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AIT Engineering Notes #4: Collecting Data Alone Does Not Lead to Improvement

Featured visual for AIT Engineering Notes #4.

Collecting data alone does not create improvement.

When NX usage data is aggregated, patterns begin to appear: “this command is used frequently” or “this operation is repeated many times.”

However, it is risky to decide improvement measures from the numbers alone. Why is the operation frequent? Is the work really necessary? Is it driven by a design rule? Can it be replaced by another method? Can it be automated? These backgrounds cannot be understood from data alone.

That is why we need “data analysis × process understanding × shop-floor interviews.”

AI may also be useful here. It can organize large volumes of logs and explain patterns and characteristics in an understandable way. People can then review the results and decide what should be improved.

AI does not decide the answer; it creates material that helps people think. We see this as one possible role of AI in Engineering Automation.

What would you want to learn from CAD usage data?

AIT Engineering Notes #3: Introduced Functions ≠ Functions Actually Used

Featured visual for AIT Engineering Notes #3.

“Introduced functions” and “functions actually used” are not necessarily the same.

CAD systems offer many useful functions, and many companies also establish internal standards and automation tools. However, having useful functions available and actually using them in day-to-day work are different matters.

When a function is not being used, there can be many reasons:
• people do not know it exists
• they do not know how to use it
• it does not fit the current work
• they are accustomed to the existing operation
• another method is faster

The important point is not to conclude that “not used = a problem.”

Find the trend in the usage data, then confirm the background with the shop floor. From there, the next action becomes clearer: education, standardization, a workflow change, or perhaps automation.

Data is not the answer itself. It is material for finding better questions.

Are there functions in your workplace that were introduced but are rarely used?

AIT Engineering Notes #2: Clues for Improvement Are Hidden in NX Syslog

Featured visual for AIT Engineering Notes #2.

NX Syslog contains clues for improvement.

When NX is used every day, the system records a variety of execution information. Syslog may be thought of mainly as “a log to check when trouble occurs.”

However, viewed from another angle, it also contains information that can help us understand how NX is actually being used.

For example, by aggregating the commands used and their trends, we can gain clues about:
• frequently used functions
• functions that are hardly used
• operations that are repeatedly executed
• usage patterns by user

Of course, logs alone cannot tell us why a particular operation was performed. That is why the combination of looking at the data, finding patterns, and talking with the shop floor is important.

Syslog can be more than a troubleshooting log; it can also become a starting point for thinking about process improvement.

Have you ever used NX Syslog for anything other than troubleshooting?

AIT Engineering Notes #1: How Is NX Actually Being Used?

Featured visual for AIT Engineering Notes #1, also shared on LinkedIn and published here on the official website.

Manufacturing companies introduce many CAD functions, design rules, and automation tools into their engineering environments.

However, can we objectively understand which functions are used most often, where repetitive work exists, which operations take time, and whether the mechanisms introduced are truly being used on the shop floor or in design practice?

Interviews with engineers are extremely important. At the same time, some aspects are difficult to see through human perception alone. This is where actual usage data becomes useful.

By looking at both human insight and data, we can better understand the real state of the engineering workplace. Before thinking about automation, it is important to first understand the current situation. In October, we will explore the theme of improving workflows through NX usage data.

In your workplace, do you understand how CAD is actually being used?