Randomised Field Trial of Process-Control System Diagnostics for Yield Optimisation in Tanzanian Manufacturing

"background": "Manufacturing in developing economies faces persistent challenges in production efficiency and resource utilisation. Process-control diagnostics, while established in industrialised nations, lack rigorous field evidence of their impact on yield within the specific infrastructural and operational contexts of sub-Saharan Africa. ", "purpose and objectives": "This study aimed to conduct a methodologically robust evaluation of a structured process-control system diagnostic intervention. The primary objective was to quantify its causal effect on production yield within a randomised field trial setting in a Tanzanian manufacturing sector. ", "methodology": "A randomised controlled field trial was implemented across multiple production sites. Sites were randomly assigned to a treatment group receiving the diagnostic intervention or a control group continuing standard practice. Yield was measured as the mass ratio of finished product to raw material input. The impact was estimated using a linear mixed-effects model: Y{it = \0 + \1 Treatmenti + \ Xit + \ +, where \ denotes site random effects. Robust standard errors were clustered at the site level. ", "findings": "The diagnostic intervention led to a statistically significant mean yield increase of 7. 3 percentage points (95% CI: 4. 1 to 10. 5; p < 0. 01) compared to the control group. Analysis identified specific bottlenecks in calibration and maintenance scheduling as the primary mechanisms for this improvement. ", "conclusion": "The application of a structured process-control diagnostic system effectively enhanced manufacturing yield in this context. The results provide causal evidence that systematic engineering diagnostics can translate into substantial material efficiency gains even where advanced automation is limited. ", "recommendations": "Manufacturing firms should integrate structured diagnostic protocols into routine operational management. Policymakers and industry associations are advised to support the development of local technical capacity for implementing and sustaining such engineering-led process optimisation. ", "key words": "process control, manufacturing, field experiment, yield optimisation, industrial engineering, Sub-Saharan Africa", "contribution statement": "