Industry 4.0: An Introduction
Digitisation of the physical world brings a unique set of opportunities for asset- intensive industries like manufacturing, mining, oil and gas, energy, utilities, and transportation. From assembly lines that repair themselves to intelligent distribution networks where every product can be monitored in real time, Industry 4.0 (i4.0) is just beginning to have a real impact across the industrial world. Referring to the fourth industrial revolution, it's the combination of industry and Internet of Things (IoT) technology.
At the heart of i4.0 are three key solutions:
• Data and analytics (e.g. machine learning [ML])
i4.0 has been portrayed as a paradigm that impacts the bottom line, by improving operational efficiencies across supply-chain, the production floor and distribution channels. However, in a world where existing business models are being threatened by low-asset or no-asset upstarts, i4.0 has another important function: it has the potential to impact the top- line by enabling new business models. Let's take a look into how organisations today are taking advantage of the opportunity that i4.0 offers.
"Industrial companies play a major role in the world today. Manufacturers must embrace technological advances to improve plant productivity, compete against rivals, and maintain an edge with customers."
One person in every eight is employed in manufacturing, while 16% of global GNP is generated by the sector. Manufacturing invests heavily in R&D too - delivering 20% of global innovation, and funding 77% of all research and development, so it's understandable why the sector is so important to economic growth.
Against this backdrop, the industry continues to bounce back from the economic uncertainty of 2008. Competition and the pressure to protect margins remains fierce, particularly with existing business models being challenged by the emergence of low-asset or no-asset upstarts. In response to these changing socio-economic factors, industrial leaders are exploring technological transformation.
Key findings from PwC's Global Industry 4.0 Survey of 2,000 participants from companies across 9 industrial sectors, showed that by 2020:
• Investments in i4.0 applications are expected to total US$4.5 trillion.
• Additional revenues as a result of these investments are expected to reach US $2.4 trillion.
• Costs are expected to reduce by US$2.1 trillion.
Driven by disruptions in technology and fed by big data, i4.0 is enabling industrial companies worldwide to digitise value chains, connect automation and drive innovation across product portfolios in an entirely new way. The concepts and technologies at the heart of this revolution are
connectivity, advanced data and analytics, and cloud.
"Gartner says by 2020, more than half of major new business processes and systems will incorporate some IoT element(s)."
Advanced data and analytics capabilities, when applied to the data from the connected physical world, are set to revolutionise the industry. The data gleaned from IoT enables a virtual representation of a physical asset/ device/product/plant to be created - some referring to this as a "digital twin".
This digital twin can then be used to deliver a range of capabilities, such as predicting failures; optimising processes by simulating changes; augmenting the experience of the user; and creating virtual experiences for individuals who are not physically with the asset.
These capabilities and their impact are greatly enhanced when ML is added. This is because ML algorithms can provide better predictive accuracy - and constantly learn - delivering better-optimised results. ML capabilities such as machine vision can also support organisational goals, like improving quality control and safety on the factory floor.
"I think that the more sophisticated parts of the business, like design and R&D, are much more likely now to adopt cloud because of its agility, quality and innovation."
Cloud technology is a core enabler of i4.0, as it is an ideal environment for capturing, storing, and analysing the data generated by i4.0 at low cost. With the agility that cloud offers, it also provides an environment where companies can experiment without expensive investments in infrastructure.
This enables industrial companies to more readily adopt a culture which promotes innovation and new business models.
Smart systems that capitalise on predictive data analytics and automated manufacturing and precision engineering are driving demand for ever-smaller components. Machine learning increases production capacity by up to 20% while lowering material consumption rates by 4%.
Smart(er) Supply Chain
"With Smartsheet we've reduced overhead and complexity and cut time spent on processes. We can proudly say that we've met our goal to create easy-to-adopt digital practices and a more efficient, sustainable supply chain."
The industrial supply chain is already one of the most data-rich environments.
Now, thanks to cloud, IoT, advanced analytics and ML technologies, companies can build, ship and track raw materials and parts across thousands of locations, on- spec, on-time and in-budget - critical in an environment where margins are tight. By using the data from connected objects, companies can make minor adjustments which, when applied at scale, make a significant difference to the bottom line.
