As of this writing, factories of the future are poised to create some 10 million new jobs, seven million of them in analytical services and IT, and companies like IBM and Siemens have invested +$12B developing smart platforms to help manufacturers of every size attain first-mover advantages. These are the trendlines on the emerging topic of Industry 4.0 and how the massive efficiencies it is driving, impact global production.
And before you say "Industrial? What does that have to do with me?", think about any physical product in your life and the path it traveled from the moment it was created, to the moment you acquired it. If it's something you can touch, it went through a production process. And that means the path it traveled can be automated, digitized and optimized. Of course, none of this happens without adapting and upskilling your workforce to understand the crucial role data and insights will play in the future - more on that later.
These are just some of the pressing issues associated with the future of manufacturing. In this article we will cover some of the major concepts, considerations and emerging technologies that have come together to empower Industry 4.0 – a movement that simply could not have occurred at any other time in history.
"Every technological revolution takes about 50 years" - Jack Ma
I recently had the pleasure of wrapping up the research phase of a digital transformation engagement for a $4B refinery client. The team and I have been immersed in research and exposed to an immense level of client complexity, that had us considering everything from mechanical engineering to chemical processes, and from commodities trading on global market exchanges to sophisticated hedging strategies. In an industry where the competition has had a 120-year head start and their revenues rival the size of many countries GDP’s, we’ve been exploring ways to improve the customer experience and out-maneuver the industry. Data, speed, quality, efficiency and security are the levers we can pull, which naturally pointed us towards exploring an Industry 4.0-based strategy. In the process, we got a crash course on how the world makes things.
So, what is Industry 4.0?
To set the stage, let's take two minutes to cover the monumental advancements the world has made in the way we work and create things. The First Industrial Revolution happened at the start of the 1700’s and is widely credited to the invention of the steam-based engine and use of water pressure to power motion. The Second Industrial Revolution had to do with mass production and electricity (think Henry Ford, and the efficiency brought about by the assembly line). The Third Industrial revolution started in 1970 and was characterized by automation and the introduction of computers. And the Fourth Industrial Revolution (Industry 4.0) is the concept of connecting and controlling physical devices via several emerging technologies, to create what’s being termed as "smart facilities," "smart factories," or "smart manufacturing models." Industry 4.0 represents the next phase in the digitization of the manufacturing sector.
Each of the advancements empowering Industry 4.0 merit articles of their own, but at a high-level, the Fourth Industrial Revolution is made possible due to the astonishing rise in data volumes, cloud storage, computational power, connectivity, the emergence of analytics and business-intelligence capabilities; new forms of human-machine interaction such as 3D, or additive manufacturing, touch interfaces and augmented-reality systems; and improvements in transferring digital instructions to the physical world, such as advanced robotics and cyber-physical systems leveraging the Industrial Internet of Things (IIoT), which include station-level sensors, scanners, mobile input devices and actuators to control physical machines. Layer in artificial intelligence (AI) and machine learning (ML) - because what good is an article these days without those buzzwords thrown in? But seriously, those last two advances start to make things like condition monitoring, predictive machine maintenance, and defect reduction of 99.99885% possible. Crucially, these technologies align us to a growing trend we've all been following for some time: Buyer behavior is shifting towards heightened expectations for immediacy, personalization, and order customization.
When it comes to Industry 4.0, the definition of done is attaining maximum product quality and efficiency (down to a batch size of one), with the same near-perfect execution as a traditionally-sized production run.
IIoT and BI reporting are great enablers for visibility.
Every evolution follows logical stages, and the same is true for launching Industry 4.0 initiatives within your organization - being on the path to digital maturity is a pre-requisite. If you're facility is still paper-based, you're going to have to start at the first stage, or computerization. And if you want to reap the rewards that come with being predictive, rather than reactive, you must connect your data silos and centralize your data storage. Beginning your Industry 4.0 journey is not possible without first addressing the first two stages of computerization and connectivity.
Once connectivity is established, IIoT brings together brilliant machines to surface advanced analytics, business intelligence, automation and enable sophisticated production planning. It’s the networking of a multitude of devices connected by communications technologies that results in systems that can monitor, collect, exchange, analyze, and deliver valuable new insights to the cloud, which in turn drive smarter, faster business decisions for industrial companies. Cyber-physical systems, powered by IIoT sensors and actuators at the machine-level, allow smart facilities to pair the virtual and physical worlds to head off problems before they occur, prevent expensive downtime, and model new production scenarios and opportunities with minimal investment. IIoT devices can detect vibrations in a piece of machinery, examine the temperature radiating off a furnace, and enable visibility and control over your industrial systems environment to prevent cyber-attacks - introducing massive innovation and predictability.
After all the systems are connected and the data is flowing, putting Business Intelligence (BI) systems in place helps an enterprise deliver powerful visualizations, uncover insights, suggest potential outcomes and support enhanced decision making.
When combined, IIoT and Business Intelligence reporting enable businesses to be more transparent and predictive by monitoring real-time data and running virtual experiments without having to fail-over real-world locations, servers, or systems – all while increasing adaptability to change and reducing costs. Modeling and prediction on this scale, requires a map, or digital twin, if you will.
The Digital Twin and The Digital Thread
Most research defines the digital twin as a digital replica of different assets, processes and systems in a business. This generic definition is basically correct. However, it's more accurately described as an integrated set of digital replicas or models driven by a rich information model called a digital thread.
