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Now showing 1 - 5 of 9

Recent Submissions

Taguchi full factorial design of experiments optimisation of cutting parameters for energy efficiency and surface roughness during the dry turning of EN19 material
(2024-05-30) Tayisepi, Nicholas; Mnkandla, Albert Nkulumo; Tigere, Godfrey; Gwatidzo, Oscar; Mutenhabundo, Winnie; Ndala, Emmanuel; Wagoneka, Lovelace Makakatanwa
During metal machining, the satisfactoriness of cost-quality-time matrix convergence effectively depends on the supreme selection of cutting parameters. This study investigated the energy use minimisation and quality surface generation through optimised cutting parameters application, as sustainability enhancement during dry turning of EN19 material. Cutting parameter optimisation is a serious challenge confronting the machining industry as they strive to achieve low energy use and better component quality generation from their operations. The utility material, EN19, is a medium-carbon low alloy steel which typically gets applied in the manufacturing of multiple profiled cylindrical machine tool, rail locomotives and motor vehicle component parts, inter alia. Taguchi Full Factorial experimental plan was used to organize the empirical experiments. ANOVA and the main effects plot signal-to-noise ratio optimisation analysis were utilised in the study to establish the influence of process parameters on the response parameters—surface roughness and energy use. The aim was to investigate and determine the correlation of the machining strategy parameters with the outcome of low energy use and quality surface texture of the components as the cutting parameters were varied, and optimised for minimum surface roughness and energy use. Results of the extensive experimental study, produced optimum cutting speed, rake angle variation and feed rate which respectively influence the response parameters positively for energy use minimisation and improved surface quality. Validation experiments confirmed model findings.
Experimental investigation and simultaneous optimisation of honing parameters of dry cast iron cylinder relining sleeves of motor vehicle engine blocks for surface finish and energy use
(Pouyan Press, 2025-11-19) Tayisepi, Nicholas; Mugwagwa, Lameck; Mnkandla, Albert Nkulumo; Mapindu, Innocent; Muhla, Takudzwa McDonald
Machining based manufacturing industries consume significant amounts of electrical energy, to power the several modules constituting the machine tool, with low levels of efficiency. Honing operations, are vital machining manufacturing operations, utilised in the motor vehicles engine block cylinders internal surfaces super-finishing process, for improving many functional attributes of the machined cylinders. In an environment of diminished energy generation, bulk electrical energy users, like the machining industry, encounter many pressures to reduce consumption. Electrical energy consumption is a production driver of the ozone layer depleting carbon emissions, from the manufacturing sector. Governments’ environmental legislation directives, in collaboration with environmental protection lobbyist groups, added to the ever soaring energy market prices, all exert mounting pressure on the machining industries, such as engine block manufacturers and repairers. Thus, compelling them to consider reducing energy consumption from their operations processes as well as increasing the efficiency of their machining processes. Machining productivity improvement and operation efficiency are influenced by the selection and setting of cutting parameters, during practical operation. In this present experimental study, honing parameters were investigated and optimised with focus on energy use conservation and surface quality enhancement during the machining operation. The L16 experiments were planned using Minitab 19. The three cutting parameters investigated were varied at four levels each. The study results showed the optimum honing parameters combination conditions, respectively, determined for surface roughness, power and total machining energy. The study results confirms that significant Energy could be saved by optimising process parameters at the machining planning stage.
Maize grain forced-convection mechanical drying process optimization: a case of Concession depot of company X in Zimbabwe
(Wood & Paper Science Department at North Carolina State University, 2025-11-19) Tayisepi, Nicholas; Mhlanga, Samson; Zana, Alois; Alrasheedi, Nashmi H.; Louhichi, Borhen; Sahu, Santosh Kumar
Grain drying is a process that succeeds harvesting and is performed to sustainably maintain the properties of grain during the storage period. Elevated moisture content in grains shortens their shelf life, as it promotes bacterial growth. In this present research, the maize grain mechanical drying process parameters; drying air temperature (30 ºC, 60 ºC, and 110ºC), airflow rate (1.2 m/s, 1.5 m/s and 1.8 m/s), and drying time (30 min,120 min, and 180 min); were investigated and optimized as regards their effect on the on the dried grain quality and moisture reduction process to minimize the desiccating energy consumption. A full factorial design of experiment was planned, and optimization was carried out utilizing statistical tools, including analysis of variance and the main effects plot signal-to-noise ratio. Results revealed that the evaluated dehydration process parameters, air temperature, and air flow rate, significantly influenced the drying dynamics, whilst the time parameter displayed minimal impact on the process. The optimum drying process parameters were established to be 30 ºC drying temperature, 1.5 m/s airflow rate, and 120 min drying process run time. The percentage error margin between the predicted and confirmation experimental run results at the optimum parameter setting condition was less than 15%.
Multi-response optimisation of milling parameters of AISI D2 steel using response surface methodology and desirability function
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-09-13) Hernández, Luis W.; Ahmed, Yassmin Seid; Curra, Dagnier A.; Pérez, Roberto
This study investigates multi-objective optimization of end-milling parameters for AISI D2 cold-worked tool steel using GC1130-coated carbide inserts under wet machining, focusing on cutting speed and feed rate per tooth values beyond manufacturer recommendations. The objective was to identify parameter settings that minimize surface roughness while maximizing cutting tool life—two performance criteria that often conflict in practice. A full-factorial design of experiments was implemented, varying the cutting speed (220–310 m/min) and feed rate (0.06–0.25 mm/tooth). Response Surface Methodology (RSM) was used to develop predictive models, and a desirability function approach (DFA) was applied to perform multi-response optimization under three weighting schemes. The statistical models showed strong reliability, with R2 values of 81.09% for surface roughness and 95.02% for tool life. The optimal settings—220 m/min cutting speed and 0.25 mm/tooth feed—resulted in a tool life of 11.03 min and surface roughness of 0.587 μm. This yielded the highest desirability index (D = 0.8706) under tool-life-prioritized weighting, outperforming other cases by up to 10.69%. These findings offer a practical balance between quality and durability, especially for applications where tool wear is a limiting factor.
Goat marketing decisions by smallholder farmers in Bikita district of Zimbabwe
(Under Review, 2022-10) Sibanda, B.; Zivenge, E.; Munyati, V. T.; Musemwa, L.; Mafuse, N.; Musara, J. P.
Goats are an important source of livelihood for smallholder farmers domiciled in arid areas of Zimbabwe. Economic reforms such as liberalization of markets have opened up avenues for smallholder goat farmers to produce more diverse products and participate in high-end and rewarding markets. These markets include export and processing linked marketing channels. The main objective of the paper was to explore the factors affecting smallholder farmers’ involvement in goat marketing and the intensity of goat sales in Bikita district. A representative sample of 392 goat farmers was proportionately selected from 5 wards. The double hurdle model was used to evaluate market participation and market participation intensity decisions guided by the probit model and censored tobit model respectively. Results show that the decision to participate in goat marketing was exclusively influenced by experience in goat farming while intensity of goat marketing was exclusively influenced by household labour, access to other sources of information and the market prices. Age of household head, access to credit and affiliation to marketing associations influences both decisions. These include the The study recommends that, central government and private sector companies should encourage and support more farmers to affiliate into marketing associations. This is a key strategy that can be used to promote market information dissemination among goat value chain stakeholders. Formation of marketing hubs can also increase goat marketing participation thorough increased access to decentralised marketing points. Opening up credit lines can also ultimately result in farmers commercially producing goats as they increase their herds. Keywords: Double hurdle model, market participation, smallholder goat farmers, marketing associations