A framework for Industry 4.0
We’re surrounded by more and more connected devices we’re calling the Internet of Things. We can turn our heating on from our phones on the commute home. Pegs can tell us when to bring the washing in so it doesn’t get wet. Cars know the hazards ahead and warn us before we get there so that we can avoid them. Many of the ‘things’ have been manufactured within the ‘Industrial Internet of Things’ or ‘Industry 4.0’. But where did the 4.0 came from? What was 3.0, and why are you going to hear about it more and more? Welcome to the fourth industrial revolution!
A brief history of industrial revolutions
In the 19th Century we moved from producing what we consumed on farms and in workshops to large scale production in factories. We captured the power of steam and we built engines that lead to mass mechanisation. We called this the first industrial revolution – Industry 1.0.
From the 1850’s to World War I, electricity moved us on again. We created steel and built assembly lines and welcomed in a new age of mass production. This was the second industrial revolution – Industry 2.0
Information became the next ‘revolution’ from the 1950’s to the 1970’s. As a result, we all got comfortable with computers, everything started to become digital and elements of manufacturing moved into automation and robotics. Hello Industry 3.0.
That brings us to today, the ‘Internet of Things’ and Industry 4.0. Machines are starting to support we humans to make decisions and do work for us in areas too hazardous for us to go, or with tasks too complex.
The four components of Industry 4.0
What’s made this possible? Four ingredients combined bring us Industry 4.0 – things that are instrumented, interconnected, inclusive and intelligent.
Data surrounds us. The devices we carry around generate data, the cars that we drive generate data. The exercise and sleep monitors we wear generate data. More and more of the products and services we interact with will be generating data. That’s on top of the data we generate ourselves with all our status updates, posts, videos, photos and more. We’re awash with it. It’s getting quicker too. The speed with which the data gets from chips to analytics is accelerating as Texas Instruments and ARM have found working with IBM. All that data is no use unless it’s moved somewhere it can be analysed. That could be where it originates, in a cloud, or both such as IBM’s BlueMix – all that data needs somewhere secure to go.
We’re constantly connected. We wake up and check our smart phones. Apple’s latest OS updates included Siri, the interface you can talk to; Google’s Home and Amazon’s Echo all make it easier for us to talk to our connected devices and for them to do things for us – including answer back. There are clouds that hold our information and process it, and ‘fog computing’ that does what clouds do – but on the ground at the ‘edge of the network’ as IBM and Cisco do.
There are also platforms to help process the information, like the Watson IoT Platform. If you’re familiar with ‘The Hitch Hiker’s Guide to the Galaxy’s’ ‘Babel Fish‘ or Star Trek’s ‘Universal Translator’, these platforms provide a place to receive the data, translate it into a common format that the computing ‘brains’ can work with, and pass back the results and insight. If you’ve ever used Facebook’s ‘Messenger’ app, you’ll have used this standard language called MQTT.
Those standards are important too. With such a variety of development happening at speed, there’s always the chance of another ‘betamax’ or ‘VHS’ showdown. Companies need to agree and conform to standards such as ASPICE, ISO 26262 and many other to ensure that we all continue to talk the same language.
Do you have an alarm that knows that the weather is going to be bad? That the bad weather will jam up the traffic. As a result of that jammed traffic, your journey take longer, so your alarm gets you up a little earlier so that you’re not late for work? This is an example of a three of data sets (weather, traffic and maps) that working together with a device (your alarm clock) can anticipate a need for you and change your environment to accommodate for it. Applying data from one place such as the Weather Company to another can make a significant difference, and keep you on time for the office.
The power of partnerships
For some companies, the data they produce can even become a new revenue stream. Take the humble umbrella. Mary Poppins’ had special powers, and you might think that of connected umbrellas too. A clothing manufacturer might want to know where umbrellas have been used to supply stores with waterproof clothing that might sell well, and show adverts with offers to encourage passers-by to purchase them. A building owner might find it useful to know how many employees are coming to work with umbrellas to schedule the cleaning operators to mop floors to prevent anyone slipping up and change the temperature so that damp employees feel comfortable. A taxi company might want to know where umbrellas were congregated to adjust where its fleet was operating to take advantage of travelers not wanting to stand in the rain. Context data adds insight and can drive revenue.
These partnerships will become increasingly important and new relationships will form within industries and across industries like never before. Having a place where those industrial relationships can grow and flourish, accompanied by the expertise to facilitate it such as IBM’s IoT HQ in Munich will see more connections being made that consumers will benefit from.
Last, but by no means least is intelligence. With the availability of cloud computing and the sophistication of analysis, all of that ‘big data’ can be used to make better informed decisions. Those decisions come with a degree of confidence such as IBM’s Watson. Machine learning, artificial intelligence, predictive analytics and cognitive computing learn from the data created by the growing number of connected sensors around us.
With these four elements in place, we enter a new industrial revolution – Industry 4.0.
The three stages of manufacture
Bringing the four components together to create Industry 4.0 is all well and good, but how does it influence the goods and services we consume? Introducing the three stages of the manufacturing process: designing, making and using. Across each of these three areas, Industry 4.0 is changing the way that products come to market.
