BEF Raw Material Specification Optimization for Dynamic Procurement

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Solution Overview

Problem

The existing methods for procuring brightness enhancement film (BEF) raw materials are inefficient and unreliable, leading to unscientific procurement plans, high costs, and low utilization rates due to manual size optimization based on experience rather than systematic or dynamic optimization.

Innovation Solution

A dynamic optimization method and system using an integer programming model to optimize real-time order and inventory data, generating the most reasonable raw material specifications and procurement plans by deriving optimal raw material sizes and allocating them effectively.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual size optimization based on experience is used, then procurement decisions can be made quickly, but the optimization is inefficient and unreliable leading to high costs and low utilization rates

Engineering Contradiction:

Improveprocurement optimization efficiencyVSAvoidprocurement plan reliability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent replaces manual experience-based procurement optimization with an automated computer system that uses integer programming algorithms to calculate optimal raw material sizes and procurement plans, substituting human judgment with systematic mathematical optimization

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system dynamically adjusts raw material specification parameters based on real-time order data and inventory levels, transforming fixed experience-based specifications into flexible, data-driven parameters that optimize both cost and utilization rates

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If fixed procurement specifications are used, then procurement processes are simple, but they cannot adapt to fluctuations in order quantity leading to low utilization rates and diverse procurement specifications

Engineering Contradiction:

Improveprocurement plan adaptabilityVSAvoidoptimization system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements dynamic procurement specifications that automatically adjust based on real-time order quantity fluctuations and inventory levels, transforming static procurement plans into adaptive systems that respond to changing demand conditions

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The optimization system automatically generates procurement plans based on input order data and inventory information, enabling the system to self-adjust specifications without requiring manual intervention for each procurement decision

Inventive Principle:

Principle #25Self-service

3Loss of time

If real-time dynamic optimization is implemented, then procurement plans can be adjusted quickly, but the computational complexity increases requiring sophisticated optimization models

Engineering Contradiction:

Improveprocurement planning timeVSAvoidoptimization model complexity

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system pre-calculates optimal raw material sizes and procurement quantities based on forecasted order data and current inventory levels, enabling proactive procurement planning that reduces reactive decision-making time

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary computational layer that translates complex integer programming optimization into actionable procurement specifications, bridging the gap between mathematical models and practical procurement decisions

Inventive Principle:

Principle #24Intermediary (Mediator)

4Loss of energy

If raw material utilization rate is increased, then procurement costs decrease, but it requires systematic optimization approaches rather than manual methods

Engineering Contradiction:

Improveraw material utilization efficiencyVSAvoidprocurement process simplicity

Core Design Contradiction:

Loss of energyVSEase of manufacture

Solution Approach 1:

The patent replaces manual procurement processes with automated computer-based optimization systems that systematically maximize raw material utilization through integer programming, achieving higher efficiency despite increased system complexity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11694004B2Dynamic optimization method and system for procurement specifications of brightness enhancement film (BEF) raw materials

Publication Date: 2023.07.04 GUANGDONG UNIV OF TECH

AI summary

A dynamic optimization method for procurement specifications of BEF raw materials includes: obtaining finished product data; obtaining an initial feasible raw material size set; mapping the initial feasible raw material size set in length and width directions to obtain a complete feasible raw material size set; filtering an unreasonable raw material size out of the complete feasible raw material size set to obtain a final feasible raw material size set; and determining whether a scale of the final feasible raw material size set is larger than a threshold, if not, building and solving an integer programming model, and outputting results; and if yes, batchwise processing the final feasible raw material size set to obtain multiple subsets, and building an integer programming model for each subset, and solving the integer programming model, and outputting results. A dynamic optimization system of BEF is further provided.