Today's machining shop floors, characterized by large variety of products in small batch sizes, require dynamic control and real-time monitoring capabilities that are responsive and adaptive to the rapid changes of production capability and functionality.
Today's machining shop floors, characterized by a large variety of products in small batch sizes, require dynamic process planning capabilities that are responsive and adaptive to the rapid changes of production capacity and functionality.
Manufacturing in a job-shop environment is often characterized by a large variety of products in small batch sizes, requiring real-time monitoring for dynamic distributed decision making, and adaptive control capabilities that are able to handle, in a responsive way, different kinds of uncertainty, such as changes in demand and variations in production capability and functionality.
Nowadays machine tool control, for small batch sizes, suffers from a lack of flexibility at machine level.
This will see Industry 4.0 technologies not only increase efficiency and reduce waste, but also enable smaller batch sizes, more personalised products and greater product innovation.
Although Hybrid Capture II was used within this evaluation, alternative options that require smaller batch sizes are also available and these have not been evaluated within this study.
This was done by adding small batches (∼3mg; particle size 106 150μm) of a char to a hot bed of silica sand (diam. 90 126μm) fluidised by different mixtures of O2+N2, varying from 0 to 100 vol% O2.
The proposed approach results in energy consumption reduction by optimizing batch sizes and operating conditions.
