Manufacturing’s next act
Industry 4.0 is more than just a flashy
catchphrase. A confluence of trends and technologies promises to reshape the
way things are made.
Mention “Industry 4.0” to most manufacturing executives and you
will raise eyebrows. If they’ve heard of it, they are likely confused about
what it is. If they haven’t heard of it, they’re likely to be skeptical of what
they see as yet another piece of marketing hype, an empty catchphrase. And yet
a closer look at what’s behind Industry 4.0 reveals some powerful emerging
currents with strong potential to change the way factories work. It may be too
much to say that it is another industrial revolution. But call it whatever you
like; the fact is, Industry 4.0 is gathering force, and executives should
carefully monitor the coming changes and develop strategies to take advantage
of the new opportunities.
Coming to terms
Start with some definitions. We define
Industry 4.0 as the next phase in the digitization of the manufacturing sector,
driven by four disruptions: the astonishing rise in data volumes, computational
power, and connectivity, especially new low-power wide-area networks; the
emergence of analytics and business-intelligence capabilities; new forms of
human-machine interaction such as touch interfaces and augmented-reality
systems; and improvements in transferring digital instructions to the physical
world, such as advanced robotics and 3-D printing. (The four trends are not the
reason for the “4.0,” however. Rather, this is the fourth major upheaval in
modern manufacturing, following the lean revolution of the 1970s, the
outsourcing phenomenon of the 1990s, and the automation that took off in the
2000s.)
Most of these digital technologies have been
brewing for some time. Some are not yet ready for application at scale. But
many are now at a point where their greater reliability and lower cost are
starting to make sense for industrial applications. However, companies are not
consistently aware of the emerging technologies. We surveyed 300 manufacturing
leaders in January 2015; only 48 percent of manufacturers consider themselves
ready for Industry 4.0. Seventy-eight percent of suppliers say they are
prepared.
Consider an example of each disruptive trend:
·
Big
data. An African gold mine
found ways to capture more data from its sensors. New data showed some
unsuspected fluctuations in oxygen levels during leaching, a key process.
Fixing this increased yield by 3.7 percent, worth up to $20 million annually.
·
Advanced
analytics. Stronger analysis
can dramatically improve product development. One automaker uses data from its
online configurator together with purchasing data to identify options that
customers are willing to pay a premium for. With this knowledge, it reduced the
options on one model to just 13,000—three orders of magnitude fewer than its
competitor, which offered 27,000,000. Development time and production costs
fell dramatically; most companies can improve gross margin by 30 percent within
24 months.
·
Human-machine
interfaces. Logistics company
Knapp AG developed a picking technology using augmented reality. Pickers wear a
headset that presents vital information on a see-through display, helping them
locate items more quickly and precisely. And with both hands free, they can
build stronger and more efficient pallets, with fragile items safeguarded. An
integrated camera captures serial and lot ID numbers for real-time stock
tracking. Error rates are down by 40 percent, among many other benefits.
·
Digital-to-physical
transfer. Local Motors builds
cars almost entirely through 3-D printing, with a design crowdsourced from an
online community. It can build a new model from scratch in a year, far less
than the industry average of six. Vauxhall and GM, among others, still bend a
lot of metal, but also use 3-D printing and rapid prototyping to minimize their
time to market.
These changes and many others like them are
sure to be far reaching, affecting every corner of the factory and the supply
chain. The pace of change, however, will likely be slower than what we’ve seen
in the consumer sector, where equipment is changed frequently. The coming of
steam power and the rise of robotics resulted in the outright replacement of 80
to 90 percent of industrial equipment. In coming years, we don’t expect
anything like that kind of capital investment. Still, the executives surveyed
estimate that 40 to 50 percent of today’s machines will need upgrading or
replacement.
