Optimization of aluminium sheet production in a distressed economy
| dc.contributor.author | Nnabude, Michael | |
| dc.date.accessioned | 2026-03-25T12:03:53Z | |
| dc.date.available | 2026-03-25T12:03:53Z | |
| dc.date.issued | 2024-10 | |
| dc.description | This thesis is for the award of Master of Engineering (M.ENG.) in Industrial Production Engineering | |
| dc.description.abstract | This research deals with the optimization of aluminum sheet production in a distressed economy. The aluminum roofing sheet industry plays a pivotal role in the construction sector due to the inherent advantages of aluminum roofing sheets including corrosion resistance, lightweight properties and recyclability. Operational inefficiency results in higher production costs and operational delays. The methods applied in this study includes data collection through questionnaires and the company record books. Data analysis using Excel and Python were used to identify trends and pattern in machine failure and this helped in understanding the factors contributing to decline in productivity. Strategic maintenance initiative including Lean manufacturing tools like Heijunka and Takt Time were used to facilitate increase in production while application of predictive maintenance through regression model were used to reduced average machine downtime thereby increasing the operational efficiency. From the result obtained, the Analysis of production data from 2017 to 2021 shows operational inefficiencies and external disruptions, such as machine downtime and pandemic-related constraints, which collectively contributed to a 28.8% decline in total production and a 20% reduction in production targets over the period. The application of predictive maintenance through regression models demonstrated a substantial improvement in operational efficiency, notably reducing average machine downtime by 55.3% from 1,316.67 hours in 2021 to 588.34 hours in 2023. In addition, strategic maintenance initiatives, including lean manufacturing tools like Heijunka and Takt Time, facilitated a 56.2% increase in total production from 3,170 tons to 4,950 tons between 2017-2021 and 2022-2023 periods, respectively. This enhancement not only optimized production schedules but also aligned production rates more closely with market demand, resulting in a 30.4% improvement in net revenue generation after expenses. Cost management strategies further stabilized machine maintenance costs around the benchmark figure of ₦6,000,000 in 2022-2023, showcasing effective financial control amid economic uncertainties. | |
| dc.identifier.citation | Nnabude, M. (2024). Optimization of aluminium sheet production in a distressed economy [Unpublished Master's Thesis]. Federal University of Technology, Owerri, Nigeria | |
| dc.identifier.uri | https://repository.futo.edu.ng/handle/20.500.14562/2481 | |
| dc.language.iso | en | |
| dc.publisher | Federal University of Technology, Owerri | |
| dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.subject | Distress economy | |
| dc.subject | regression model | |
| dc.subject | lean manufacturing | |
| dc.subject | productivity | |
| dc.subject | optimization | |
| dc.subject | Department of Mechanical Engineering | |
| dc.title | Optimization of aluminium sheet production in a distressed economy | |
| dc.type | Master’s Thesis |