Methodological Evaluation and Panel-Data Estimation for Risk Reduction in Tanzanian Industrial Machinery Fleets
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| Format: | Recurso digital |
| Language: | English |
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2020
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| _version_ | 1866901975407263744 |
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| author | Kavishe, Neema Mwakyembe, Abasi Mfinanga, Juma |
| author_facet | Kavishe, Neema Mwakyembe, Abasi Mfinanga, Juma |
| contents | <p>Industrial machinery fleets in developing economies face significant operational risks, yet systematic, data-driven methodologies for quantifying and mitigating these risks are scarce. Existing approaches often rely on cross-sectional data, failing to capture temporal dynamics and unobserved heterogeneity within fleets. This paper aims to develop and evaluate a methodological framework for the empirical analysis of machinery fleet risk. The primary objective is to apply panel-data econometric techniques to measure the effectiveness of targeted maintenance interventions on risk reduction. A longitudinal dataset was constructed from maintenance logs, incident reports, and operational records for a fleet of heavy industrial equipment. A two-way fixed effects model was employed to control for time-invariant machine-specific factors and common temporal shocks. The core specification is $Risk_{it} = \alpha_i + \lambda_t + \beta Intervention_{it} + \gamma X_{it} + \epsilon_{it}$, where robust standard errors were clustered at the machine level. The implementation of structured preventative maintenance protocols was associated with a statistically significant 18.2% reduction in major incident risk (95% CI: 12.5% to 23.9%). Unobserved machine heterogeneity accounted for a substantial portion of the variance in baseline risk profiles. Panel-data estimation provides a robust methodological advance for isolating the causal effect of risk-reduction strategies in industrial settings, moving beyond descriptive correlation. Fleet managers should adopt panel-data frameworks for continuous safety performance evaluation. Investment in digitised, time-consistent record-keeping is essential to enable such analyses. reliability engineering, maintenance optimisation, fixed effects model, industrial safety, asset management This paper presents a novel application of econometric panel-data methods to engineering asset management, demonstrating a rigorous approach to quantifying the efficacy of safety interventions in an industrial context.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18970994 |
| institution | Zenodo |
| language | eng |
| publishDate | 2020 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Methodological Evaluation and Panel-Data Estimation for Risk Reduction in Tanzanian Industrial Machinery Fleets Kavishe, Neema Mwakyembe, Abasi Mfinanga, Juma Panel-data estimation Risk reduction Industrial machinery fleets Sub-Saharan Africa Developing economies Maintenance engineering Operational safety <p>Industrial machinery fleets in developing economies face significant operational risks, yet systematic, data-driven methodologies for quantifying and mitigating these risks are scarce. Existing approaches often rely on cross-sectional data, failing to capture temporal dynamics and unobserved heterogeneity within fleets. This paper aims to develop and evaluate a methodological framework for the empirical analysis of machinery fleet risk. The primary objective is to apply panel-data econometric techniques to measure the effectiveness of targeted maintenance interventions on risk reduction. A longitudinal dataset was constructed from maintenance logs, incident reports, and operational records for a fleet of heavy industrial equipment. A two-way fixed effects model was employed to control for time-invariant machine-specific factors and common temporal shocks. The core specification is $Risk_{it} = \alpha_i + \lambda_t + \beta Intervention_{it} + \gamma X_{it} + \epsilon_{it}$, where robust standard errors were clustered at the machine level. The implementation of structured preventative maintenance protocols was associated with a statistically significant 18.2% reduction in major incident risk (95% CI: 12.5% to 23.9%). Unobserved machine heterogeneity accounted for a substantial portion of the variance in baseline risk profiles. Panel-data estimation provides a robust methodological advance for isolating the causal effect of risk-reduction strategies in industrial settings, moving beyond descriptive correlation. Fleet managers should adopt panel-data frameworks for continuous safety performance evaluation. Investment in digitised, time-consistent record-keeping is essential to enable such analyses. reliability engineering, maintenance optimisation, fixed effects model, industrial safety, asset management This paper presents a novel application of econometric panel-data methods to engineering asset management, demonstrating a rigorous approach to quantifying the efficacy of safety interventions in an industrial context.</p> |
| title | Methodological Evaluation and Panel-Data Estimation for Risk Reduction in Tanzanian Industrial Machinery Fleets |
| topic | Panel-data estimation Risk reduction Industrial machinery fleets Sub-Saharan Africa Developing economies Maintenance engineering Operational safety |
| url | https://doi.org/10.5281/zenodo.18970994 |