Optimization of Aluminium Roofing Sheet Production in a Distressed Economy: A Case Study of a Manufacturing Company in Nigeria

Nnabude Michael, Uche Remy, Nwufo Olisaemeka Chidozie, Arukalam Okechi Innocent and Ekpechi Daniel Arinze
Additional contact information
Nnabude Michael: Department of Mechanical Engineering, Federal University of Technology, Owerri, Nigeria.
Uche Remy: Department of Mechanical Engineering, Federal University of Technology, Owerri, Nigeria.
Nwufo Olisaemeka Chidozie: Department of Mechanical Engineering, Federal University of Technology, Owerri, Nigeria.
Arukalam Okechi Innocent: Department of Polymer and Textile Engineering, Federal University of Technology, Owerri, Nigeria.
Ekpechi Daniel Arinze: Department of Mechanical Engineering, Federal University of Technology, Owerri, Nigeria.

Post-Print from HAL

Abstract: This study optimized an aluminum roofing sheet production company in a distressed economic environment characterized by persistent operational inefficiencies. Production and maintenance data, was obtained from the case study company records and structured questionnaires, and was analyzed using Excel and Python software. The regression-based predictive maintenance model and selected lean manufacturing tools were applied to improve operational performance. Analysis of production data from 2017 to 2021 revealed a 28.8% decline in total output and a 20% reduction in production targets, primarily due to machine downtime and external disruptions. Following the implementation of predictive maintenance, average machine downtime decreased by 55.3%, from 1,316.67 hours in 2021 to 588.34 hours in 2023. In addition, the adoption of lean tools such as Heijunka and Takt Time increased total production by 56.2%, rising from 3,170 tons (2017–2021) to 4,950 tons (2022–2023), and resulted in a 30.4% improvement in net revenue. Maintenance costs were also stabilized at approximately ₦6,000,000 during the 2022–2023 period. These findings demonstrate that the combined application of predictive maintenance and lean manufacturing techniques can significantly enhance productivity, cost efficiency, and operational resilience in manufacturing industries operating under economic constraints.

Date: 2026-01-23
References: Add references at CitEc
Citations:

Published in Journal of Global Economics, Management and Business Research, 2026, 18 (1), pp.207-230

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05475159

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().