Applying the overall equipment effectiveness (OEE) indicator to improve the layout of a packaging sector allows for the identification and mitigation of losses associated with the sector’s availability. Availability, one of the three components of the OEE, measures the actual time that equipment is operational in relation to the planned time, identifying inefficiencies such as unplanned and planned downtime. A case study in an industrial plant demonstrated that layout reorganizations, based on OEE analysis, can significantly reduce these losses. The approach consisted of mapping the production flow and strategically reallocating machines to minimize the time spent moving between processes and reduce bottlenecks. By prioritizing critical equipment and optimizing its availability, the factory will get a 15% increase in the overall OEE index. In addition, the study showed that layouts aligned with the logic of continuous production help to reduce the impact of failures, improving responsiveness to daily demands. Using OEE as a guide reinforces the importance of clear metrics for industrial engineering decisions. This method not only improves operational efficiency, but also promotes a culture of continuous improvement, essential in competitive environments and aligned with the principles of Industry 4.0. The article may open the way for comparative studies between different industrial sectors, investigating the effectiveness of using OEE in reconfiguring layouts, and may also suggest integration with Industry 4.0 technologies, such as IoT sensors and Big Data analysis, to improve the collection and interpretation of OEE data.

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Improving Layout Efficiency in Packaging Sectors Using the Overall Equipment Effectiveness Indicator for Problem Detection and Improvement

  • Carlos Regattieri,
  • Francisco J. G. Silva,
  • Ana Azevedo,
  • Marisa Santos,
  • M. Teresa Pereira

摘要

Applying the overall equipment effectiveness (OEE) indicator to improve the layout of a packaging sector allows for the identification and mitigation of losses associated with the sector’s availability. Availability, one of the three components of the OEE, measures the actual time that equipment is operational in relation to the planned time, identifying inefficiencies such as unplanned and planned downtime. A case study in an industrial plant demonstrated that layout reorganizations, based on OEE analysis, can significantly reduce these losses. The approach consisted of mapping the production flow and strategically reallocating machines to minimize the time spent moving between processes and reduce bottlenecks. By prioritizing critical equipment and optimizing its availability, the factory will get a 15% increase in the overall OEE index. In addition, the study showed that layouts aligned with the logic of continuous production help to reduce the impact of failures, improving responsiveness to daily demands. Using OEE as a guide reinforces the importance of clear metrics for industrial engineering decisions. This method not only improves operational efficiency, but also promotes a culture of continuous improvement, essential in competitive environments and aligned with the principles of Industry 4.0. The article may open the way for comparative studies between different industrial sectors, investigating the effectiveness of using OEE in reconfiguring layouts, and may also suggest integration with Industry 4.0 technologies, such as IoT sensors and Big Data analysis, to improve the collection and interpretation of OEE data.