Programmable Display Screen Prediction for Equipment Error Response
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Solution Overview
Problem
In manufacturing fields, operators face delays in responding to equipment errors due to the time-consuming process of switching between screens on programmable displays, which hinders prompt resolution of issues.
Innovation Solution
A programmable display system that learns the probability of screen usage during equipment events and prioritizes content display based on detected events, using a detection part, learning part, and specification part to quickly show relevant screens, thereby reducing the time to address errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If operators manually switch between screens on programmable displays to respond to equipment errors, then they can access necessary information, but the response time is delayed due to the time-consuming screen switching process
Solution Approach 1:
The system performs preliminary actions by learning and predicting which screens will be needed before the operator actually needs them. When an equipment error occurs, the prediction unit has already prepared the relevant screens based on historical operation data, allowing immediate display without manual navigation delays.
Solution Approach 2:
The programmable display system serves itself by automatically predicting and preparing screens without operator intervention. The learning unit continuously analyzes operator behavior patterns and automatically configures the display sequence, making the system self-optimizing and eliminating the need for manual screen switching operations.
2Adaptability or versatility
If the programmable display stores and manages multiple pieces of content for various equipment events, then it can provide comprehensive information, but the complexity of managing and retrieving the right content increases
Solution Approach 1:
The learning unit continuously monitors operator screen selection behavior and uses this feedback to refine predictions. The system analyzes which screens operators actually access during equipment events and adjusts the prediction algorithm accordingly, creating a self-improving content management system that adapts to actual usage patterns.
Solution Approach 2:
The system changes the parameter of content organization from static manual categorization to dynamic probability-based ranking. Instead of fixed screen sequences, the prediction unit adjusts content priority based on learned probabilities, transforming the content management approach from rigid to flexible and adaptive.
Data Source
AI summary
To provide a programmable display that enables content for coping with an event that has occurred to be promptly used. A programmable display that can communicate with a control device that controls production equipment includes a display; a storage device that stores a plurality of pieces of content that can be used by the programmable display; a detection part that detects a predetermined event that occurs in the production equipment; a learning part that learns a probability that each of 5 the plurality of pieces of content will be used under a condition that the predetermined event occurs by monitoring content used by the programmable display when the predetermined event is detected; and a specification part that specifies content having a high possibility of being used by the programmable display among the plurality of pieces of content based on the learned probability when the predetermined event is detected.