Faculty Advisor

Sarkis, Joseph

Faculty Advisor

Putnam, Craig B.

Faculty Advisor

Miller, Bradley A.

Faculty Advisor

Powell, Adam Clayton

Abstract

The Scalable Sort Automation MQP evaluates the effectiveness of a system level design for an automated sortation system that is scalable to high class count and high volume. Subsystems underwent low level design, prototyping, and evaluation of criteria such as cycle time, cost, and volume. The system architecture couples traditional sorting techniques such as linear grating and serialization with novel machine learning technology. The LEGO catalog is used as a base case in testing the subsystems, the catalog carries a high-class count of close to 70,000 with many of the classes being distinct in size, shape, weight and other mechanical properties and features. The system is then evaluated in an economic model centered around conducting LEGO aftermarket sales through bricklink.com.

Publisher

Worcester Polytechnic Institute

Date Accepted

2020-05-18

Major

Interdisciplinary

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

Business

Advisor Department

Computer Science

Advisor Department

Mechanical Engineering

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