Using Analytics from Connected Tools to Gain Insights

Assembly manufacturers can utilize the power of data and its derived insights to increase productivity, improve quality, optimize performance and lower costs. Connected devices are growing exponentially in the manufacturing industry, and facilities now use programmable logic controller (PLC) platforms to connect and communicate with equipment.

The real advantage of connected assembly tools is getting the fastening data. But, collecting data is not where the value lies. Manufacturers achieve value by analyzing the data and using it to gain insights into how to improve production processes and product quality.

A digital factory is only as valuable as the people who understand how to analyze the data and then take appropriate action from the insights. The key to accomplishing this is training the workforce so they can leverage the data and analytics and understand how best to use the insights they’ve gained.

A successful controller implementation involves a system that is simple to use so both technically savvy and non-technical users can take advantage of its benefits. To start, it is essential to comprise a list of data and analytic parameters to be gathered through the system and then articulate how each organizational department will use the insights.

Manufacturers rely on tool controller suppliers to build in the functionality to collect data, provide the capability for analysis, and incorporate indicators to notify operators, line supervisors and other personnel when a threshold exceeds on a fastener. For example, tool controllers provide a common set of data, with factors like actual torque used, what the angle result was, the time and date when the fastening occurred and which tool and station were used to tighten a screw or bolt. They then associate this data with a variety of parameter targets. For example, if the tightening result was 10, what were the targets or limits? Analytics can show why the tool did not meet a target parameter or why the target was exceeded. It can also show what a tool tried to do, what the tool actually did, when the tool did it and which tool did the work.

After an engineer sets a predictive threshold on the controller, they can then use a third-party application, or better yet, use a controller like the INSIGHTqc with built-in Statistical Process Control (SPC) to monitor the percentage of completions for a particular fastening cycle. If the number of uncompleted actions goes above a 5 percent threshold, the controller notifies a line supervisor with an email alert showing the station and that the fastener tightening has gone over the maximum threshold. Since the controller stores the data internally, line supervisors and quality control personnel can review and analyze the data and see the tightening curves. With this information, they can make adjustments to the program, investigate the components or correct a process to address the problem.

The digital factory is a competitive advantage. Manufacturers can benefit from the insights that connected tools provide and differentiate themselves by using the power of data analytics.