Three core focus areas can be associated with the Digital Twin:
• Product: A product digital twin will typically include electronics and software simulations, finite element structural, flow and heat transfer models and motion simulations.
• Production: The production digital twin adds 3D and predictive analytical models to engineer and virtually commission production lines. When the Production model is combined with Product, the
digital twin can drive factory work stations and electronic work instructions.
• Performance: This model enables Big Data insight discovery, analysis and monitoring from in-service products and production systems. Performance analytics quickly identifies product issues disrupting the supply chain, manufacturing process or customer experience. This feature of the digital twin may also include data analysis to discover hidden product issues before they occur; graphical displays to clearly identify potentially problematic configurations; and automated data monitoring to fine-tune operations and provide insight for improving products.
The Digital Thread refers to the communication framework that allows a connected data flow and integrated view of the asset’s data throughout its lifecycle. It equates to mapping the through-line across all three facets of the Digital Twin.
"An investment in knowledge pays the best interest." - Benjamin Franklin
Industry 4.0 is what empowers predictive insights and makes efficient capital employment possible. The traditional industrial model is still based on the principle of decreasing product costs through the volume of products manufactured - the higher the volume produced, the lower the unit costs. Industry has historically been much more focused on optimizing the costs and price of products, and less so with optimizing the capital required to make them – we're working to expand the conversation.
At Rightpoint, we guide our clients to look at capital expenditure investments through the lens of expected Return on Capital Employed. The ROCE calculation helps businesses to determine the validity of making such an investment. There are two metrics required to calculate the return on capital employed - earnings before interest and tax and capital employed. Earnings before interest and tax (EBIT), also known as operating income, shows how much a company earns from its operations alone without regard to interest or taxes. EBIT is calculated by subtracting cost of goods sold and operating expenses from revenues. And Capital Employed is simply the sum of shareholder’s equity and debt liabilities, reviewed to gain an understanding of the total amount of capital utilized to generate profits.
Are you still with me? Great. What you need to know is this: Industry 4.0 investments show near immediate impact on overall returns.
A report by Roland Berger calculates increases in ROCE by +25 PPTS following the transition to Industry 4.0 strategy. Other large infrastructure players at the forefront of the movement such as German conglomerate Siemens, AG report the following results from Industry 4.0 use cases:
• A packaging manufacturer client reduced inventory of finished goods from 3 months to 3 weeks
• Onsite commissioning for a parts manufacturer shortened from 6 months to less than a day
• A leading tool manufacturer increased overall operational productivity by 40%
• A luxury car manufacturer saved 3 million kilowatt hours and reduced their eco emissions by 550 tons - CO2 equivalents per year
PWC's global survey with over 2000 participants from companies in nine major industrial sectors and 26 countries revealed the following:
• Investments in Industry 4.0 are expected to result in $493Bn in increased revenues within the next three years
• Most Industry 4.0 Investments are calculated to show a return on investment within 3 years
• Only 4% of companies surveyed are considered "first movers" based on their Industry 4.0 investments and diversity of projects – and these first movers are 3x more successful in reported revenue increases and cost reductions
All companies are becoming technology companies.
Before you jump to conclude this relentless pursuit of efficiency means the robots are coming for our industrial jobs next, consider a recent Pew Research survey on the future of jobs. All sides have taken positions, but I take a slightly more nuanced view. The industrial companies of the future will need access to a wide variety of skills, including those of data scientists and algorithm architects, no doubt. But what is any human, if not another valuable company asset to be invested in and optimized for efficient output? Industry 4.0, when implemented strategically, should seek to maximize the efficiency of all assets - human and physical.
The issue today is that people who were perfectly suited to their jobs in the past, will find the advances in technology will continue to outpace their abilities and lead to ever-shifting job requirements. Gaps in advanced knowledge, agility, or fit then - should be interpreted as organizational optimization challenges, rather than individual performance challenges. And there’s data to support that organization’s that take this more empathetic view of employee development could find themselves in the best position to attract the workers they’ll need tomorrow. Employer sponsored training just so happens to be the highest valued benefit expectation among millennial workers.
The next evolution we see could very well be in organizational empathy, and how we address workers who are struggling to keep up. And in a knowledge-based economy, organizations that invest in training can market themselves as partners in upskilling and developing their workforce.
Industry 4.0 - No longer just an emerging trend to watch.
The smart facilities of tomorrow will excel at connecting the dots between machines, work flows, people, and materials while interconnecting the work of design, production planning, and distribution. Skilled workers who can bridge the space between virtual and physical production and sophisticated data analysis will be in high demand and accelerate innovation through concepts such as achieving near-zero defects, attaining batch size one and commercializing additive manufacturing.
As your company becomes active in Industry 4.0, you’ll find the benefits go far beyond extending your digital reach or selling new types of products and services. It will establish your company, your employees, and your entire ecosystem of suppliers, partners, distributors, and customers as a fully interconnected, integrated digital network, linked to other networks around the world.
To learn more about how Industry 4.0 is impacting your business sector, and the ways your business will create, operate and service customers tomorrow, contact us.
Rob Hendricks is the Director of Digital Strategy at Rightpoint. Follow him on LinkedIn and Twitter.