ChapterPDF Available

Blockchain: From Industry 4.0 to the Machine Economy

Authors:

Abstract

The extreme automation of our factories is necessary in order to face the Fourth Industrial Revolution. This new industrial paradigm will force our industries to manufacture much shorter and customized series at increasingly competitive prices, even tackling the manufacture of thousands of different configurations of a single base product. In order to achieve this, our production processes must have a flexibility in their configuration that has never been imagined before. This flexibility and ability to adapt automatically to demand are the essence of the Fourth Industrial Revolution and are part of the Western strategy to recover an industrial sector increasingly threatened by the Eastern production of large series at really competitive prices. Based on our participation in more than a dozen proofs of concept in the automotive, aeronautics, agri-food, or energy sectors, we describe the scenarios in which blockchain technology brings the greatest benefits to Industry 4.0. After finishing different experimentations, we carried out an in-depth analysis of the true added value of blockchain in the industry and contrasted our conclusions through interviews with more than 20 people in charge of innovation from different industries. As a result, we have obtained the principal four values of blockchain technology applied to Industry 4.0.
Selection of our books indexed in the Book Citation Index
in Web of Science™ Core Collection (BKCI)
Interested in publishing with us?
Contact book.department@intechopen.com
Numbers displayed above are based on latest data collected.
For more information visit www.intechopen.com
Open access books available
Countries delivered to Contributors from top 500 universities
International authors and editor s
Our authors are among the
most cited scientists
Downloads
We are IntechOpen,
the world’s leading publisher of
Open Access books
Built by scientists, for scientists
12.2%
118,000
130M
TOP 1%
154
4,500
Chapter
Blockchain: From Industry 4.0 to
the Machine Economy
OscarLage
Abstract
The extreme automation of our factories is necessary in order to face the Fourth
Industrial Revolution. This new industrial paradigm will force our industries to
manufacture much shorter and customized series at increasingly competitive
prices, even tackling the manufacture of thousands of different configurations of a
single base product. In order to achieve this, our production processes must have a
flexibility in their configuration that has never been imagined before. This flex-
ibility and ability to adapt automatically to demand are the essence of the Fourth
Industrial Revolution and are part of the Western strategy to recover an industrial
sector increasingly threatened by the Eastern production of large series at really
competitive prices. Based on our participation in more than a dozen proofs of
concept in the automotive, aeronautics, agri-food, or energy sectors, we describe
the scenarios in which blockchain technology brings the greatest benefits to
Industry 4.0. After finishing different experimentations, we carried out an in-depth
analysis of the true added value of blockchain in the industry and contrasted our
conclusions through interviews with more than 20 people in charge of innovation
from different industries. As a result, we have obtained the principal four values of
blockchain technology applied to Industry 4.0.
Keywords: blockchain, DLT, Industry 4.0, trust, cyber security, IoT, IIoT, industrial
systems
. Introduction
The automation of our industries and the relationships of the different agents
in the value chain will allow us to eliminate many repetitive manual processes
with little added value that reduce the competitiveness of the industry [1].
Even the automation of tendering and contracting processes can improve our
competitiveness.
Technologies, such as artificial intelligence, flexible robotics, IoT, or augmented
reality will allow us to advance in the digitalization and optimization of our pro-
cesses, but the great barrier to implement a fully automated production systems and
especially relationships is precisely the lack of trust and security [2].
Trust is the basis of a new research line that in recent months has had an
increasing impact on industrial forums and conferences: blockchain technology.
Blockchain is a distributed ledger of transactions and digital events that have been
executed and shared among participating parties. Each transaction is consensuated,
mathematically linked and stored by the network of participants, thereby achieving
Computer Security Threats
its immutability. Blockchain allows us to operate our procedures and relationships in
the digital environment in a much more safe and reliable way [3].
The next few years will see a profound transformation of industrial processes,
increasing the synchronization between different agents in the value chain, as well
as extreme automation of decision-making, all thanks to the reliability offered by
blockchain. It is even hoped that in the future, it will be able to transform its own
business models, just as in recent decades the Internet has done, which has so far
been the most disruptive technology in history.
In this chapter, we will explain the different use cases and scenarios that we
consider to have greater potential in the future of Industry 4.0, starting first with
generic industrial cases and then analyzing the specific cases of the energy industry.
This selection has been made based on the experience of more than a dozen block-
chain projects in the domain of Industry 4.0.
Next, we will describe the four main generic values that we have discovered after
different proofs of concept with several companies. Finally, we will discuss future
lines of research linked to a new concept such as the machine economy and report
the final conclusions of the chapter.
. Bringing blockchain into Industry .
After carrying out different proofs of concept, mainly associated with manu-
facturing companies, as well as analyzing other experiments carried out by third
parties, we expose in a critical way which would be the main application scenarios
of the blockchain technology and its benefit for industrial companies.
All the analyzed cases have been contrasted through a working meeting with
several companies in order to analyze the real need and utility of them. The fol-
lowing are the use cases that have presented greatest utility in the experimentation
process, responding to real needs not covered today in their ecosystems.
. Traceability
The traceability of industrial goods throughout the entire supply chain, includ-
ing even the life cycle of a product, is one of the applications that according to
consulted experts in the experimentation, as well as the level of maturity of the
technology in this field, is expected to have a greater impact on the short/medium
term of the industry.
For any point in the chain, it is very valuable being able to have visibility of the
destination and use of its components; thanks to this information the participant
in the supply/value chain will be able to (i) analyze the impact of any change in the
design/composition of their product, (ii) anticipate changes in consumption habits/
trends, (iii) avoid manually entering details of the products/components received
by suppliers, (iv) automate complaints and warranties without the need for paper-
work, or even (v) avoid reusing certificates of origin.
We are facing a known need that the big industrial players have wanted to solve
on different occasions [4–7]. The large industries have designed and built trace-
ability systems based on traditional (centralized) architectures and have made them
available throughout their sectorial supply chain. However, these systems have not
been widely accepted, and the only ones that continue to exist are those related to
food safety that is mandatory.
