Enhancing Garri Production Quality: Implementing Six Sigma and Statistical Process Control in Imo State's Agro-Processing Hubs for Defect Reduction and Export Enhancement

Abstract

Garri, a staple cassava derived product in West Africa, faces significant quality challenges in traditional processing methods prevalent in Imo State's agro-processing hubs, limiting its export potential. This study investigates the application of Six Sigma methodologies, including the Define-Measure-Analyze-Improve-Control (DMAIC) framework and statistical process control (SPC), to reduce defects and enhance consistency in garri production. Employing a mixed-methods case study design, data were collected from five small scale factories through process observations, microbial analyses, and interviews with 25 personnel. Baseline assessments revealed a 28.4% defect rate (sigma level 2.3), primarily from inconsistent fermentation, poor hygiene, and variable roasting. Root cause analysis identified key contributors, leading to pilot interventions such as standardized protocols and mechanization, which reduced defects to 8.2% (sigma level 3.8), lowered costs by 15%, and improved yields to 82%. These enhancements align garri with international standards, fostering export opportunities in a $3.65 billion global market. The findings highlight Six Sigma's efficacy in optimizing agro-industries, recommending policy support for training and mechanization to promote sustainable development in Nigeria's rural economies.

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