ABSTRACT
This study involves development and
multiobjective analysis of an integrated milling and sieving machine for
Bambara flour production. This will improve hygiene and reduce excessive
drudgery and food loss in this sector thereby aiding mass production of quality
bambara flour at low cost. Its major components include: electric motor, flour and
chaff discharging chutes, turbo-pneumatic sieve and hammer mill. Performance of
this machine was empirically evaluated and quantified using response surface
design and models at two levels of factors while desirability optimization and
benefit cost methodologies constitute the optimization and investment analysis
techniques applied in this investigation. Performance analysis results revealed
Bambara grains’ moisture content, number and speed of cross beaters and paddles
as these machine process/operational parameters (factors) with significant
influence on its performance while throughput and extraction efficiency
constitutes its functional performance indicators (responses). The cross beater
and grains’ moisture content affect the particle size of the milled grain
directly while sieving (extraction) of the grain food/starch granules (flour)
from its fibre (chaff) depends on this particle size and paddle parameters. In
addition, the multi-response performance simulation of this machine predicted
12.05%, 6, 4, 1610rpm and 1038rpm as the grain moisture content, number of
cross beaters and paddles, cross beater and paddle speeds require for its
optimal operation with over 98% accuracy. The machine performs with throughput
and extraction efficiency of 117.8kg/h and 98.45% respectively at these optimal
factor settings. Experimental evaluation revealed 41.15kg/h and 84.18% as the
average throughput and extraction efficiency of semi-mechanized Bambara flour
processing system. Thus, the novel Bambara nut milling-sieving machine for
Bambara flour production reduced the food loss to chaffin this sector to 1.55%
against 15.82% associated with the widely used semi-mechanized system. It also
promotes hygiene in this sector because it eliminated human contact with the
milled grain during sieving. The cost-benefit analysis of this machine showed
that it is viable economically because of its positive capital recovery
potentials. The machine’s payback period of 1.5years is far less than its
useful life of lOyears, while its 46.89% accounting rate of return outweighed
Nigerian banks maximum fixed deposits return of 17% and prime lending rate of
29%. Therefore, general adoption of the integrated milling and sieving machine
developed in this study is recommended for Bambara flour processing
-- (2026). Development And Parametric Analysis Of Bambara Flour Processing Machine Using Response Surface Methodology:- Ikeciiukwu, Ijeoma F. Mouau.afribary.org: Retrieved Apr 23, 2026, from https://repository.mouau.edu.ng/work/view/development-and-parametric-analysis-of-bambara-flour-processing-machine-using-response-surface-methodology-ikeciiukwu-ijeoma-f-7-2
--. "Development And Parametric Analysis Of Bambara Flour Processing Machine Using Response Surface Methodology:- Ikeciiukwu, Ijeoma F" Mouau.afribary.org. Mouau.afribary.org, 22 Apr. 2026, https://repository.mouau.edu.ng/work/view/development-and-parametric-analysis-of-bambara-flour-processing-machine-using-response-surface-methodology-ikeciiukwu-ijeoma-f-7-2. Accessed 23 Apr. 2026.
--. "Development And Parametric Analysis Of Bambara Flour Processing Machine Using Response Surface Methodology:- Ikeciiukwu, Ijeoma F". Mouau.afribary.org, Mouau.afribary.org, 22 Apr. 2026. Web. 23 Apr. 2026. < https://repository.mouau.edu.ng/work/view/development-and-parametric-analysis-of-bambara-flour-processing-machine-using-response-surface-methodology-ikeciiukwu-ijeoma-f-7-2 >.
--. "Development And Parametric Analysis Of Bambara Flour Processing Machine Using Response Surface Methodology:- Ikeciiukwu, Ijeoma F" Mouau.afribary.org (2026). Accessed 23 Apr. 2026. https://repository.mouau.edu.ng/work/view/development-and-parametric-analysis-of-bambara-flour-processing-machine-using-response-surface-methodology-ikeciiukwu-ijeoma-f-7-2