The problem with the previous approaches is that the “giant” of the supply chain
was the one that offered its system to the rest and was in charge of the custody and
coherence of the common database.
Blockchain: From Industry 4.0 to the Machine Economy
DOI: http://dx.doi.org/10.5772/intechopen.88694
This created great reticence because, even if industrial data visibility policies
were implemented so that only agreed users/companies could consume certain
information, there was a “demigod” in the supply chain which, due to the architec-
ture of the system, could have visibility and exploit the information of the entire
value chain. Furthermore, processing the information in a traditional system is very
complicated to guarantee the sovereignty and protection of industrial data [8].
The alternative to create a similar system using traditional technologies is to cre-
ate a clearing house in the supply chain, which has been done in areas such as food
safety and is the only area where traceability is complete throughout the chain [9].
However, in this case the actors only submit information related to food safety and
cannot consult/exploit the information, so the functionality is not full.
Blockchain makes it possible to eliminate these barriers thanks to a distributed
architecture in which there is no “agglutinator” of the contents. Guaranteeing
throughcontract” and cryptography the visibility and use of data (sovereignty
of industrial data) and ensuring that all participants in the network are treated
equally.
However, we have detected that an important point in these projects is to maxi-
mize and automate as much as possible the capture of data, which is why industrial
projects are considering that the Industrial Internet of Things (IIoT) should be the
origin of most of the data that are dumped in the traceability chain. Moreover, this
information should be signed by means of cryptographic hardware in these IIoT
devices, so that the reliability of the data would be extraordinary.
. Interoperability and sovereignty of industrial data
Data and its exploitation are going to be the key in this new industrial paradigm
in which we are entering, promoting even service models based on data [10]. That is
why it is said that data is the new industrial raw material and its sovereignty is a key
point today.
For this reason, several initiatives have arisen that could be called industrial data
platform and that aim to manage and share data of industrial processes, as well as
create value-added services based on them. The most evolved platforms, such as the
one from the international data space consortium, which arose in Germany but is
currently the leading European experimental platform, even include application/
service marketplaces based on industrial data [11].
Perhaps predictive maintenance together with other cases of data analysis and
prescription are the most common and tangible cases today [12], but it is expected
that really these platforms are the basis for innovative proposals of business models
and industrial services that today we cannot even imagine. However, there is cur-
rently a major barrier to the adoption of such platforms, and again it is the reliability
of the industrial data and its protection.
Firstly, there are models for selling information related to industrial processes,
the value of which will depend on the reliability of such data. Therefore, it is one
of the reasons why blockchain begins to be a buzzword in the deliberations on the
future of these platforms, since the more reliable the data, the greater will be its
value in the market.
On the other hand, these platforms must guarantee the sovereignty of industrial
data, for which blockchain architectures/platforms that natively allow confidential-
ity between parties seem the most promising [13]. Current developments include
data encryption models specific to each recipient or set of recipients, such as chan-
nels or private data collection in Hyperledger Fabric v1.4.
However, blockchain and smart contracts will even allow to execute algorithms
and data processing independently, offering the recipient only the result of its
Computer Security Threats
execution [14]. In the future the algorithms can be encoded in a native blockchain
program—the smart contract—in such a way that the owner of the algorithms can
allow the smart contract to access and process their data and generate insights about
them. However, the smart contract provider will not have access to the user’s RAW
data; this will allow them to offer a service based on the data without the customer
having to make a disclosure of such information [15].
After all, it will allow us to put in value the industrial data even without hav-
ing to expose them to a third party, allowing them nevertheless to execute certain
processes on them. This can even be very useful to test/train prediction models of
all kinds without endangering the source data, the result of which can then be a
high-value algorithm for a specific industry.
. IIoT reliability
One of the main benefits of the blockchain application to IIoT in which all the
interviewed experts agree is precisely the decentralized architecture that blockchain
can offer to IoT in general and especially to the industrial ecosystem whose require-
ments are more severe [16].
Currently the architecture of these systems is a classic client/server, which
has a series of barriers and deficiencies for an environment such as IoT/IIoT.It
is expected that the client/server architecture will not be able to respond to the
exponential growth of IIoT and IoT in general; we must bear in mind that we will
face an immense number of devices generating and consuming information from
third parties. To get an idea of this figure, an industrial control machine or device
generates hundreds of millions of data/parameters annually, and inside a medium-
sized factory, we can find tens or hundreds of devices.
The cost of centralized processing and even network equipment and connectiv-
ity to support such cross traffic between different industrial systems (clients) with
dependencies between them would be exponential if all these communications had
to pass through a central system (server). In addition, this central system (server)
would be a major bottleneck for all connected devices and a single point of failure
(SPOF) which, if compromised, could generate a production shutdown of millions
of euros in a single factory.
The trend is also that connected machines and factories interact outside their
business environment with partners, suppliers, and customers. This brings another
set of challenges at the level of identity management and device authentication.
Currently within a factory, existing systems have multiple limitations because
vendors deploy centralized systems that cannot interact safely and reliably with
third parties, even rely on costly and complex in-house or manufacturer-controlled
PKI architectures. In a global economy and in an ecosystem relationship, the
problem and complexity multiply. Thus, blockchain technology has demonstrated
that distributed authentication and identity management are highly efficient and
feasible [17] and can solve identity management problems.
For all these reasons, we are dealing with a new paradigm in which, after moving
from the traditional server model to an elastic cloud server architecture, we must
evolve toward a network of devices in which blockchain is postulated as the main
technological enabler. This paradigm shift would lead us toward decentralized
registers that could become sectorial or even universal.
But the adoption of blockchain in the IIoT ecosystem, and IoT in general, offers
another series of advantages, which although perhaps less disruptive also resolves
some of the challenges and barriers to adoption of IIoT and IoT discussed above.