Vehicle fleet management company Noxxon Sat has lowered the cost of tracking over 3,000 buses by 20% by switching to a real-time, online tracking system. The Cloud enables Noxxon Sat to store, process and analyse the buses' telemetry data inexpensively, securely, and at breakneck speeds. The whole system can scale in line with the business - no upfront investment needed.
Design and prototyping
"Before, we ran two calculations or tests at the same time, about 10 a week but with The Cloud, we can run an infinite number at the same time, with more creativity, more customisation and consequently more customer satisfaction. Today, we run 40 or more calculations a week."
Before the dawn of i4.0, design and prototyping typically followed an inefficient process, build physical prototype, test, fail, redesign, rebuild prototype, test, fail, redesign, etc. But with the power of cloud-based design, the process is being transformed into one that is dynamic and entirely digital. Imagine a working hologram of a part that can be continually modified and refined.
This kind of pre-modelling can allow the cloud-enabled teams to design, visualise and simulate their ideas almost as fast as they can imagine them, accelerating the product into the prototyping stage for physical testing. This not only reduces the cost of design and prototyping but also speeds up time to market.
Take the case of a rapidly growing French startup, Expliseat, makers of the lightest airliner passenger seats on the market. Facing a scaling issue, Expliseat turned to The Cloud to support the computational power and data crunching needed for engineering, designing and testing their product.
The cloud can also enable entirely new models of design.
Local Motors, a manufacturer of open-source motor vehicle designs, utilises innovative cloud-based technology to enable crowdsourced vehicle design. The cloud hosts a community of designers, engineers, fabricators, and enthusiasts who respond to design challenges Local Motors posts on its website. The crowdsourced community collaborates on design and critiques each other's ideas. Local Motors gives payment and full credit to those whose brainstorms are incorporated into the final products. This type of collaborative design would not be possible without cloud.
The Production Floor
Gartner says that by 2020, a quarter of a billion connected vehicles will enable new in-vehicle services and automated driving capabilities.
Cloud computing can also support the shift towards smart production. Industrial companies are embedding sensors into assembly lines and machine tools on the factory floor, then connecting them using an IoT framework and making sense of the data through ML - leveraging it at larger scale and in new ways that weren't possible before.
This approach is improving business outcomes and stands to become widespread because cloud makes it relatively easy and affordable.
For example, Ocado, the world's largest online-only grocer, makes deliveries from a highly automated warehouse. An order is completed every 2.5 seconds, and Ocado strives to make each order meet their customer's expectations. One of the problems they've been looking to tackle using i4.0 technologies is broken eggs. This is one of the leading causes for customer dissatisfaction, and while eggs may break in transit, they may have also left the warehouse floor broken. Ocado is now using machine vision technology, to take photos of orders before they are shipped, and identify common problems like broken eggs.
The result is improved product quality and increased customer satisfaction. The data from connected assets also offers opportunities to proactively monitor the condition and performance of equipment.
For example, Oden Technologies uses Google Cloud to capture and store approximately 10 million data points on each manufacturing line per day. Each of these goes into granular detail, with parameters such as the melt profile of materials and the amount of power going to the machines, as well as high-level metrics such as utilisation, the amount of raw material consumed, and the volume of material produced. Environmental information such as humidity, dewpoint, and temperature is also captured so that manufacturers can determine if there are weather-related and seasonal impacts on manufacturing efficiency.
Since manufacturers have access to live data and can analyse production data quickly, they can troubleshoot and resolve problems in minutes rather than months. The potential outcomes are significant and include increased overall efficiency, reduced costs and less industrial waste.
Augmented Reality (AR) In Production
AR is also having an impact in production, with many businesses seeing AR in industrial environments as an attractive and efficient way to organise assembly lines and warehouses. Agricultural manufacturer AGCO has factories all over the world where it makes large tractors, chemical sprayers and other farm equipment.
Google Glass is helping workers put together engines before they go on the assembly line by assisting them in case they forget which part comes next. With Google Glass, the worker scans the serial number on a part, bringing up relevant manuals, photos or videos. The worker can tap the side of headset or say "OK Glass" and use voice commands to leave notes for the next shift worker.