Lightning in a bottle
To capture the potential, manufacturers can
consider three moves. Primarily, companies can gather more information and make
better use of it. An oil-exploration company collected more than 30,000 pieces
of data from each of its drilling rigs—yet 99 percent of that data was lost due
to problems of data transmission, storage, and architecture. The tiny trickle
of data it did capture was incredibly useful for managers. But so much more can
be done. The executives we surveyed said that correcting these data
inefficiencies should improve productivity by about 25 percent.
With production data now available for the
asking, executives rightly wonder about how to begin. Which data would be most
beneficial? Which data leakages are causing the most pain? Which technologies
would deliver the biggest return on investment for a company, given its unique
circumstances? To sort through the choices, manufacturing leaders can use a
“digital compass” (exhibit). The compass consists of eight basic value drivers
and 26 practical Industry 4.0 levers. Cross-functional discussions that will
help companies find the levers that are best suited to solve their particular
problems.
One kind of lost value
that is sure to interest manufacturers is process effectiveness. Industry 4.0
offers new tools for smarter energy consumption, greater information storage in
products and pallets (so-called intelligent lots), and real-time yield
optimization. Swiss giant ABB used the latter in an Australian cement kiln. A
computer-based system mimics the actions of an “ideal” operator, using
real-time metrics to adjust kiln feed, fuel flow, and fan-damper position. The
company found that the new tools boosted throughput by up to 5 percent.
The bigger picture
Strategists should also take Industry 4.0 into
account as they contemplate the company’s future directions—the second way to
capture the potential. The traditional manufacturing business model is
changing, and new models are emerging; incumbents must be quick to recognize
and react to these new competitive challenges. More specifically, executives
must consider the following options—and watch for others that may be deploying
them. Eighty-four percent of the manufacturing suppliers we surveyed expect new
competitors to enter the market soon.
·
“Platforms,” in which
products, services, and information can be exchanged via predefined streams.
Think open-source software applied to the manufacturing context. For example, a
company might provide technology to connect multiple parties and coordinate their
interactions. SLM Solutions, a 3-D-printer manufacturer, and Atos, an IT
services company, are currently running a pilot project to develop such a
marketplace. Customers can submit their orders to a virtual broker platform run
by Atos. Orders are then allocated to SLM’s decentralized network of production
sites, and subsequently produced and shipped to the customer. Some companies
are also trying to build an “ecosystem” of their own, as Nvidia has in its
graphics-processor business. It provides software developers with resources,
and offers start-ups help to build companies around Nvidia technologies.
·
Pay-by-use and
subscription-based services, turning machinery from capex to opex for
manufacturers. Rolls-Royce pioneered this approach in its jet-engine business;
other manufacturers have followed suit.
·
Businesses that
license intellectual property. Today, many manufacturing companies have deep
expertise in their products and processes, but lack the expertise to generate
value from their data. SAP offers consulting services that build on its
software. Qualcomm makes more than half of its profits from
intellectual-property royalties. Manufacturers might offer consulting services
or other businesses that monetize the value of their expertise.
·
Businesses that monetize
data. The SCiO, a Kickstarter project, is a low-cost, pocket-sized spectrometer
that uses near-infrared technology to assess the composition of materials. It
is expected to cost $250, whereas traditional machines cost upward of $10,000.
Every time a SCiO is used, it contributes to a large database of scanned
materials, helping to make the machine more accurate. To be sure, it is a
consumer product, and not yet ready for industrial use. But industrial models
are on the way. Kaggle, a distributed network of about 270,000 data scientists,
has already helped more than 20 Fortune 500 companies solve their toughest data
problems.
To get the most out of Industry 4.0 technologies, and to get
past square one with a digital business model, companies will have to take a
third step: prepare for a digital transformation. Manufacturers should begin
today to join the hunt for the best digital talent, and think about how to
structure their digital organization. Data management and cybersecurity will be
critical problems to solve. Many companies will find that a “two speed” data
architecture can help them deploy new technologies at the speed required, while
also preserving mission-critical applications.
byCornelius Baur and Dominik Wee
http://www.mckinsey.com/insights/manufacturing/Manufacturings_next_act?cid=other-eml-alt-mip-mck-oth-1506
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