Blockchain offers us a decentralized record of information, which is also
reliable and unalterable. That is why besides avoiding the single point of failure
Blockchain: From Industry 4.0 to the Machine Economy
DOI: http://dx.doi.org/10.5772/intechopen.88694
of traditional systems, it offers us a more resilient system, not only in terms of
system availability, which increases exponentially by avoiding the single point
of failure, but also in terms of information, since it provides us with a reliable
record [18].
Offering a reliable record of information due to its immutability and ensuring
non-repudiation of operations are an enabling factor for transactions between
unknown devices or different organizations.
As we have mentioned before, one of the biggest barriers to adopting a higher
level of automation in the industrial environment is precisely the mistrust of data,
especially data from third parties. Although the industries themselves in many cases
do not rely on automating some critical processes based on their own information
due to potential sabotages or failures, it is impossible to think that they will do it
based on third party information sources.
Blockchain offers reliability over our own information—thanks to the integrity
and strong authentication of our issuers—as well as over information provided
by third parties. Such reliability will allow greater automation and avoid many of
today’s low value-added manual processes that are provoked by a lack of confidence
in the data.
The decentralization of information and its immutability are also a major advan-
tage for critical industrial infrastructures (chemical, energy, etc.). According to
the latest recommendations for critical infrastructure protection like the European
Critical Infrastructure Protection (ECIP) or NIST Cybersecurity Framework, they
should be able to guarantee the custody of their data in the case of any fortuitous
incident (natural disaster, system failure) or deliberate incident (physical and/or
logical attack) for forensic analysis.
Nowadays, this custody of information in case of cyber incidents is practically
impossible to achieve since the attacker usually stays inside the system 146days
before executing the attack or being detected [19], and one of its objectives is to
meticulously study the infrastructure not only to maximize its impact but also to be
able to erase any trace once the cyberattack is executed.
This is why traditional backup systems and data replicas are usually eliminated
during the attack; however, if the infrastructure was connected to a blockchain
network, the attacker would have to completely erase each and every one of the
nodes of the distributed blockchain network to make their footprints disappear,
something totally unthinkable. In fact, during all the time that the attacker remains
investigating, the infrastructure is erasing his trail, so a simple periodic comparison
of the logs of the infrastructure itself against its unalterable copy in blockchain
could alert us of the existence of an intruder in the network or detect any change in
the machine code of our industrial devices.
However, although blockchain is postulated as the solution to IIoT’s architectural
design problems, it must be kept in mind that current solutions and ledgers must
evolve in order to respond to the needs of IIoT devices in real time (low latency,
bandwidth, message size). That is why in the blockchain, ecosystem begins to
emerge new developments and technologies aimed at overcoming this barrier
[2022]. If this is achieved, the potential market and technological impact could
lead to the long-awaited paradigm shift we were talking about earlier.
. A new energy industry
In the last years, the energy sector has initiated a major transformation of the
electricity grid, the industrial infrastructure responsible for transporting and
distribution electricity from the generation plants to the consumer. The smart grid
Computer Security Threats
is a much more automated and resilient grid and offers unprecedented levels of
reliability and service continuity.
. Energy sector considerations regarding the previous section
The smart grid itself is a network of IIoT devices and is also considered a critical
infrastructure, so everything mentioned above about the advantages of using block-
chain in IIoT devices obviously applies directly to this industry.
Traceability is also relevant in the energy industry; therefore, at the end of 2018
ACCIONA announced, in collaboration with Tecnalia, the first proof of concept
for the use of blockchain to trace the renewable origin of energy. In this case the
fundamental objective of traceability is to guarantee the renewable origin of the
energy and thus differentiate the energy generated in a sustainable way.
Even so, since the initial experimentation, there are several utilities that have
made different proofs of concept, and we must distinguish between (i) the trace-
ability of energy from its point of origin, with information collected from the IIoT
itself (smart meters of the power plant) or (ii) the traceability made retrospectively
based on the data that the utility itself (not the machines) introduces in the block-
chain. The first one gives a total guarantee and trustworthiness; in the second case,
the reliability is given by the utility itself and does not have a superior value than a
report signed by the energy company itself.
Equally important is the interoperability and sovereignty of the data in a smart
grid in which different operators and manufacturers collaborate with a common
industrial objective—the grid resilience—but with competing business objectives.
. Prosumers and the value of energy data
We are facing a decentralization of energy production in part due to a new
participant in the ecosystem, the prosumer [23]. Prosumers, unlike a traditional
consumer—who simply consumes the energy provided by the smart grid—also are
able to produce its own energy (Figure ).
The proliferation of prosumers in the energy ecosystem is going to cause that
these consumers will have more information and detail than the utility itself, some-
thing unthinkable until now where every kilowatt consumed by a home or company
is accounted by the energy distributor.
These prosumers may be consuming energy without the utility being aware of it,
but they must provide service to the user if it punctually needs more energy than is
able to produce, either because of an increase in consumption, because the user has
photovoltaic generation on the roof but the day is cloudy, etc.
Figure 1.
Smart grid architecture and energy flows including prosumers.
Blockchain: From Industry 4.0 to the Machine Economy
DOI: http://dx.doi.org/10.5772/intechopen.88694
In fact, these users have critical information to operate the system that will be
extremely valuable for the stakeholders of the energy system in order to opti-
mize their processes and ensure the stability of the network. It will allow them
also to predict energy demand more accurately, avoiding deviations in the daily
markets, improving the balance of the grid, and so on. Even in the case of large
consumers, some companies offer optimized energy savings based on a baseline
measurement.
However, the user is increasingly aware of the value of these data and not only
because of their impact on the energy ecosystem. Starting from the detail of energy
consumption, it is possible to infer a quite exhaustive profile of the user and, for
example, to carry out a very good segmentation for marketing impacts.
The following transformation of the energy sector could be precisely based on
the exploitation of these data, and thanks to blockchain, users could have control of
them and therefore of their privacy.
