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How To Utilize Data to Improve Assembly

ir tools
ir tools
ir tools
ir tools
March 1, 2020

Five ways data can help improve assembly

Using information to power better assembly performance by detecting inconsistencies, understand operator performance, and more.

Smart tools can provide information on the proper running speed and tightening strength of power tools, driving greater assembly efficiency.

Data-driven decisions help companies improve product quality and keep costly mistakes to a minimum. However, data is only valuable to manufacturers if they can analyze and apply insights accurately and consistently.

While digital technologies like connected tools can help manufacturers make crucial production decisions to boost quality and efficiency, the first step is understanding how the collected data can amplify continuous improvement efforts. Here are five ways manufacturers can use collected data to improve their production process.

1. Detect tightening inconsistencies

Both the quality and consistency of a fastened joint often rely on how fast a tool is running during the fastening cycle. If the tool runs too fast or too slow it can lead to the joint not being properly tightened or relaxed. Connected tools have data recording functions that manufacturers can leverage to make sure tools are running at the proper speed and can detect any inconsistencies in the tightening process.

Looking for quick answers on assembly and manufacturing topics? Try Ask ASM, our new smart AI search tool. Ask ASM →

2. Understand operator performance over time

With reviewable insights from connected tools, manufacturers can increase accountability with their teams to meet their production targets. The simple analysis of thousands of recorded data points helps those in charge of the assembly process identify where operators are thriving and where focus is needed to improve throughput or performance.

3. Prevent quality holds caused by improperly secured fasteners

If an operator incorrectly installs a fastener, a smart tool can detect the condition and notify the user of the mistake immediately. Operators can address the issue in-line, before it becomes a systemic quality problem and creates costly production delays and rework due to quality issues.

4. Identify areas of waste to improve throughput

If a tool runs too slowly or the operator does not optimize it properly for the tightening process, a station could fail to meet its required takt time. With programmable data-collecting tools, manufacturers can analyze insights derived from the tightening records to identify areas of delays, takt misses or bottlenecks and can make continued strides towards optimizing lean production operations.

5. Support line re-balancing activities

Connected tools that are easy to use and to set up are easily transferable to different employees, as well as are the duties of managing them. When repositioning operators to balance an assembly line, digital technologies that are simple and flexible will help quicken the transition and optimize uptime in facilities, both for those responsible for using them and for those setting them up.

While it’s important to collect data, the information is useless if manufacturers don’t know what to do with the information or how to implement change. Data without insights is a digital paperweight, and the ability to derive actionable insights from the data is the key to success.

Visit irtools.com/Insightqc to learn more.

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