The headsets are being used in other industries as well. Boeing is using Google Glass in aeroplane manufacturing, reducing production time for harnesses by 25% and cutting error rates in half.7 Companies working in the healthcare and energy industries are also listed as some of the Google Glass certified partners.
With IDC predicting that the virtual and AR market will be worth US$162 billion by 2020, this is just the beginning of AR's application in industry.
Greener Manufacturing and Social Value
Every manufacturer is under pressure to become more environmentally- conscious and sustainable.
IoT is used to enable smart buildings which save energy, and the industry is rapidly moving beyond motion-sensor lighting. Cloud-connected building controls enable companies to tap into building connectivity and sensors with the goal of ensuring that power usage is optimised and building equipment is performing at its best.
Beyond the building, large-scale commercial and industrial systems also consume a lot of energy. Google itself faced a similar problem, with vast data centres housing thousands of power-greedy servers. By applying machine learning to its own data centres, Google has reduced the amount of energy it uses for cooling by up to 40%. Tackling these issues not only reduces a manufacturer's environmental impact, it improves the bottom line too, all the while protecting the planet - a win-win.
To help employees be more productive, happier, healthier and connected with other teams around the globe, Whirlpool turned to The Cloud to foster their "winning workplace". As a result, Whirlpool is enabling in-house collaboration across sales, manufacturing and merchandising teams, regardless of location.
The workforce can also track all their metrics across the company in real time, removing barriers to creativity and productivity. This is unlocking global collaboration and making the company feel local while delivering results to the business, allowing Whirlpool to exceed customer expectations and bring products to market faster.
Digitisation is empowering people to work more safely too: ranging from wearable devices that safeguard workers' health and safety, by delivering instant alerts to them wherever they are, to drones operating in remote places and dangerous conditions so humans don't have to.
Aside from digitisation, the skills gap is an issue affecting manufacturing companies. However, by embracing the modern workplace - for example, using video or AR for training and worker support - companies can begin to plug the gap while appealing to the next generation of employees.
Beyond the Hype
"With the help of The Cloud, we are changing the fundamental business model ... we're providing an entirely new set of value-based services that transform the home, rather than just replacing bulbs that burn out."
Industry 4.0 disruption is likely to be profound. But how do you move beyond the hype to get to the real bottom- line impact? Start by addressing the following challenges.
• Rapid data growth - machine-to- machine (M2M) connections are creating unprecedented volumes of data. How industrial companies scale to meet this data challenge will be key to success. Cloud is a key solution that can help companies deal with the rapid and unexpected increase in data volumes.
• Desperately seeking data scientists - future competitive advantages will not exist in manual labour skills but in the data literacy of your organisation. Data scientists are the future workforce, and industrial companies will need to compete to attract those with the best talent. Selecting the data platforms that analysts and data scientists like to use will be crucial.
• Data and cyber security - the credibility, security and privacy of information carries great importance for brand integrity and trustworthiness. Google works with industrial companies as well as governmental agencies, global banks and advanced healthcare providers on secure innovations that guard against data and cyber-attacks through end-to-end security built into every layer from data centre to device.
• Integration with legacy architecture - IT departments are addressing the demand to overlay new digital capabilities on top of their existing infrastructure to support the business. Many companies find that cloud simplifies this effort as it delivers a fully managed and unlimited infrastructure, enabling companies to deploy new technologies at speed - and focus on innovation, not problems with their infrastructure.
Continue the Journey
"A 10x goal forces you to rethink an idea entirely. It pushes you beyond existing models and forces you to totally reimagine how to approach it."
Industry 4.0 is a journey that offers long-term value as well as short- term gains. Industrial companies are beginning to implement these technologies with many still in experimental and prototype phase. Instead of a big-bang transformation, most companies are focusing more on developing a progressive roadmap.
Depending on where companies are on the roadmap, it's clear that i4.0 offers significant benefits such as:
• Optimising processes and operations
• Unlocking innovation, enabling new products, services, and data-based business models
• Empowering workforces, enabling global-scale collaboration