Ecuador is a leading producer of white shrimp, Litopenaeus vannamei, exporting 1.069 million tons and generating $7 billion by 2022. However, challenges in the post-larval phase affect the sustainability and profitability of shrimp farming. In this study, we applied the Six Sigma DMAIC methodology to optimize the growth and survival rates of shrimp larvae. In the Define phase, biotic and abiotic variables influencing larval growth were identified. The Measure phase involved collecting data on shrimp weight and key environmental conditions, including pH, temperature, ammonia, sulfur percentage, and algal presence. Statistical analysis during the analysis phase revealed critical insights into the impact of these variables on growth rates. The proposed improvements in the improve phase included enhanced water quality management, optimized feeding strategies, and stress reduction measures. Control charts and multivariate analysis during the control phase ensured the sustainability of these improvements. This study demonstrates that applying Six Sigma methodologies can significantly enhance the productivity and profitability of shrimp farming by addressing critical growth and survival factors.

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A Six Sigma Approach to Enhancing the Production Performance of Pacific White Shrimp (Litopenaeus Vannamei): a Proposal for Optimizing Stocking Density and Acclimation Methods

  • Génesis Dayana Guevara Huacón,
  • Melissa Arlette Zambrano Peñafiel,
  • Hernán Lara-Padilla,
  • Tania Rojas

摘要

Ecuador is a leading producer of white shrimp, Litopenaeus vannamei, exporting 1.069 million tons and generating $7 billion by 2022. However, challenges in the post-larval phase affect the sustainability and profitability of shrimp farming. In this study, we applied the Six Sigma DMAIC methodology to optimize the growth and survival rates of shrimp larvae. In the Define phase, biotic and abiotic variables influencing larval growth were identified. The Measure phase involved collecting data on shrimp weight and key environmental conditions, including pH, temperature, ammonia, sulfur percentage, and algal presence. Statistical analysis during the analysis phase revealed critical insights into the impact of these variables on growth rates. The proposed improvements in the improve phase included enhanced water quality management, optimized feeding strategies, and stress reduction measures. Control charts and multivariate analysis during the control phase ensured the sustainability of these improvements. This study demonstrates that applying Six Sigma methodologies can significantly enhance the productivity and profitability of shrimp farming by addressing critical growth and survival factors.