Methodological Evaluation of Industrial Machinery Fleets Systems in South Africa:Randomized Field Trial for Risk Reduction Assessment

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Main Authors: Dlamini, Nomonde, Mthombeni, Sibusiso, Khumalo, Nokuthula, Tembo, Mamello
Format: Recurso digital
Language:English
Published: Zenodo 2004
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_version_ 1866902059116134400
author Dlamini, Nomonde
Mthombeni, Sibusiso
Khumalo, Nokuthula
Tembo, Mamello
author_facet Dlamini, Nomonde
Mthombeni, Sibusiso
Khumalo, Nokuthula
Tembo, Mamello
contents <p>Industrial machinery fleets play a critical role in South Africa's manufacturing sector, yet their operational efficiency and risk management are areas of ongoing concern. A randomized field trial was conducted, with data collected from 50 randomly selected machinery fleets over a six-month period. Key performance indicators (KPIs) were monitored to assess fleet efficiency and safety measures. The analysis revealed that implementing predictive maintenance models led to a reduction in unplanned downtime by an average of 20% across the tested fleets, indicating significant improvements in operational reliability. The findings suggest that the integration of advanced analytics and predictive maintenance can substantially enhance the efficiency and safety of industrial machinery fleets in South Africa. Based on the trial results, it is recommended that manufacturers adopt a combination of preventive and predictive maintenance strategies to mitigate risks associated with their fleet systems. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18793889
institution Zenodo
language eng
publishDate 2004
publisher Zenodo
record_format zenodo
spellingShingle Methodological Evaluation of Industrial Machinery Fleets Systems in South Africa:Randomized Field Trial for Risk Reduction Assessment
Dlamini, Nomonde
Mthombeni, Sibusiso
Khumalo, Nokuthula
Tembo, Mamello
Sub-Saharan
Fleet Management
Randomization
Risk Assessment
Supply Chain Optimization
Maintenance Strategies
Statistical Analysis
<p>Industrial machinery fleets play a critical role in South Africa's manufacturing sector, yet their operational efficiency and risk management are areas of ongoing concern. A randomized field trial was conducted, with data collected from 50 randomly selected machinery fleets over a six-month period. Key performance indicators (KPIs) were monitored to assess fleet efficiency and safety measures. The analysis revealed that implementing predictive maintenance models led to a reduction in unplanned downtime by an average of 20% across the tested fleets, indicating significant improvements in operational reliability. The findings suggest that the integration of advanced analytics and predictive maintenance can substantially enhance the efficiency and safety of industrial machinery fleets in South Africa. Based on the trial results, it is recommended that manufacturers adopt a combination of preventive and predictive maintenance strategies to mitigate risks associated with their fleet systems. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.</p>
title Methodological Evaluation of Industrial Machinery Fleets Systems in South Africa:Randomized Field Trial for Risk Reduction Assessment
topic Sub-Saharan
Fleet Management
Randomization
Risk Assessment
Supply Chain Optimization
Maintenance Strategies
Statistical Analysis
url https://doi.org/10.5281/zenodo.18793889