Abstract

The ongoing fourth industrial revolution is pushing manufacturing towards smart, cognitive, and more adaptable systems. These new paradigms will require a huge number of computational resources. To meet these needs, the evolution of Industrial Internet added a layer of low-power heterogeneous devices with processing capabilities on the edge of the network, closer to the area where it is needed. Single board computers are the most common hardware platform found in the edge nodes. Due to its computation performance and power efficiency, the resources of this layer on the edge should be explored to solve processing demanding tasks. Maybe systems like the enterprise resource planning systems (ERP) and the manufacturing execution systems (MES) that are typically hosted in the industrial cloud can take advantage of sharing services between the cloud and the edge. This work aims to explore the edge layer collaboration with the cloud, sharing computational power to process the manufacturing scheduling problems linked to the ERP and MES. Therefore, in this preliminary study, we investigate the potential of single board computers to solve manufacturing scheduling problems. We present the experiments with four versions of Raspberry Pi, a well-known single board computer, evaluating them from the energy consumption and computation time points of view. Experiments show that it is possible to solve these scheduling problems in a reasonable time, with a lower energy consumption than other high-end computing devices.

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