. The core value of blockchain in the industry
After analyzing the results of different proofs of concept and the benefits
provided, we could say that blockchain can bring a number of differential features
to Industry 4.0.
Perhaps the most popular is the decentralization of processes and business
models. Blockchain provides by definition the intermediation between two parties
in a reliable way [24] that is why many processes and organizations whose main
value is the intermediation between parties can be optimized thanks to blockchain
technology. We will therefore see intermediaries that adopt technology to be more
efficient and robust, thus being able to offer a better service at more competitive
prices or consortiums of companies that invest in creating themselves platforms to
manage their relationships without depending on current intermediaries.
At the same time, blockchain offers an unalterable record of the history of any
asset or industrial good, so traceability on that record is natural for blockchain
technology. In addition, this record can be shared with third parties in an exercise
of transparency of their processes.
Blockchain offers a really efficient synchronization of processes; it provides us
with a single consensuated vision of the information related to industrial assets and
processes, something really important in cases where different players and informa-
tion systems must be coordinated to achieve a common industrial objective.
It is a perfect synchronization technology, resilient to network microcuts or
failures of the systems involved in the industrial process. These usual deficiencies
of the traditional technologies generate incoherencies in the data and consequently
incorrect decision-making due to a bad synchronization of the information shared
between the collaborating systems.
Finally, we should emphasize the blockchain capacity for process automation
thanks to being a reliable source of information by offering a synchronized, con-
sensual, and unalterable record on which we can also have a non-repudiation of
the information, as each participant signs each of their transactions as if it were a
digital contract in pdf.
As we have already commented, automating our industrial processes based on
information from third parties is really risky if the source is not reliable. Unlike the
technologies that we usually handle, blockchain offers us that certainty, even an
evidence that can be used to claim a third party if the recorded information is not
real or accurate.
Computer Security Threats
. Machine economy
The previous sections focused on explaining the results of proofs of concept and
analysis of the applicability of blockchain in Industry 4.0, mainly in the improve-
ment of processes and the creation of new products/services. In the current section,
the focus will be to introduce a new economic paradigm that arises from the merger
of industry, economy, and disruptive potential of blockchain, an area that precisely
because it is still very experimental opens different lines of future research, the
machine economy.
To understand the machine economy, we must first understand how we are
facing a new paradigm of decentralization and disintermediation, which is
already a small phenomenon in the world of currencies and will soon be a real-
ity in many other areas. Entities such as eBay or Amazon already have to face
the competition of OpenBazaar, an open-source blockchain software that offers
near the same value as those companies. At the same time, the highly appreciated
platform business models such as AirBNB or UBER are reflecting on what value
to contribute beyond intermediation; otherwise they will be disintermediated by
blockchain technology.
But the real potential of blockchain is not just to eliminate intermediaries; really
these “cryptocurrencies” are digital tokens that represent a value [25]. Obviously
the simplest application has been to create cryptocurrencies in which the blockchain
issued those tokens instead of a central bank, but those tokens can represent what-
ever we want. Those tokens can represent the possession of a house or the identity
of a person and all their history, but they can also represent the right to consume a
service, to make decisions about the future of an organization, etc.
And this is where the real disruptive change begins; with the so-called crypto
economy or token economy, an economy dominated by these tokens that is crypto-
graphically protected by the blockchain will change the rules of the game and allow
the total decentralization of the economy. In this new economy, the value will be
tokenized, and these tokens will represent very different values as we commented.
This token economy is already emerging, it started with the cryptocurren-
cies, and we have also lived a new paradigm in the search for funding for business
projects, in which under the name of initial coin offering (ICO) entrepreneurs with
disruptive ideas find a new blue ocean of funding [2628]. These entrepreneurs sell
tokens that in many cases represent a service of that startup in the future, some-
thing similar to crowdfunding but totally globalized and without intermediaries
who must manage those rights of future use of a platform. But these projects are
going one step further than a simple decentralized crowdfunding; they are even
devising new types of autonomous and decentralized organizations known as
decentralized autonomous organizations (DAO) [29].
These organizations are created and financed by the community in order to offer
an autonomous service thanks to blockchain. Imagine that we are tired of Google,
Twitter or Facebook continues to earn money with our personal data, but we do
not want to lose its functionality. Blockchain allows the community to finance and
launch a new social media, or any other service, but without being managed by any
for-profit entity, nor has a company registration number (CRN) in any country. It
will be a virtual organization offering the service and relying on the community to
perform those tasks that cannot perform by itself as investment decisions or strat-
egy. So the community itself will run this virtual organization in a format similar to
how a federation of worker cooperatives works.
This organization will be able to charge for its services and reinvest all the ben-
efits in the development of improvements, new functionalities, etc. These organiza-
tions could also share part of those benefits with their promoters and community or
Blockchain: From Industry 4.0 to the Machine Economy
DOI: http://dx.doi.org/10.5772/intechopen.88694
simply offer these users free services. In this type of organizations, the “shareholder
pact” has been programmed since its creation, “code is law.” In fact, the change of
these rules will have to be agreed by the community of users.
Machine economy is precisely to transfer this concept of DAO to the machines;
we could be in front of a new evolution of the IoT.Let us imagine, for example,
something we all know, a car. In a few years, it would not be difficult to imagine that
there are a significant number of users who do not have a car and that there is a fleet
of cars at their disposal.
These cars could be sovereigns; they could have their own identity, history, and
even their own “wallet” to store digital value (tokens) that they will use to manage
and store the value they receive by offering their transport services to passengers, as
well as to pay for their recharges, tolls, cleaning, and maintenance.
In this way, we turn this car into an economic agent itself, with its own economy,
self-sufficient, and even with its own business model. Whats more, this car would
foster new micro-service ecosystems around it.
