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THE HIDDEN PROBLEM
BIG SHRIMP GIVEAWAY

WE REGRADED 500,000 LBS OF HLSO FROM TOP PROCESSORS FROM ECUADOR, INDIA, AND HONDURAS AND OBTAINED CONSERVATIVE SAVINGS OF $0.07 to $0.12/lb or $500K to $+1M ANNUALLY

CASE STUDY 

WHAT IS YOUR BIGGEST CHALLENGE RELATED TO GRADING?

INACCURATE MECHANICAL GRADING IS A LARGE, BUT HIDDEN EXPENSE.

There is always an initial belief among shrimp processors that there is very little room for improvement in their current grading operation, critical to the shrimp industry. 

 

When we ask shrimp processors the main problems with their current roller grader operation, we get many different answers. Still, we've rarely heard of processors talking of one of the biggest and most expensive problems. 

BIG SHRIMP GIVEAWAY: Putting Large Shrimp in a lot and getting small shrimp money for them!   When large shrimp are mis-graded into lower-priced categories, their selling price is reduced. This problem quietly costs even the most efficient Shrimp processors thousands of dollars each day. 

 

$$        $$$

Rollers graders don't have the visibility nor precision to define the weight limits for each bin the way the SMART Sorter is capable of. This fundamental limitation is something that even the best operators can’t improve.

 

METHODOLOGY

We've seen from our current SMART SORTER customers the huge economic and processing benefits they get from the new system, the reason why many of our customers have more than one grading unit. But we wanted to put our system to the test in this below-referenced Case Study.  

Approximately 500,000 lbs. of shrimp from 10 companies and 113 lots were used in this analysis to compare the financial benefit of grading with a Roller Grader versus a Smart Sorter. Urner Barry prices for the date of the first run of completed containers were used to calculate revenue. In addition, a simulation using average annual prices across five years, from 2015-2020, was utilized to understand performance through time and varying prices.

THE RESULTS

  • We obtained a tighter UR and improved the size distribution of the product from every single supplier.    

  • The SMART Sorter precisely targeted the smallest count within a grade avoiding selling big shrimp as smaller counts.  

  • Improvements range from $0.07 to $0.12 per pound.

  • We improved the consistency of the product. 

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CONSERVATIVE SAVINGS OF $0.02 to $.12/lb THAT TRANSLATE INTO 500K TO $+1M ANNUALLY. 

EVEN WHEN TESTING WITH LOW-AVERAGE YEARLY PRICES

 

PROVEN & SIMPLE BENEFITS

  • Improve your ability to precisely target the smallest count with tighter UR, within a grade all while reducing labor, QC and streamlining the process and increasing visibility in your factory throughput. 

In every single case, we saw the same problem: Big Shrimp Giveaway, putting larger shrimp in a lot, and getting small shrimp money for them.

Using prices at run time, the Smart Sorter shows an overall improvement of $.08/lb graded while the improvements range from $.07 to $0.12 by company.  

We obtained greater profits per pound even when we tested our data with the last six years of low-average yearly prices all while reducing labor, QC, and streamlining the process. 

With this Business Case, we have yet another test that shows that the Smart Sorter will generate a higher revenue than the Roller Grader each year even if Urner Barry prices drop, such as in 2020.

The SMART Sorter is quickly uncovering huge economic and processing benefits to the Shrimp Industry. 

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Simulation of the revenue generated by both machines across five years using the annual prices from Urner Barry. It is clear that the Smart Sorter will generate a higher revenue than the Roller Grader in each year even if Urner Barry prices drop, such as in 2020.

GET IN TOUCH 

VISIT US OR SEND US YOUR PRODUCT TO SEE IT FOR YOURSELF. 

Visit our testing facility in New Orleans Louisiana to see it for yourself.
Send us some of your product and we will test it on the SMART Sorter for you or demonstrate the test live.
©Laitram Machinery
220 Laitram Lane, Harahan, LA70123, USA.