Selected thematic authors in relation to optimising OEE and performance metrics
| Authors | Themes |
|---|---|
| Basak et al. (2022) | The adaptability of the OEE metric serves to detect production weaknesses for elimination |
| Bengtsson et al. (2022) | Managerial biases affect decision-making processes |
| Chong and Ng (2016) | Financial implications of OEE are a focus, as performance metrics directly affect profitability |
| Costa and Lopes (2021) | Systematic data collection, combined with inter-departmental collaboration, enhances product availability and quality, boosting organisational productivity |
| Dal et al. (2000) | Implementation of lean practices results in productivity increase and waste reduction |
| De Ron and Rooda (2006) | develops a method to distinguish performance metrics from conventional models |
| Di Luozzo et al. (2021) | How IoT systems operate to prevent machine failures and maintain uninterrupted production |
| Di Luozzo et al. (2023) | Predictive maintenance plays a vital role in minimising downtime and improving system reliability |
| Franzini et al. (2021) | Demonstrates how system-level performance monitoring supports additive manufacturing objectives, enabling better strategic decisions |
| Gendre et al. (2016) | The real-time monitoring function of MES tools reduces downtime and improves reliability |
| Gola and Nieoczym (2017) | Targeted modifications lead to documented improvements in machine stability and production robustness |
| Hedman et al. (2016) | Demonstrates how inaccurate data classification leads to meaningless automated system outcomes |
| Ljungberg (1998) | Emphasise the requirement to address data basics while establishing sustainable TPM activity outcomes |
| Authors | Themes |
|---|---|
| The adaptability of the OEE metric serves to detect production weaknesses for elimination | |
| Managerial biases affect decision-making processes | |
| Financial implications of OEE are a focus, as performance metrics directly affect profitability | |
| Systematic data collection, combined with inter-departmental collaboration, enhances product availability and quality, boosting organisational productivity | |
| Implementation of lean practices results in productivity increase and waste reduction | |
| develops a method to distinguish performance metrics from conventional models | |
| How IoT systems operate to prevent machine failures and maintain uninterrupted production | |
| Predictive maintenance plays a vital role in minimising downtime and improving system reliability | |
| Demonstrates how system-level performance monitoring supports additive manufacturing objectives, enabling better strategic decisions | |
| The real-time monitoring function of MES tools reduces downtime and improves reliability | |
| Targeted modifications lead to documented improvements in machine stability and production robustness | |
| Demonstrates how inaccurate data classification leads to meaningless automated system outcomes | |
| Emphasise the requirement to address data basics while establishing sustainable TPM activity outcomes |
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