This article introduces two real-life case studies respectively devoted to a parallel production system of a chemical company and to a production system made up of tightly interconnected machines. The objective is to highlight the most relevant features of a production system that determine the system's productivity. A calculation model that allows movement from machine-level to system-level indices is useful both during the production system design and during the performance measurement phase. The application of the presented framework provides useful results: (1) to improve analysis, and to make proper diagnosis of causes, of productivity loss and to track their evolution over the time; (2) to design and to implement specific improvement projects, aimed at removing loss causes, and thus increasing efficiency and productivity; (3) to establish proper production capacities, by focusing on bottleneck machines, to keep under control the actual system throughput; (4) to make comparisons and internal benchmarking aimed at defining machine management and productive maintenance best practices; (5) to design plant performance reporting systems and build appropriate tools to collect data from the field.
Modelling capacity and productivity of multi-machine systems
GRANDO, ALBERTO
2009
Abstract
This article introduces two real-life case studies respectively devoted to a parallel production system of a chemical company and to a production system made up of tightly interconnected machines. The objective is to highlight the most relevant features of a production system that determine the system's productivity. A calculation model that allows movement from machine-level to system-level indices is useful both during the production system design and during the performance measurement phase. The application of the presented framework provides useful results: (1) to improve analysis, and to make proper diagnosis of causes, of productivity loss and to track their evolution over the time; (2) to design and to implement specific improvement projects, aimed at removing loss causes, and thus increasing efficiency and productivity; (3) to establish proper production capacities, by focusing on bottleneck machines, to keep under control the actual system throughput; (4) to make comparisons and internal benchmarking aimed at defining machine management and productive maintenance best practices; (5) to design plant performance reporting systems and build appropriate tools to collect data from the field.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.