A handheld application for inspection and rework

CoreEnterprise Systems DevelopmentAndroid App DevelopmentRequirements DefinitionUI/UX DesignBusiness Process Improvement & Automation

Organisation: YAMATO KOGYO Co., Ltd.
Period: Jan 2023 – Dec 2024
How it started: Assigned
My part: Design through development, rollout, and QA, alone (requirements shared with my section manager)
For whom: The inspection and rework division (rolling): its staff and floor operators
What changed: Handwritten records, inaccurate and unusable for analysis → Structured data per individual product, accumulating in real time

What I did

Made per-piece inspection and rework records possible, which handwriting could not deliver.
Stayed with it end to end, from defining requirements (shared with my section chief) through design, development, testing, briefing the floor and QA after rollout.
Kept improving it after rollout as the floor asked, for example showing the label colour at the moment a label is issued.

Mocked the screens up in Figma and refined the UI while the operators tried them.
Kept the operation minimal so a record fits between tasks: reading product information from a QR code instead of typing it, pinning the defects that come up most so they can be tapped.
For the label colour, turned the real product label into SVG and reproduced the printed result in the app, so the wrong one is harder to pick.

Extraction that goes inside the implementation, visualisation that serves the business goal.
I work alongside the business from the definition of the metric itself, and stay with it through to the insight it was asked for. From IoT systems to web and mobile, I have broad experience of building software, so I extract data with a deep understanding of the implementation behind it. Visualisation and analysis are the same — I put generative AI to work and deliver quickly, in the form the person will actually use. Underneath that, I can shape the data, the context around it and the ETL that feeds it for the age of generative AI, so that people and AI alike can work with what is there.

I can design the whole system, not one layer of it
From hardware up to the cloud, I can draw the blueprint. I have built IoT hardware, web applications, mobile apps, and a game service platform running in the cloud, so I can combine pieces I have not used before and still see how the whole thing fits together. Holding that picture is also what lets me hand implementation to generative AI and still carry a whole system on my own.
I do not stop at what the tool allows
When Grafana or WebPerformer could not do what was needed, I wrote the plugin or the surrounding tooling myself. When the open-source catalog we depend on, tbls, fell short, I filed the issue and the pull request. I read the documentation and the source, and I keep digging until I find the route that actually serves the goal — and where the result is worth sharing, I share it.