Let us go a little deeper into tokenomics and the machine economy. These cars
could be offered by a company, in a similar way to the traditional model. But thanks
to blockchain, this could be financed as a kind of crowdfunding in which a DAO
would be created with the initial investment, and gradually it would increase the
fleet, grow geographically, and even replace old vehicles. The DAO would also be
able to offer truly affordable costs to its customers and allow token owners gover-
nance, decision-making, and profit-sharing.
In this way, transport could be outsourced to the machines; the same outsourc-
ing exercise could be carried out to other machines—robots—for the washing of
these cars, their maintenance, carried out by robots and even the printing of parts
on demand, the rubbish collection service, etc.
The token economy aims to return the power to the citizenry, and thanks to
being a fully digital economy, machines can be active agents of it, thus generating
their own economy, the economy of machines.
However, nowadays the machine economy is mainly an experimental concept
that requires solving different challenges. Some of these research challenges are (i)
secure hardware-based digital identity, (ii) interoperability an data sovereignty,
(iii) more scalable and computationally efficient DLT architectures, or (iv) distrib-
uted machine governance model, between others.
. Conclusions
In this chapter we have analyzed the general applicability of blockchain technol-
ogy to the new paradigm of the Fourth Industrial Revolution, and due to its par-
ticular peculiarities, we have made a brief analysis of the specific case of the energy
sector.
Based on our analysis and experimentation, we have selected three main lines of
generic application for Industry 4.0: (i) traceability, (ii) interoperability and sover-
eignty of industrial data, and (iii) IIoT reliability. Moreover, in the case of energy,
beyond exposing any particularity linked to IIoT or energy traceability, the analysis
has focused on the prosumers and the value of their data in a new decentralized
energy ecosystem.
As an outstanding contribution, the conclusions on the real value of blockchain
in the industry should be pointed out, where abstracting from any specific scenario,
the value of blockchain technology in this sector is analyzed in a universal way. The
results are four main values of the technology, which in addition to being really
the core of the analyzed cases could become applicable in other sectors. These
Computer Security Threats

differential features can be very useful to detect in an agile way if the application of
the blockchain technology in a project contributes with a differential value in front
of the rest of technologies of the state of the art.
Finally, we end with a reflection on a new paradigm that we have discovered
during our research, and that may open different lines of future research, the
Machine Economy.
Acknowledgements
This work was performed with the financial support of the ELKARTEK
2018 (CyberPrest project, KK-2018/00076) research program from the Basque
Government.
Author details
OscarLage
TECNALIA, Parque Científico y Tecnológico de Bizkaia, Spain
*Address all correspondence to: oscar.lage@tecnalia.com
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms
of the Creative Commons Attribution License (http://creativecommons.org/licenses/
by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.

Blockchain: From Industry 4.0 to the Machine Economy
DOI: http://dx.doi.org/10.5772/intechopen.88694
References
[1] Schuh G, Potente T,
Wesch-Potente C, Weber AR,
Prote JP.Collaboration mechanisms
to increase productivity in the context
of Industries 4.0. Procedia CIRP.
2014;:51-56
[2] Marques M, Agostinho C, Zacharewicz G,
Jardim-Gonçalves R.Decentralized
decision support for intelligent
manufacturing in Industry 4.0. Journal
of Ambient Intelligence and Smart
Environments. 2017;(3):299-313
[3] Drescher D.Blockchain Basics.
Berkeley, CA: Apress; 2017
[4] Banterle A, Stranieri S.The
consequences of voluntary traceability
system for supply chain relationships.
An application of transaction
cost economics. Food Policy.
2008;(6):560-569
[5] Maro S, Steghöfer JP, Staron M.
Software traceability in the automotive
domain: Challenges and solutions.
Journal of Systems and Software.
2018;:85-110
[6] Farris M, Wittmann C,
Hasty R.Aftermarket support and
the supply chain: Exemplars and
implications from the aerospace
Industry. International Journal of
Physical Distribution and Logistics
Management. 2005;(1):6-19
[7] Heyder M, Theuvsen L,
Hollmann-Hespos T.Investments in
tracking and tracing systems in the food
Industry: A PLS analysis. Food Policy.
2012;(1):102-113
[8] Kagermann H,Anderl R,
Gausemeier J, Schuh G,
Wahlster W.Industries 4.0in a Global
Context: Strategies for Cooperating
with International Partners. New York:
Herbert Utz Verlag. 2016. pp. 19-23
[9] Folinas D, Manikas I, Manos B.
Traceability data management for
food chains. British Food Journal.
2006;(8):622-633
[10] Kagermann H.Change through
digitization—Value creation in the
age of Industry 4.0. In: Management
of Permanent Change. Wiesbaden:
Springer Gabler; 2015. pp.23-45
[11] Otto B, ten Hompel M,
Wrobel S.International data spaces.
In: Digital Transformation. Berlin,
Heidelberg: Springer Vieweg; 2019.
pp.109-128
[12] Lee J, Kao HA, Yang S.Service
innovation and smart analytics for
Industry 4.0 and big data environment.
Procedia CIRP. 2014;:3-8
[13] Zheng Z, Xie S, Dai H, Chen X,
Wang H.An overview of blockchain
technology: Architecture, consensus,
and future trends. In: 2017 IEEE
International Congress on Big Data
(BigData Congress). IEEE; 2017, June.
pp.557-564
[14] Zyskind G, Nathan O,
Pentland A.Enigma: Decentralized
computation platform with
guaranteed privacy. arXiv preprint
arXiv:1506.03471; 2015
[15] Roos, J. Identity Management on
the Blockchain. Chair of Network
Architectures and Services,
Department of Computer Science,
Technische Universität München.
2018. p. 105. https://doi.org/10.2313/
NET-2018-11-1_14
[16] Breivold HP, Sandström K.Internet
of things for industrial automation--
challenges and technical solutions. In:
2015 IEEE International Conference
on Data Science and Data Intensive
Systems. IEEE; 2015. pp.532-539
Computer Security Threats

[17] Jacobovitz O.Blockchain for
Identity Management. The Lynne and
William Frankel. Beer Sheva: Center
for Computer Science Department
of Computer Science. Ben-Gurion
University; 2016
[18] Boudguiga A, Bouzerna N,
Granboulan L, Olivereau A, Quesnel F,
Roger A, etal. Towards better
availability and accountability for iot
updates by means of a blockchain.
