The first two articles in this series aimed to demystify two terms that we’re hearing a lot these days: Big data and advanced analytics. In this final article, my goal is to explain a term that is less commonly heard, but equally relevant to the biorefining sector: The Industrial Internet of Things (IIoT). Before getting to grips with IIoT, let’s cover the Internet of Things (IoT). Sometimes described as ‘machine to machine communication’, IoT is essentially about data transfer. It describes the ability of machines (things) to connect via the internet. This connection allows them to gather and exchange data in such a way that the machines themselves can make data-based decisions.

The data is gathered by sensors in the machines, which means that any machine – from household appliances to industrial machines – that can be fitted with sensors can potentially be part of IoT. When applied to manufacturing – in the context of industrial machines – this connectivity is called the Industrial Internet of Things (IIoT), and – because it is predicted to fuel the next or fourth industrial revolution it is also sometimes known as Industry 4.0. Put very simply, IIoT consists of computers and machines (or cyber-physical systems) talking to each other to discover, analyze and resolve issues in processes in advance, with minimum human supervision.

Decentralizing decision making

In the ‘smart’ factories enabled by IIoT, fully connected computers and machines monitor the physical processes of the factory and make decisions independently of any centralized control system. The decentralized decision-making made possible by IIoT offers clear potential benefits in all manufacturing environments. These include smart electricity grids that match power generation to loads, predictive maintenance cost-savings and automated production lines that maximize throughput. And for most industries, sensors are key to implementing IIoT.

Improving productivity and reducing waste

One example is the automotive industry, where Bosch uses continuous status updates gathered via sensors to achieve a 25% output improvement for production of its automatic braking system (ABS) and electronic stability program (EPS). By comparing the status updates with system simulations running at 100% efficiency, gaps in efficiency can be quickly pinpointed and closed. At Audi’s tool-making division, meanwhile, self-learning technology employs sensors to measure how much material is fed into a press and automatically adjusts when measures are outside a defined range, reducing the number of rejected parts.

Moving towards ‘smart’ biorefineries

So if data-gathering via sensors is key to IIoT, the relevance of IIoT to biorefineries is clear. As Frank Moore explained in the previous article in this series, ethanol plants use sensors to gather and analyze huge volumes of data every day. Currently all the data gathered is fed into central supervisory equipment. IIoT is about decoupling machines from applications – such as central supervisory equipment – and instead connecting them directly to the infrastructure and thereby to each other. In a GE report examining the potential benefits of IIoT across several industrial sectors, specific machine types to which IIoT could be relevant were pinpointed. Under the classification ‘critical rotating machinery’ in ethanol plants, the report identified grain handling systems, conveyors, evaporators, reboilers, dryer fans and motors as machinery that ‘can be monitored, modeled, and manipulated remotely to provide safety, enhanced productivity, and operational savings’. This list, while extensive, is only a small part of the picture however, because any machine fitted with sensors can potentially become part of IIoT, and virtually every process step in an ethanol plant uses sensors. This gives biorefineries real potential to join other ‘smart’ manufacturing processes in reaping the benefits of the fourth industrial revolution.

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Anders Drud Olsson

Senior Manager at Novozymes Data & Analytics Management
Anders brings more than 10 years’ experience in the digital field to his work with Novozymes digital services for the Biofuel industry, where he has been active for more than two years.

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