Pallet Location Planning Using Predicted Storage Duration

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Solution Overview

Problem

Warehouses face inefficiencies in labor costs and space utilization due to inefficient pallet storage planning, leading to increased travel distances and time for forklifts, which can cause bottlenecks in processes like receipt, picking, and packing.

Innovation Solution

A computer-based system predicts pallet storage durations using machine learning algorithms and optimizes pallet locations in warehouse racks by associating storage durations with specific sections based on proximity to the delivery area and pallet dimensions, minimizing travel distances and maximizing space utilization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If pallets are stored in locations closer to the delivery area to reduce travel distance, then labor costs and travel time are reduced, but warehouse space utilization decreases because long-term storage pallets occupy prime locations

Engineering Contradiction:

Improvetravel timeVSAvoidspace utilization

Core Design Contradiction:

Loss of timeVSProductivity

Solution Approach 1:

The system performs preliminary action by predicting the storage duration of incoming pallets before they are stored. Using machine learning algorithms that analyze historical data, product types, and seasonal factors, the system determines in advance how long each pallet will remain in storage. This prediction enables the optimization of storage location assignment before the pallet is physically placed, ensuring that space is allocated efficiently based on anticipated needs rather than arbitrary or manual decisions.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system applies parameter changes by dynamically adjusting storage location assignments based on multiple variables including predicted storage duration, pallet dimensions, rack availability, and proximity to delivery areas. The optimization algorithm continuously evaluates and reassigns parameters such as storage section, rack opening height, and horizontal position to achieve the best balance between minimizing travel distance and maximizing space utilization, rather than using fixed storage rules.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If pallets are stored in locations farther from the delivery area to maximize space utilization, then warehouse space is optimized, but labor costs and travel time increase

Engineering Contradiction:

Improvespace utilizationVSAvoidtravel time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Inventive Principle:

Principle #35Parameter changes

3Ease of operation

If fixed storage location rules are used for all pallets, then space utilization is simplified, but efficiency decreases due to increased travel distances

Engineering Contradiction:

Improvestorage management simplicityVSAvoidoperational efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system applies dynamics by transitioning from static, fixed storage location rules to a dynamic optimization approach. The storage location assignment is no longer predetermined by simple rules but is continuously adjusted based on real-time factors including predicted storage duration, current rack availability, pallet dimensions, and delivery area proximity. The system can adapt its storage strategy as conditions change, making the warehouse operation more responsive and efficient while maintaining ease of use through automated decision-making.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Inventive Principle:

Principle #35Parameter changes

4Adaptability or versatility

If manual pallet location planning is used, then flexibility is maintained, but labor costs increase due to intensive planning requirements

Engineering Contradiction:

Improveplanning flexibilityVSAvoidlabor cost

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system applies self-service by enabling the warehouse management system to automatically perform pallet location planning without requiring manual intervention. The machine learning model autonomously predicts storage durations, and the optimization algorithm independently determines optimal storage locations by evaluating multiple factors including rack availability, pallet characteristics, and delivery area proximity. This automated self-service approach maintains flexibility and adaptability while eliminating the labor-intensive planning process, significantly reducing labor costs.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system applies mechanics substitution by replacing the manual mechanical process of warehouse planning with an automated computational system. Instead of workers manually analyzing pallet requirements and determining storage locations, machine learning algorithms and optimization software perform these functions automatically. This substitution of human mechanical planning with automated intelligent systems maintains the necessary flexibility and adaptability while dramatically reducing the time and labor costs associated with manual planning.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentEP4062342B1Optimizing pallet location in a warehouse

Publication Date: 2025.12.31 LINEAGE LOGISTICS LLC

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AI summary

A computer-based system (100) is provided to optimize a warehouse space (102) with racks (106). The system determines (step D) a storage duration of a pallet (114) in the warehouse (102), and further determines (step E) an optimal storage location (108) for the pallet (114) in the warehouse (102) based on the excepted duration of storage and the height of the pallet (114). Such an optimal pallet storage area is selected to reduce labor costs in transporting the pallet in, within, and out of the warehouse and further optimize the management of multiple pallets in the warehouse as a whole.