMYTE, a recognized industry leader in providing robust data collection and low-code quality management solutions, offers a range of torque products designed to enhance accuracy and efficiency in various manufacturing environments.

LightStar Torque Wrench

This precise torque-measuring instrument is designed to eliminate false readings that are difficult to detect. The LightStar Torque Wrench, series technology sensor, ensures that the operator can pull at any point on the wrench and will receive an accurate measurement.

DataMyte Torque Solution

This solution provides real-time reporting and torque data collection to improve and monitor torque continuously. It’s a comprehensive system for managing all aspects of torque control, from data collection to analysis and reporting.

New Generation of Digital Torque Wrenches

DATAMYTE has introduced a new generation of their LightStar™ Carbon Fiber Torque Wrench. These digital torque wrenches offer improved performance and accuracy, making them ideal for demanding industrial applications.

These products are part of DATAMYTE’s commitment to providing quality management solutions that enhance actionable results based on collected production data. They are designed to ensure consistent, reliable torque application, improving the quality and reliability of assembled products. Book a demo with us now to see how we can help you achieve your torque accuracy goals.

 

Conclusion

The utilization of X-bar and R-charts in monitoring and analyzing torque data is vital for maintaining high-quality assembly processes. These charts not only help in identifying trends and variances in torque application but also play a crucial role in ensuring that every component is fastened correctly, thus guaranteeing the safety and integrity of the final product.

By continuously collecting torque data and adhering to predetermined control limits, engineers can significantly enhance the efficiency, reliability, and overall performance of assembly lines. It’s clear that in the realm of manufacturing, precise control and analysis of torque application are indispensable for achieving excellence in product quality.

 

 

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