In: 2017 IEEE European Symposium
on Security and Privacy Workshops
(EuroS&PW). IEEE; 2017. pp.50-58
[19] Rusi T, Lehto M.Cyber threats
mega trends in cyber space. In: ICMLG
2017 5th International Conference
on Management Leadership and
Governance. Academic Conferences and
Publishing Limited; 2017. p.323
[20] Novo O.Blockchain meets IoT:
An architecture for scalable access
management in IoT.IEEE Internet of
Things Journal. 2018;(2):1184-1195
[21] Sharma PK, Chen MY, Park JH.A
software defined fog node based
distributed blockchain cloud
architecture for IoT.IEEE Access.
2017;:115-124
[22] Dorri A, Kanhere SS, Jurdak R.
Towards an optimized blockchain for
IoT.In: Proceedings of the Second
International Conference on Internet-
of-Things Design and Implementation.
ACM; 2017, April. pp.173-178
[23] Jacobs SB.The energy prosumer.
Ecology Law Quarterly. 2016;:519
[24] Nakamoto S. Bitcoin: A Peer-to-Peer
Electronic Cash System. 2008. http://
bitcoin.org/bitcoin.pdf
[25] Hargrave J, Sahdev N,
Feldmeier O.How value is created
in tokenized assets. In: Blockchain
Economics: Implications of Distributed
Ledgers-Markets, Communications
Networks, and Algorithmic Reality.
ICCS 2018. Cambridge MA. Vol. 1. 2018.
p.125
[26] Catalini C, Gans JS.Initial Coin
Offerings and the Value of Crypto
Tokens (No. w24418). Cambridge, MA:
National Bureau of Economic Research.
2018
[27] Adhami S, Giudici G,
Martinazzi S.Why do businesses go
crypto? An empirical analysis of initial
coin offerings. Journal of Economics
and Business. 2018;:64-75
[28] Feng C, Li N, Lu B, Wong MH,
Zhang M.Initial Coin Offerings,
Blockchain Technology, and White
Paper Disclosures; 2018
[29] Hsieh YY, Vergne JP.Bitcoin and
the rise of decentralized autonomous
organizations. Journal of Organization
Design. 2018;(1):14
... With a distributed platform, time stamp entry fraud is reduced, and user information is stored in a network-wide, immutable ledger using intelligent contacts. Blockchain helps reduce system costs by eliminating manual coordination and management processes between multiple isolated ledgers [28]. ...
... Artificial intelligence, the IoT, machine learning, cloud computing, cybersecurity, and adaptive robotics, among other essential technologies required for Industry 4.0 transformation, produce significant changes in organizational business operations. Industry 4.0, with its autonomous cyber-physical production systems and intelligent goods, needs comprehensive methods and will result in long-term changes in industrial manufacturing [28]. Digitization has an influence on all global systems as well as the most current forms of civilization. ...
... Previously they used centralized servers to store their data which are costly to deploy and maintain. Blockchain is a decentralized directory that provides a way to power industries and a more transparent system that enables a more trusted and secure environment [28]. Blockchain is an immutable ledger that enables near-real-time data replication across a network of business partners. ...
Chapter
Full-text available
In this competitive world, businesses are constantly looking for options or environments that can give them access to real-time data and insights to make smarter, faster decisions about the business, which in turn can ultimately boost the efficiency and profitability of the entire operation. In addition, it should empower businesses to address potential threats and issues before they become more significant problems. Moreover, failing to adopt the technology of the Fourth Industrial Revolution (Industry 4.0) caused companies to fall behind, as their operations were not digitized enough to match competitors. Thus, to stay ahead of the competition, companies need to use Industry 4.0. Industry 4.0 is often used to point to business and chain manufacturing development. Artificial intelligence (AI), the Internet of things (IoT), Big data, and Blockchain are examples of Industry 4.0 technologies that have the potential to open up new opportunities in a variety of sectors, most notably the industrial and logistics industries. Blockchain can be incorporated to improve security, privacy, and data transparency for small and large enterprises. The chapter thus discusses the industry 4.0 concepts at length. It presents the topic's background information and discusses the need for Industry 4.0. The chapter also briefly reviews the various related technologies and explores the role of Blockchain in Industry 4.0 and Blockchain for sustainable development. The chapter then presents some examples of what manufacturing may accomplish. It is realized that the chapter strongly assists the users in understanding the concepts and gaining insights into Industry 4.0. It is also discovered that the chapter facilitates users to familiarize themselves with the newest research on Industry 4.0 and identify future research directions.KeywordsIndustry 4.0BlockchainArtificial intelligenceBigdataSupply chainSmart factory
... This can be seen in a multitude of application areas such as manufacturing where machines in a factory can sell their services during downtime, communicate with other machines in the factory and self-maintain themselves by re-ordering spare parts, all without the need for human presence [9]. In the preceding example a machine is turned into an economic agent which facilitates microtransactions between other agents and entities to create a microservice ecosystem in which services become commoditized [10]. Hence, each machine will have its own identity, history and (bank) account to store digital tokens to pay for services e.g., replacement parts. ...
... These are further detailed below. This paper considers all attributes mentioned in publications pertaining to the machine economy [8,10,13]. ...
... Each machine will have its own operating language and therefore the system must allow different machine systems to connect and interact with each other seamlessly, for data exchange to take place. This requires certain standards to be created within each specific industry e.g., manufacturing interface standard for machine equipment [8,10]. ...
