Johan Jonzon, Co-Founder and CMO, Crosser How can Industrial Internet of Things (IIoT) edge analytics improve manufacturing efficiency?
Research from market insight provider IoT Analytics has revealed that making edge computing systems ‘smart’ by integrating intelligent tools is a key driver of the technology’s continued growth. Edge analytics is a major enabler of an intelligent edge solution, broadening the scope of its use cases by enabling low latency, high-volume data actions. Here, Johan Jonzon, Co-Founder and CMO of low-code streaming analytics platformCrosser, explains the important role of edge analytics in Industry 4.0.
A 2020survey conducted by industrial automation provider Yokogawa revealed that 48 per cent of respondents valued productivity as a key focus in their digitalization strategies, while 40 per cent regarded operational efficiency as their main objective.
Edge computing plays a key role in facilitating this acceleration, but making the edge intelligent is essential to maintaining its value. Edge analytics is the process of collecting, analysing and acting on data gathered from IIoT devices directly from the edge, enabling manufacturers to improve their efficiency and make innovation happen faster. But how?
Accessing machine data
Big data laid the foundations of Industry 4.0, yet accessing it in the right way continues to challenge manufacturers. Factory floors have so many different machines, which all collect data with the potential to provide valuable insight. Retrieving relevant data in the correct format is the first hurdle for manufacturers looking to make the most of their edge capabilities.
However, it isn’t just the quantity of data that edge analytics controls. It is also used to harmonise data by converting different datasets into a common format for machine compatibility and comparison. Factory floors hold equipment from multiple generations, which all collect data in different ways.
Processing this vast amount of data at the edge prevents overwhelming the cloud system, and also significantly reduces associated costs. By avoiding expensive cloud entry services, only processing and storing relevant data on the cloud can reduce costs by up to 99 per cent.