Shift Generation System with Predictive Condition Evaluation

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Solution Overview

Problem

The existing automatic shift generation systems using genetic algorithms face complications due to the difficulty in setting and optimizing shift conditions, leading to trial and error processes that are time-consuming and inefficient.

Innovation Solution

A shift generation system that includes a hardware processor capable of accepting shift conditions and member information, generating shifts, evaluating the achievement state of shift conditions, predicting the effect of changes in shift conditions on the evaluation, and presenting these predictions to users.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If multiple shift conditions are set in automatic generation using genetic algorithm, then the shift generation can be automated, but the complexity of setting and optimizing conditions increases and trial and error becomes necessary

Engineering Contradiction:

Improveautomatic shift generationVSAvoidshift condition setting complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The system calculates an evaluation value that quantifies the degree to which shift conditions are satisfied by generated shifts. This feedback mechanism allows users to automatically adjust conditions based on quantitative results, eliminating trial and error. The evaluation value serves as a guide for optimizing shift conditions without manual testing.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent replaces manual trial and error optimization with an automated evaluation system. Instead of mechanically testing multiple condition sets manually, the system uses computational evaluation to automatically determine optimal conditions, substituting manual mechanical processes with automated computational analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Manufacturing precision

If shift conditions are strictly set, then the shift generation precision is improved, but the number of solutions decreases or evaluation value does not converge to 100%

Engineering Contradiction:

Improveshift condition satisfaction precisionVSAvoidnumber of valid shift solutions

Core Design Contradiction:

Manufacturing precisionVSQuantity of substance

Solution Approach 1:

The evaluation value provides continuous feedback on how well generated shifts satisfy the shift conditions. Users can adjust conditions based on this feedback to achieve 100% satisfaction while maintaining adequate solution quantity. The feedback loop enables precise optimization without blindly reducing solution space.

Inventive Principle:

Principle #23Feedback

3Manufacturing precision

If trial and error of changing shift conditions is performed, then the optimization of shift conditions is achieved, but the time consumption and complexity increase

Engineering Contradiction:

Improveshift condition optimizationVSAvoidtime for trial and error

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent replaces manual trial and error with an automated evaluation system that computationally determines optimal shift conditions. Instead of manually testing multiple condition sets and observing results, the system automatically calculates evaluation values and identifies optimal conditions, substituting time-consuming manual processes with rapid computational analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250029032A1Shift generation system, shift generation method, and non-transitory recording medium storing computer-readable shift generation program

Publication Date: 2025.01.23 KONICA MINOLTA INC

AI summary

A shift generation system includes a hardware processor that accepts a shift condition and member information, generates a shift for a member based on the shift condition and the member information, evaluates an achievement state of the shift condition for the generated shift, predicts an effect of a change in the shift condition on the evaluation, and presents the predicted effect.