Edge and Cloud: Are they Best for Processing Critical Business Data?

Data is at the heart of the Industrial Internet of Things (IIoT) and Smart Manufacturing. Establishing platforms to collect and analyse this data is critical for optimising manufacturing insights into processes. The most effective setup combines edge and cloud-based platforms to get the best of both worlds. In this blog article, we ask the question, are Edge and Cloud technologies the best places to process critical business data?

Mitsubishi Electric’s Chris Evans looks at why the future of network infrastructure balances edge processing and cloud capabilities.

Some may view edge and cloud computing technologies as competing platforms whereas they are synergistic. By harnessing the strengths of both and delivering the analysis, businesses can maximise productivity, efficiency and reduce costs.

Machines and automated systems on the shop floor generate vast amounts of time-critical data. Data processing and analysis need to happen in real-time to meet the demands of automated production. Edge computing operates in real-time using Advanced Analytics (AA) and Artificial Intelligence (AI) to conduct predictive and preventative modelling. It also reduces the number of data points dealt with in centralised, cloud-based locations, resulting in large cost savings.

Processing data using edge technology can provide seamless data coordination between the Operational Technology (OT) and Information Technology (IT) layers. Edge technology that follows the guidelines laid down by the Edgecross Consortium will support several network protocols. This allows data collection from plant level assets regardless of the automation vendor equipment used to control them.

The Edge and Cloud Conundrum

Deciding on how to use edge and cloud-based platforms depends on which best suits the operational and business drivers. For example, the edge is the best place to handle critical operational activities and production analytics requiring real-time processing. But processing business analysis that does not need real-time processing can be either a centralised or cloud-based.

The use of “Digital Twins” is increasing in IIoT and Smart Manufacturing, so where should they live in the plant topology? The digital twin is a virtual model of a process, product or service. It allows the logical comparison and analysis of “what we should have” against “what we have actually got.” Creating digital twins often occurs at the enterprise level, with the logical comparison carried out at the edge. In other words, knowledge development occurs in the cloud and actioned at the edge.

Leveraging the benefits of edge and cloud computing technologies, allows businesses to maintain optimal operational efficiencies and drive up productivity. They are also important as new technologies not associated with automation migrate to the plant floor for further process intensification. For example, Virtual Reality (VR), Augmented Reality (AR), natural language understanding and speech recognition. As these innovative opportunities are fast becoming practical realities, it is important for manufacturers to choose the right solutions partner.

By selecting future-oriented automation specialists, such as Mitsubishi Electric, businesses can rely on high-quality technologies and solutions. In this way, it is possible to enjoy these new technologies as soon as they are available and to put in place Smart Manufacturing strategies to boost operations as well as optimise processes. Download the full article here

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