The Inconsistent Archive
Your glaze test logs are likely a fragmented mess. A photo on a white background one day, on a wooden table the next. Your notes say "cranberry red," but it looks burgundy in different light. This disconnection between image, recipe, and data makes finding past successes or diagnosing failures a manual, frustrating hunt.
The Principle: Structured, Searchable Visual Data
The core framework for modern documentation is to treat every glaze test as a structured data point, not a scattered note. By systematically linking a standardized photo with consistent metadata, you transform subjective observations into an objective, searchable database. This structure is what allows AI and smart search to function.
Your Foundational Tool: A Digital Notebook
The first step isn't complex AI; it's consistent logging. Use a free, flexible digital notebook like Obsidian or Notion to be your single source of truth. Its purpose is to force structure. Each test entry becomes a dedicated page where you can link a standardized image, its recipe ID, firing log, and performance notes.
Mini-Scenario: You need a glossy, stable glaze for a new vase design. Instead of flipping through notebooks, you query your digital log: "Show me all glazes with a gloss meter reading >70 GU that are also stable on vertical surfaces." Your linked system returns the viable candidates instantly.
Three Steps to Implement AI-Ready Logging
- Standardize the Capture. Always photograph tests on the same, non-reflective mid-grey backdrop. This removes environmental variables, allowing for true visual comparison and setting the stage for reliable future AI analysis of color and texture.
- Enforce a Data Template. For every test, create an entry with a unique Test ID (e.g., 250415-Shino01). Mandatory fields must include the Recipe ID, objective color description (e.g., "rutile blue breakout"), quantified texture, firing log details, and performance notes. Add at least five descriptive tags like
#crystallineor#cone10_reduction. - Link Relentlessly. This is the most critical step. Link your test entry back to its master recipe file. This bridges the disconnection, ensuring the image is forever tied to its formula and results. This network of linked data is your automation foundation.
Key Takeaways
Move from subjective, disconnected records to objective, structured data. Consistency in your photography and logging is the prerequisite for any automation. By using a digital notebook to link images, recipes, and results, you build a powerful, queryable knowledge base that turns your past experiments into a proactive asset for perfecting future batches.
Word Count: 498
Top comments (0)