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Ken Deng
Ken Deng

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From Scattered Notes to Smart AI: Finding Patterns in Your Firing History

Are your glaze results a beautiful mystery, changing with the seasons? You take meticulous notes, but connecting a slow-cooling cycle to that perfect crystal formation feels like intuition, not science. What if you could turn that intuition into actionable data?

The key is shifting from asking vague questions to asking specific, data-based questions that your logged information can answer. Instead of wondering “Why are my glazes inconsistent?”, you can query a consolidated dataset.

The Framework: Ask Your Data a Better Question
Build your analysis on this structure: "Compare [Group A] and [Group B] for [Specific Outcome]. What was the difference in [Measured Variable]?" This forces you to define success/failure and isolates one variable from your logs.

For example: "Compare the successful and failed firings for my crystalline glaze. What was the average cooling rate difference between the two groups?" This precise question can be answered by analyzing your kiln logs.

Your Central Hub: Google Sheets
A simple spreadsheet is a powerful engine for this. Use Google Sheets’ built-in “Explore” feature (click the star icon in the bottom right) as your analysis tool. After you merge your firing logs, material batch numbers, and even notes from image logs on glaze thickness, “Explore” can automatically spot trends, correlations, and create charts from your columns.

How to Start Implementing This Week

  1. Ask One Specific Question: Pick one recurring issue, like pinholes or color variation. Formulate a question using the framework above, targeting data you already log.
  2. Run Your First Analysis: Input your relevant historical data into a spreadsheet. Use the “Explore” function to ask your question and uncover a potential pattern.
  3. Close the Loop: Fire a test based on the insight. Log all results—good or bad—back into your system. This confirms or refutes the pattern, making your data smarter.

By consistently logging data and learning to interrogate it with specific questions, you transform anecdotal experience into reliable, repeatable knowledge. Your kiln log becomes a predictive tool, not just a diary.

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