Digital twin

Data strategy for IoT and Industry 4.0

When people talk about industry and manufacturing, their heads often turn to large scale production with huge machines and a massive pool of people doing a multitude of jobs. Although many industrial companies and factory settings have been using forms of digital technology for some time now, only in recent years has this started to become more mainstream.

There has been a realization that using artificial intelligence (AI) and Internet of things (IoT) devices through the supplier chain, can have amazing effects on efficiency and cost savings.

When you hear about AI in the media, it often sounds very futuristic, but in reality AI is not at the level that movies or television might lead us to believe. Whilst companies might like to stick a picture of a Terminator or Marty McFly style hoverboard in their advertising, that is very much an exaggeration and we are a few decades away (at least) from that kind of fully autonomous world.

The most common application is known as machine learning. This technique trains computer algorithms to think like humans do using existing data from the world around it. For example, we could load a computer with thousands of pictures of cats and dogs. The computer will ingest those images, convert them to data and going forwards, will work out for itself whether an animal is a cat or a dog.

To put this into a real-world context. An IoT device is anything that connects to the internet. Most people have countless technologies that do this from smartphones to laptops, tablets, Alexa, Google Home, televisions and even kettles, fridges and washing machines.

When we speak to Alexa (the IoT device), it takes what we say and converts that into data using a method called natural language processing (NLP). That data is then matched against a huge database of previous conversations to find the closest match. Alexa can then reply to your command. Every time you have a conversation, Alexa learns and becomes more accurate.

So, for every IoT device we have, the more it gets used, the more useful it becomes as they learn from data. This is one reason that we are seeing a movement towards Industry 4.0. When we talk about anything “4.0” right now, it generally refers to the next evolution of technology. In this case it refers to industry and manufacturing.

The advances in computer power, data, AI and IoT will orchestrate rapid advancement over the coming years, and by the end of the decade, it is fully expected that the world will look quite different.

We are at a stage now where there is enough computing power and data available in the world to make fast progress within industrial settings, hence, the buzz around Industry 4.0.

Whilst in the third industrial revolution (Industry 3.0), computers started being introduced, in this forward-thinking era, having connected machines that communicate with each other is key without the need for human involvement. This will be a combination of physical systems, IoT and AI to create a data driven smart factory that is more efficient, productive and cost effective than we have ever seen before.

The network of all these machines is what we are calling Industry 4.0. Here are a few of the use cases being utilised in practice.

Opportunities – with countless devices and sensors in a smart factory comes a vast amount of data. This can include information about the devices, environment, staff or outputs. It might take a human day to sift through millions of data points, but new technology allows real-time analysis. For example, a sensor might flag that temperatures are too warm for production and reducing those will increase yield.

Supply chain – data can be connected throughout the entire supply chain, from factory to the shelf for example. One common use case is in shipping when products are delayed and everything else connected to the system can be proactively adjusted.

Autonomous equipment – Most of us will be aware that autonomous vehicles are on the horizon with the likes of Tesla suggesting that driver-less cars could be on the roads as early as 2020 (there are already some being used in trials).

In the Industry 4.0 context, the same technology can be used with cranes or trucks to make operations more efficient. For example, a crane that is controlled remotely rather than requiring a human driver.

Robotics – this is quite key to the future of Industry 4.0 as the machinery becomes more cost effective in factories. Amazon are a leader in the use of robotics, using such technology to move items around the warehouse, saving on resource cost and physical floor space.

— Ram Narasimhan, Global Executive Director – AI and Bigdata, Xebia.

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