Optical Package Dimensioning With Real-Time Worker Productivity Feedback
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Solution Overview
Problem
In material handling environments, manual dimensioning of packages is prone to errors, especially with irregular shapes, leading to financial losses due to incorrect dimensioning and inefficient resource management.
Innovation Solution
A system that provides real-time productivity information to workers by accessing order-level data, dimensional data from range images, and worker operation data to compute productivity metrics and provide actionable insights for improving positioning and handling of packages, using a dimensioning system with a pattern projecting unit and range imaging unit to capture accurate dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual dimensioning is used, then operational flexibility is maintained, but measurement precision deteriorates due to human error
Solution Approach 1:
The patent replaces manual mechanical measurement systems with an automated optical dimensioning system that uses cameras and image processing algorithms to capture and analyze package dimensions, eliminating human error while maintaining workflow flexibility through automatic integration
Solution Approach 2:
The dimensioning system performs self-measurement by automatically capturing images of packages and computing dimensional data without requiring worker intervention, with the system independently processing measurements and providing results back to the workflow
2Measurement precision
If automated dimensioning systems are implemented, then measurement precision improves, but device complexity increases
Solution Approach 1:
The dimensioning system is designed as a multi-functional integrated unit that combines image capture, dimension computation, worker identification, productivity tracking, and feedback provision into a single system, reducing overall complexity by eliminating the need for separate manual processes and multiple independent systems
Solution Approach 2:
The patent introduces a computing device that acts as an intermediary between the camera system and the material handling workflow, processing images and dimensional data while interfacing with existing warehouse management systems, thereby simplifying integration without sacrificing measurement precision
3Productivity
If real-time productivity monitoring is implemented, then productivity is improved through feedback, but loss of information increases due to data processing requirements
Solution Approach 1:
The system implements real-time feedback by continuously monitoring worker productivity metrics through automated dimensioning and providing immediate performance information to workers and managers, enabling continuous improvement while efficiently processing data through integrated computing resources
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances accuracy in dimensioning, reduces errors, and improves operational efficiency by providing real-time feedback and instructions to workers, leading to better resource management and cost optimization in material handling environments.
Implementation Method 1
a pattern projecting unit configured to project a light pattern on an item placed in a field of view of the dimensioning system; a range imaging unit configured to capture one or more range images of the item on detecting a light pattern which is reflected from the item
Data Source
AI summary
Various embodiments described herein relates to techniques for providing real-time productivity information to a worker in a material handling environment. In this regard, for computing a productivity metric of the worker, a productivity metrics system may access various types of data. In this aspect, the productivity metric system may receive: order level data associated with multiple items identified for shipping; worker operation data associated with the workers and at least one workflow being operated by the workers; and dimensional data of the items being handled by the workers. The productivity metric system may compute the productivity metrics of the worker based on: the order level data, the dimensional data, the worker operation data, and a count of items handled by the worker. Further, the productivity metrics system may provide notifications including actionable insights indicative of actions to be performed by the worker.