Real-Time Production Visualization Tools
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Solution Overview
Problem
Production system data is often difficult to comprehend and not timely enough to identify factors that can be modified to improve production system performance, requiring years of experience to effectively manage operations and processes.
Innovation Solution
A suite of visualization tools that display production system data in real-time, providing graphical representations of work measure attributes and takt time calculations to help identify and correct issues causing negative impacts on production performance, implemented using a computer system with user interfaces and pass-fail monitors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If production system data is displayed in traditional formats, then data completeness is maintained, but data comprehensibility deteriorates and real-time understanding becomes difficult
Solution Approach 1:
The production system data is segmented into multiple hierarchical levels (facility level, production line level, production cell level, machine level) allowing operators to view data at appropriate granularities. Each level displays only relevant metrics and details, transforming the overwhelming comprehensive data into manageable segmented views that improve comprehensibility without losing underlying information completeness.
Solution Approach 2:
The system adds temporal and hierarchical dimensions to traditional production data displays. Time-series visualizations show trends over configurable periods, while hierarchical navigation allows drilling down from facility-level summaries to machine-level details. This multi-dimensional approach transforms static comprehensive data into dynamic, navigable visualizations that are both complete and comprehensible.
2Measurement precision
If production data is collected and processed thoroughly, then measurement precision is improved, but response time deteriorates making real-time adjustments difficult
Solution Approach 1:
The system pre-calculates and pre-processes production metrics at multiple hierarchical levels, maintaining aggregated summaries ready for immediate display. When data arrives, pre-computed trends and comparisons are already available, eliminating the need for real-time complex calculations. This preliminary processing ensures measurement precision is maintained while response time is dramatically reduced for real-time decision-making.
Solution Approach 2:
The system implements real-time feedback loops where production data is continuously monitored, analyzed, and displayed with immediate visual indicators of performance deviations. Pass-fail monitors and trend comparisons provide instant feedback on whether production metrics are meeting targets, enabling operators to make timely adjustments without waiting for lengthy analysis processes.
3Loss of information
If detailed production metrics are tracked, then production performance understanding is improved, but operational complexity increases requiring years of experience to interpret
Solution Approach 1:
The system uses color-coded visual indicators to represent production status and performance levels. Pass-fail monitors display green for meeting targets, yellow for warnings, and red for failures. Trend lines use color variations to indicate improvement or deterioration. This color-coding system transforms complex detailed metrics into immediately interpretable visual signals, maintaining full information quality while dramatically improving ease of operation and reducing the experience required to interpret data.
Solution Approach 2:
Different sections of the interface display data with different levels of detail and visualization styles appropriate to their purpose. Summary dashboards show high-level KPIs with simple visualizations, while detailed views provide comprehensive metrics for deep analysis. This local quality approach ensures that each part of the interface provides the appropriate level of detail for its function, making the system easy to operate for routine monitoring while still providing deep insights when needed.
Data Source
AI summary
A production system includes a processor, a non-transitory computer readable medium including computer program code instructions, and a user interface. The user interface and the processor, under control of the computer program code are configured to visually display at least a first graphical representation of a first work measure attribute and a second graphical representation of a second related work measure attribute for a production operation over a time range, and visually display a variance between trends of the at least first and second graphical representations of the first and second work measure attributes over the time range.