SBIR/STTR Research Award

STTR Phase II: Automation of the Crosscut Operation in a Wood Processing Mill

Award identifier ee77537186546d420bf2197fbb201cc4ac3768a6bb87977c4857eb97e88c4645Awarding agency National Science Foundation

Award amount

$0

Program and phase

STTR · Phase I

Award year

2003

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Barr-Mullin Inc.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research abstract

This Small Business Technology Transfer (STTR) Phase II project is to design and develop a fully automated system for crosscutting planks of lumber into parts with specific length and surface characteristic requirements. This system consists of a scanning device with four heads to scan the four surfaces of each incoming plank, a mathematical programming model and a software system to determine an optimal cutting pattern for each plank, and all necessary mechanisms to interface with (and to coordinate the operation of) various components of the manufacturing line. These components include the transport devices such as conveyor belts, the positioning devices, the saw mechanism, and the subsequent cut-piece sorter. Installation of an automated system would result in both higher speed and higher yields. The project will also extend the scope of this mathematical model, in combination with the models for the gang-rip saw operation, to create a combined system for ripping and crosscutting. The software system developed under this research grant will have an impact on the efficiency of the crosscut operation, by increasing both its speed and its yield. This in turn could lead to substantial reductions in the manufacturing cost as well as to significant savings in the overall consumption of wood, which is a scarce national resource. This project supports the educational development of one graduate student at NC State University.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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