Purpose
Practically all salmon fillets produced in Norway are trimmed clean of unwanted fat, bone remnants and other defects according to customer requirements. In today’s modern salmon-processing plants, the trimming operation is performed by a combination of automated trimming machines and manual post-trimming. Manual post-trimming is necessary due to the inability of current trimming machines to obtain satisfactory trimming. The purpose of this paper is to describe the work done so far toward a robotic post-trimming of salmon fillets.
Design/methodology/approach
A prototype concept system was developed to explore the possibility of robotic post-trimming. The concept is based on 3D machine vision, a high-speed robot manipulator and a flexible light-weight cutting knife.
Findings
The developed prototype demonstrated the feasibility of detecting a pre-defined object to be trimmed in 3D, and performing the specified trimming cut along a 3D cutting trajectory.
Research limitations/implications
The developed prototype system was built and integrated – focusing so far only on a single trimming operation: the tail cut.
Originality/value
The originality in the paper is the description of a prototype integrated system, focused on robotic post-trimming of salmon fillets. The value is in providing a starting point for further development toward a complete robotic post-trimming of salmon fillets.
ABSTRACT:19 Among the rest raw material in herring (Clupea harengus) fractions, produced during the 20 filleting process of herring, there are high value products such as roe and milt. As of today there 21 has been little or no major effort to process these by-products in an acceptable state, except 22 for by manual separation and mostly mixed into low-value products. Even though pure roe and 23 milt fractions can be sold for as much as ten times the value of the mixed fractions, the 24 separation costs using manual techniques render this economically unsustainable. Automating 25 this separation process could potentially give the pelagic fish industry better raw material 26 utilization and a substantial additional income. In this paper, a robust classification approach is 27 described which enables separation of these by-products based on their distinct reflectance
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