EEI Selection System with Relative Filtering
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Solution Overview
Problem
Existing web applications lack the ability to automatically determine and display compatible Electrical Equipment Infrastructure (EEI) items to users in a helpful manner, often failing to provide sufficient filtering and sorting criteria, which can lead to inefficient selection of EEI due to compatibility issues and suboptimal power supply matching.
Innovation Solution
A configuration tool that allows users to enter relative and hard selection criteria, including target values and preferences, to filter and sort EEI items based on compatibility and closeness to target values, with automatic filtering of incompatible items and prioritization of preferred features, using a combination of relative and soft weights for sorting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system displays all available EEI items to users, then users have access to complete information, but users cannot easily identify compatible items and optimal matches
Solution Approach 1:
The system performs preliminary filtering and compatibility checking before presenting EEI items to users. By pre-processing the EEI database to identify compatible items based on selected equipment, the system eliminates the need for users to manually check compatibility, thus reducing information loss while maintaining ease of operation.
Solution Approach 2:
The system provides feedback to users by highlighting compatible items and indicating compatibility status. This feedback mechanism helps users quickly understand which items work together without overwhelming them with all available options, effectively addressing both information completeness and operational simplicity.
2Ease of operation
If the system provides basic filtering options, then the interface remains simple, but users cannot apply sufficient criteria to find optimal EEI combinations
Solution Approach 1:
The filtering interface dynamically adapts based on user selections and requirements. As users select EEI items, the system automatically adjusts available filter options and applies relevant criteria, allowing the interface to remain simple while providing sophisticated filtering capabilities when needed.
Solution Approach 2:
The filtering system serves multiple functions: it filters by basic criteria, checks compatibility, ranks items by optimality, and provides recommendations. This multi-functional approach allows a single interface to handle both simple browsing and complex selection tasks without increasing apparent complexity for the user.
3Reliability
If users manually check compatibility of each EEI item, then selection accuracy improves, but time consumption increases significantly
Solution Approach 1:
The system performs compatibility checking automatically without requiring user intervention. The EEI database self-validated compatibility relationships are pre-computed and automatically applied when users make selections, ensuring accurate compatibility verification while eliminating the time users would spend manually checking each item.
Solution Approach 2:
Compatibility relationships are pre-calculated and stored in the system before users begin their configuration task. This preliminary processing ensures that when users select items, compatibility is instantly verified, maintaining high selection accuracy while minimizing the time users spend on compatibility checks.
4Reliability
If the system recommends high-capacity power supplies for all servers, then compatibility is ensured, but efficiency decreases due to oversized power supplies
Solution Approach 1:
The system applies different power supply capacity recommendations based on the specific server's requirements rather than using a one-size-fits-all approach. By analyzing each server's actual power consumption characteristics and matching them with appropriately sized power supplies, the system ensures compatibility while optimizing energy efficiency for each local case.
Solution Approach 2:
The system dynamically adjusts power supply capacity recommendations based on varying server specifications and workloads. By changing the recommended power supply parameters to match actual needs rather than always recommending high-capacity units, the system maintains compatibility assurance while improving overall power efficiency and reducing energy waste.
Data Source
AI summary
Techniques are described for a computing device to receive from a user, a selection of EEI drawn from a list of EEI. A method includes (a) receiving a relative selection criterion from the user, the relative selection criterion including a target value for a first feature of the EEI and a direction of comparison; (b) filtering out, from the list, EEI having values for the first feature that are outside the direction of comparison from the target value; (c) sorting remaining EEI from the list based on closeness of the first feature to the target value, yielding a sorted order; (d) displaying the remaining EEI in the sorted order on a display screen; and (e) receiving a selection of EEI from the displayed EEI from the user via a user interface device. A system, apparatus, and computer program product for performing this method and similar methods are also described.