Article
Full-text available
Blockchain Technology has gained prominence since 2008 with trust, reliability, speed, and transparency becoming major advantages. It has also been applied and researched within a multitude of industry applications ranging from manufacturing to financial transactions through to real estate. In addition to Artificial Intelligence (AI) and Internet of Things (IoT), Distributed Ledger Technology (DLT) such as blockchain serves as the backbone to the Machine Economy, which is a relatively recent concept in which machines can communicate and exchange data with each other autonomously, allowing manufacturing companies to become more competitive. However, using blockchain for exchanging large volumes of data requires significant fees and energy due to its use of miners to validate transactions which is a barrier for manufacturing companies to implement. Directed Acyclic Graph (DAG), which is a different type of DLT is an example of an alternative to blockchain which aims to overcome most of the problems currently on the blockchain and promises to enable fee-less transactions with much lower power requirements than blockchain. In this paper, the authors explore the DLT aspect of the machine economy within the manufacturing context. Firstly, the enabling DLT technical attributes of the machine economy are analysed. This is followed by an evaluation of all DLT’s, focusing on the challenges and benefits of each alternative. Following on from this, a cross comparison of each DLT type is done which leads into a discussion and future directions to be drawn.
... Digital assets in this context refer to the data, tokens, and smart contracts that leverage AI and blockchain integration (Pfeiffer and Bugeja, 2021). Blockchain facilitates the tokenization of physical and digital assets (Lage, 2019). AI algorithms can analyze patterns and behaviors related to tokenized assets, providing insights for better asset management and investment decisions (Rathore, 2023). ...
... 7. Dynamic Pricing Mechanisms: Employ AI to develop dynamic pricing mechanisms that adjust in real-time based on supply, demand, and other relevant factors. This flexibility can lead to more efficient allocation of resources and encourage responsible energy consumption (Lage, 2019). 8. Cybersecurity and Privacy: Use AI for enhancing cybersecurity measures to safeguard the integrity of the blockchain and protect sensitive energy-related data (Salama et al., 2023). ...
Article
Full-text available
Artificial Intelligence (AI) algorithms can be employed to enhance the security of the blockchain networks in the era of industry 4.0. Smart contracts, powered by blockchain, can be developed by using the AI capabilities. These contracts can execute themselves based on predefined conditions, automating various processes and reducing the need for intermediaries. Blockchain provides a transparent and immutable ledger for supply chain transactions. AI can be integrated to analyze this data, providing insights into the entire supply chain. This helps in tracking and tracing products, ensuring authenticity, and optimizing the supply chain based on data-driven decisions. AI algorithms can be employed to analyze data from the manufacturing process recorded on the blockchain. This allows for predictive maintenance and quality control, helping to identify and address issues before they result in defects or downtime. AI and blockchain can work together to secure the massive amount of data generated by IoT devices in an Industry 4.0 setting. Blockchain ensures the integrity and immutability of IoT data, while AI can analyze this data for insights and optimization. AI and blockchain can facilitate the creation of decentralized energy grids where AI algorithms optimize energy distribution and blockchain ensures transparent and secure energy trading through smart contracts. AI and blockchain can support decentralized and collaborative manufacturing networks where different entities can securely and efficiently collaborate on production processes. Blockchain enables individuals or organizations to securely monetize their data. AI can help analyze and determine the value of data, ensuring fair compensation in tokenized ecosystems. In this paper, applications of AI-Powered Blockchain Technology in Industry 4.0 is reviewed and discussed and future research works are also suggested. As a result, efficiency, transparency, and security across various industrial processes can be enhanced by analyzing the recent achievements in AI-Powered Blockchain Technology in Industry 4.0.
... Üretim süreçlerinin konfigürasyonundaki esneklik ve talebe otomatik olarak uyum sağlama yeteneği, dördüncü sanayi devriminin özüdür (Lage, 2019). Birbirinden farklı verileri yakalamak, güvenli bir şekilde iletmek ve analiz etmek, dinamik ve sürekli olarak yeni optimizasyon süreçlerini tetikleyen rehberli kararlar almak için esastır. ...
Article
Full-text available
Industry 4.0 has a significant impact on production, which is the crucial business function. Production and logistics are two distinct activities that cannot be separated from one another. The supply chain has become a critical component of boosting a company's efficiency and competitiveness. To achieve this, a knowledge- based, technology-based plan for the scope and effect of logistics technologies have to be implemented. Businesses seeking to stay up with today’s modern industry's fundamental developments confront worldwide competition. In light of this, Industry 4.0 is presently regarded as the most important idea for overcoming these production difficulties. This compilation research intends to integrate multiple methodologies in a Logistics 4.0 framework to generate a fresh image of the logistics industry's digitization progress. First, a brief history of industrial revolutions was explored, followed by a discussion of the notion of Industry 4.0 and finally the term Logistics 4.0. As digitalization relies on the collaboration of all technical bases to give the desired answer, existing solutions supporting Logistics 4.0 are outlined by technologies: additive manufacturing/3D printing, augmented reality, big data analytics, blockchain technology, cloud services, collaborative planning forecasting and replenishment, drones , electronic data interchange, e-procurement, enterprise resource planning, global positioning systems and general packet radio services (GPS and GPRS), pick-to-light and pick-by-voice, radio frequency identification, sales and operations planning, internet of things, transportation management system, warehouse management system, wearable technologies and digital twin. For scholars, this paper drew a conceptual framework based on the historical development of industrial revolutions and reviewed the literature to examine the impact and role of Industry 4.0 throughout the supply chain management. For people interested in working in the subject of Industry 4.0 and Logistics 4.0, the research provides a unique literary viewpoint in Turkish.
... Üretim süreçlerinin konfigürasyonundaki esneklik ve talebe otomatik olarak uyum sağlama yeteneği, dördüncü sanayi devriminin özüdür (Lage, 2019). Birbirinden farklı verileri yakalamak, güvenli bir şekilde iletmek ve analiz etmek, dinamik ve sürekli olarak yeni optimizasyon süreçlerini tetikleyen rehberli kararlar almak için esastır. ...
