Abstract
The paper dwells upon an approach to classifying fish processing machinery by means of cluster analysis. The classification presented herein helps optimize equipment upgrades and troubleshooting. The goal hereof is to analyze the fish processing machinery present in the market by means of cluster analysis. The paper covers fish dressing machines present in the fish processing market. The research methods include hierarchical cluster analysis, Euclidean distance, intergroup relations, and comparative analysis. SPSS is used to run calculations. The research has produced fish processing machinery clusters distinguished by performance, processable raw materials, and engine power; the research team has also tested a method for multidimensional classification for fish processing machinery analysis. These results are of use in a broad range of production tasks; they will be of interest for fish processing market analysts and machinery designers. Multidimensional classifications can be applied to arrange the production process, including selecting the most optimal equipment from a list of similar units.
Export citation and abstract BibTeX RIS
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.