Have you ever taken an Uber or rented a Car2Go? These two services are changing the idea of car ownership. You can call a car from an app and rent a car by the hour. You use your phone to open the door and pay for your journey. For you, gone are the days of owning or leasing a car, thinking about servicing, insuring, and parking. Alternatively, you might have a car that plans your route for you, takes into account the impact that traffic will have on you, keep you safely in your lane, know when you need to take a break, even know when there’s a hazard in the road ahead, and which way you need to move to avoid it.
You might just use a voice activated interface to update your car’s software rather than have it serviced. Upgrading your car may become as easy as upgrading your phone. Creating new features that the market demands and assuring reliable products will be key for manufacturers. Companies are now this continuous industrial engineering approach to managing their entire engineering processes for designing, developing, testing, deploying and managing their high-end systems.
How we use products today informs the designs of the future
Today’s sensors can modernise old assets. The way we use assets today is steering the designs of the future. That bulky remote control that still ended up down the side of the sofa, replaced with a small control that just has what you need, or no physical control, you simply tell your television what you want it to do or wave at it.
Insight in product design is coming from the way we are using products today. The data we generate steers the products we’ll buy in the very near future. Indeed it will guide not just product design, but move manufacturers into new areas. Michelin are known for their tyres. Today they can manage fleets better with connected tyre data; guide drivers on how to save fuel and keep safe through changes in the way they drive; become instructors, teaching other companies how to travel the road more efficiently. Michelin moves from a tyre manufacturer to a driving instructor.
Sakishi Toyada introduced the ‘5 whys’ into his car company Toyota’s production lines – an industrial revolution in its own way with its new time management approaches. If there was a fault on the line, asking ‘why?’ five times found the human interaction that was usually at fault and could be fixed.
- Why has the line stopped? Because the belt is broken
- Why is the belt broken? Because the transmission drive has failed.
- Why has the transmission drive failed? Because it was not lubricated.
- Why was it not lubricated? Because it missed its scheduled service.
- Why did it miss its service? Because an employee forgot to schedule it.
With today’s sensors and analytics, and the context of external data that can influence wear and tear like weather, predictive maintenance can become widespread. Production lines can predict issues and schedule time to fix them, right down to product and component level. You can listen to manufacturing sounds. You can pick up unexpected sounds and identify what caused them. Then you can fix any issues to fulfill orders and maximise throughput.
The German Engineering company Schaeffler are pioneering the development of ‘mechatronic’ components which combine both mechanical and electronic capabilities into individual parts which have the ability to monitor and report on their own performance.
Data becomes a new revenue stream
Following on from what we saw in the design phase, the data that smart production lines can produce, can in itself become a revenue stream and open new opportunities for manufacturers. As the autumn evenings draw in, you can switch on your heating on your commute home so that it’s warm when you get in. Utility companies can use the thermostat’s data to encourage you to conserve energy at peak times – possibly incentivising you via your smart phone.
As a result of all of these new connected production lines, products and services and the ways that we interact with them are opening up new jobs. Experience designers, application developers and data scientists will be in high demand along with the implementation and maintenance professionals to install and keep the Industry 4.0 production lines and apps in peak condition.
Apple OS X Sierra release brought their voice assistant Siri to the desktop along with iOS 7 which updates it on their phones and tablets. Following this, we’ll soon become familiar with asking our laptops to do things, spared the laborious task of instructing them what to do with a keyboard. This new form of human/computer interaction is among many that we’ll start to see. You can control a BB8 droid with your mind and have a chat with your autonomous car Olli to ask it where the best restaurant is – and have it take you there whilst you catch up on the latest edition of that box set you’re following.You won’t be disappointed by the products you want being unavailable – manufacturers’ production lines and supply chains will ensure that what you want is ready whenever you want it.
Wearable and embedded sensors make it possible to monitor workers and their surroundings to prevent them injuring themselves from falls, over-exertion, heavy machinery and many other hazards. This leads to great news, given that 321,000 people die each year from occupational accidents. NorthStar Bluescope Steel, a steel producer for global building and construction industries for Australia, New Zealand and North American markets, is creating smart helmets and wrist bands to help employees stay safer in dangerous environments. Employees and their managers can respond to real-time alerts if their physical well-being is compromised or they don’t follow safety standards.
Revolutions are disruptive
Revolution is by its nature disruptive, and Industry 4.0 is no different from its predecessors. The work that people do will change. Sophisticated ‘aware’ robots could replace people doing manual, labour intensive work, repetitive activities or work in hazardous environments. New roles will emerge requiring new skills. The availability of those resources may be too low in the early days, slowing companies moving to Industry 4.0 models.
Where there is data there is risk. Leading on from risk there are hackers who will hack. As a result, maintaining secure networks and keeping data safe will be paramount. This is particularly important when you consider all the devices we’re using and the connected ‘things’ we’re interacting with. Technology will continue to evolve rapidly. Following this will be the questions you need to ask yourself. Do you update your phone each time a new handset comes out or do you wait? Scale that to production lines and the cost of waiting or moving increases exponentially. Fail to move sufficiently quickly and you risk losing out to another Uber or Netflix.
The $15 trillion pay off
In summary, Industry 4.0 offers a huge payout. In ‘Defining and Sizing the Industrial Internet’ David Floyer estimated the value of Industry 4.0 at $15 trillion of global GDP by 2020. That comes from the increased efficiency of industrial plant equipment and long-term maintenance and management. The contribution to adjoining Industrial Internet networks, and the value of disruptive new business models. If you’d like to find out more about Industry 4.0 and join the next industrial revolution, visit IBM Industry 4.0.