Substrate Processing Unit Status Display for Time-Series Abnormalities
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Solution Overview
Problem
In substrate processing apparatuses, operators face difficulty in grasping the status of multiple processing units due to overwhelming time series data, making it hard to identify abnormalities and prioritize urgent units effectively.
Innovation Solution
A data processing method that calculates evaluation values by comparing time series data with reference data and displays an evaluation result screen with pie charts showing the ratio of abnormalities, where the pie chart size changes based on the number of abnormalities, along with additional visual indicators like arrows and face marks to represent trends and urgency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all time series data from multiple processing units is displayed on the screen, then complete information is provided, but the operator cannot easily grasp the status of the substrate processing apparatus
Solution Approach 1:
The patent segments the overwhelming time series data into unit-specific summaries, where each processing unit is represented by a pie chart showing abnormality ratios. This segmentation transforms the undifferentiated mass of data into discrete, comparable units that can be quickly scanned and understood, resolving the contradiction between providing complete information and enabling easy status graspability.
Solution Approach 2:
The patent employs color-coded pie charts and visual indicators to represent different levels of abnormality and status. By using color changes and visual differentiation, the system maintains complete information while making it immediately perceptible and easy to grasp at a glance, allowing operators to quickly identify problematic units without being overwhelmed by raw data volume.
2Measurement precision
If detailed time series data is displayed for each processing unit, then abnormality detection precision is improved, but the complexity of the display screen increases
Solution Approach 1:
The patent extracts the essential abnormality information from detailed time series data and presents it in simplified pie chart format. By taking out only the critical metrics (abnormality counts and ratios) while eliminating redundant temporal details, the system maintains high abnormality detection precision while significantly reducing display screen complexity.
Solution Approach 2:
The patent transforms one-dimensional time series data into two-dimensional pie charts that visualize abnormality distributions across different processing units. This dimensional transformation allows precise abnormality detection to be conveyed through visual area proportions rather than numerical tables, reducing display complexity while preserving detection precision.
3Productivity
If the number of processing units is increased to improve productivity, then output increases, but the difficulty of detecting and measuring abnormalities increases
Solution Approach 1:
The patent merges the status information of multiple processing units into a unified visual display format. By combining individual unit pie charts into a single screen overview with consistent visual language, the system enables effective monitoring and abnormality detection across increased numbers of processing units, allowing productivity scaling without proportionally increasing detection difficulty.
Solution Approach 2:
The patent creates a universal pie chart template that serves multiple processing units simultaneously. This multi-functional display format can accommodate any number of processing units while maintaining consistent abnormality detection capabilities, allowing the system to scale productivity without increasing the fundamental difficulty of detecting and measuring abnormalities.
Data Source
AI summary
In order to process time series data obtained in a substrate processing apparatus having a plurality of processing units, a data processing method includes an evaluation value calculation step of obtaining a score of the time series data by comparing the time series data with reference data, and a result display step of displaying an evaluation result screen including, for each processing unit, a number of score errors being a number of substrates of which score is abnormal, and a pie chart showing a ratio of the number of score errors to a number of processed substrates. A display size of the number of score errors and that of the pie chart change depending on the number of score errors.