Predictive Systems and Big Data in IoT in Manufacturing

The Internet of Things (IoT) is the general term that covers a world where smart systems, sensors and a large array of devices are connected together to offer business and consumers a more streamlined experience.

Market Researcher Gartner last year predicted in their Hype Cycle 26 billion devices would be connected by 2020, with Morgan Stanley increasing that figure to 75 billion. Others believe that only 50 million devices will be connected, but these are all estimates and no one really knows how many there will be. Do we really need to put a figure on it? We all know that the world will become more connected. The connectivity value in these networks will provide new ways of thinking, opportunities to exploit and act upon information and disrupt business models as well as introduce new security threats.

Take for instance manufacturing, linking up the IoT, sensors, robotics to automate the manufacturing process now let’s throw in Big Data. Across the world manufacturers are starting to look at linking Big Data within their manufacturing processes and IoT to transform and disrupt their manufacturing processes. Big data within the manufacturing process is becoming a game changer. While companies have been producing data for a years, new data tools are enabling real time analysis that provide real time problem solving, machine health monitoring and costs avoidance. Germany initiated an Industry 4.0 Government initiative to encourage its industry sector to realise the potential of this connection. Real time data driven decision support systems for the factory, that link in with logistic providers, other manufacturers of component parts and their clients, a system capable of synchronising all the areas in the supply chain, providing full visibility to all of those involved. The combination of IoT, and Big Data optimisation is bringing about huge opportunities.

These processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to Big Data to inform their decision support. The medical profession with environments such as hospitals where patients are their core component, interlinking with multiple chain events in a system of people orientated processes is possible.

Predictive systems play a key role in the Industrial IoT and supply chains. Intel and Mitsubishi piloted automated systems at the Intel manufacturing facility in Malaysia incorporating big data solutions to focus on improving productivity. By incorporating predictive machine health to reduce component failure the pilot optimised the process to realise savings of $9 million during its course.
To realise the vision of IoT in manufacturing interlinking all aspects of the supply chain, from an IT perspective will be a challenge. Many existing companies operate legacy structures which differ greatly from open architectures and data sharing. Linking data from disparate sources can’t be simply merged. To support the IoT, common data models, standards and architecture that spans the supply chain will need to be brought together. In some industries these standards already exist. Industries such as food and drink, have standards to measure the temperature of containers, track shipments and analyse food contamination, all standard parameters across the supply chain.

The impact of using big data and predictive systems in IoT manufacturing will represent great economic value. Optimised and automated factories will achieve results at a faster rate, reduce energy operating costs with increased efficiency, and processes that react to demand. Incorporating real time data will open up markets for companies to be able to response to changing consumer demand quickly, supply markets faster inline with demand. Future visions will include predictive machine health monitoring potentially not just in the manufacturing process, but also enabling streamlined after sales opportunities for companies to supply their consumers with parts before complete failure. Big data, predictive models and IoT will potentially open up greater markets that would benefit all within the supply chain.

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