Article
This research explores the role of Blockchain Technology (BCT) integrated with Reverse Supply Chain Networks (RSCN) and evaluates the relationship between BCT and sustainability performance in multi-industries. A qualitative research design was employed to develop a conceptual framework for BCT in RSCN for multi-industries. This research collected and analysed primary and secondary data from four case studies as focal actors. These focal actors are from industries in Jordan, namely food, pharmaceuticals, electronics, and toys. These actors are lead firms in their RSCNs and have experience working with RSCNs and technology applications such as BCT. Primary data were acquired from interviews with managers working in various industries. Analysis of secondary data has identified two types of the key BCT-influencing themes: internally focused and externally focused BCT-integrated drivers of RSCNs. The analysis also identified how they leverage sustainability performance improvements, including their use of RSCN approaches and features. This research is one of the few attempts to explore BCT integrated into RSCN for better sustainability performance through understanding the implementation and evaluation that contributes to the theoretical and practical knowledge of supply chains within emerging economies. All types of actors-as-stakeholders involved with national programs and projects can adopt the new framework that provides the changes required for RSCN. The key findings contribute to the field of RSCN where the adoption of BCT as a broad-based strategy to attain sustainability goals and reverse chain activities along the supply chain is a goal.
Article
Full-text available
This review gives concise information on green technology (GT) and Industrial Revolution 4.0 (IR 4.0). Climate change has begun showing its impacts on the environment, and the change is real. The devastating COVID-19 pandemic has negatively affected lives and the world from the deadly consequences at a social, economic, and environmental level. In order to balance this crisis, there is a need to transition toward green, sustainable forms of living and practices. We need green innovative technologies (GTI) and Internet of Things (IoT) technologies to develop green, durable, biodegradable, and eco-friendly products for a sustainable future. GTI encompasses all innovations that contribute to developing significant products, services, or processes that lower environmental harm, impact, and worsening while augmenting natural resource utilization. Sensors are typically used in IoT environmental monitoring applications to aid ecological safety by nursing air or water quality, atmospheric or soil conditions, and even monitoring species’ movements and habitats. The industries and the governments are working together, have come up with solutions—the Green New Deal, carbon pricing, use of bio-based products as biopesticides, in biopharmaceuticals, green building materials, bio-based membrane filters for removing pollutants, bioenergy, biofuels and are essential for the green recovery of world economies. Environmental biotechnology, Green Chemical Engineering, more bio-based materials to separate pollutants, and product engineering of advanced materials and environmental economies are discussed here to pave the way toward the Sustainable Development Goals (SDGs) set by the UN and achieve the much-needed IR 4.0 for a greener-balanced environment and a sustainable future. Graphical abstract
Article
Full-text available
Bitcoin represents the first real-world implementation of a “decentralized autonomous organization” (DAO) and offers a new paradigm for organization design. Imagine working for a global business organization whose routine tasks are powered by a software protocol instead of being governed by managers and employees. Task assignments and rewards are randomized by the algorithm. Information is not channeled through a hierarchy but recorded transparently and securely on an immutable public ledger called “blockchain.” Further, the organization decides on design and strategy changes through a democratic voting process involving a previously unseen class of stakeholders called “miners.” Agreements need to be reached at the organizational level for any proposed protocol changes to be approved and activated. How do DAOs solve the universal problem of organizing with such novel solutions? What are the implications? We use Bitcoin as an example to shed light on how a DAO works in the cryptocurrency industry, where it provides a peer-to-peer, decentralized, and disintermediated payment system that can compete against traditional financial institutions. We also invited commentaries from renowned organization scholars to share their views on this intriguing phenomenon.
Article
Full-text available
The Internet of Things (IoT) is stepping out of its infancy into full maturity and establishing itself as part of the future Internet. One of the technical challenges of having billions of devices deployed worldwide is the ability to manage them. Although access management technologies exist in IoT, they are based on centralized models which introduce a new variety of technical limitations to manage them globally. In this paper, we propose a new architecture for arbitrating roles and permissions in IoT. The new architecture is a fully distributed access control system for IoT based on blockchain technology. The architecture is backed by a proof of concept implementation and evaluated in realistic IoT scenarios. The results show that the blockchain technology could be used as access management technology in specific scalable IoT scenarios.
Article
Full-text available
Initial Coin Offerings (ICOs) allow companies and entrepreneurs to raise money through cryptocurrencies, in exchange for a ‘token’ that can be sold on the secondary market or used in the future to gain products or services. In the first semester of 2017 only, according to media observers, more than $ 1.2 billion were raised through ICOs, mainly from technology-driven companies in the seed or startup phase. The ICO surge obviously attracted the attention of both investors and market authorities, given the analogies with Initial Public Offerings (IPOs). The debate about protecting investors from frauds and speculation bubbles as well as hampering money laundering and other illegal practices through cryptocurrencies is gaining momentum, while the ICO potential benefits (e.g. reducing the financing gap for new technology ventures, allowing the design of ‘smart contracts’ with pledgers and opening secondary markets for exits and trade) are still far to be fully investigated. In this work we provide the first comprehensive description of the ICO phenomenon analyzing a sample of 253 offerings occurred from 2014 to August 2017. We find that the success rate is quite high (81.0%); projects are originated mainly in the US, Russia, UK and Canada. The project objective is predominantly related to fintech services, to the development of a blockchain, or to the issuance of new cryptocurrencies. ICO tokens grant contributors the right to access to platform services in 68% of the cases, governance powers in 24.9% of the cases ad profit rights in 26.1% of the cases. The secondary market for ICO tokens is quite liquid on the first day of trading, and the initial underpricing is positive (median value +24.7%).
Article
Full-text available
The recent expansion of the Internet of Things (IoT) and the consequent explosion in the volume of data produced by smart devices have led to the outsourcing of data to designated data centers. However, to manage these huge data stores, centralized data centers such as cloud storage cannot afford auspicious way. There are many challenges that must be addressed in the traditional network architecture due to the rapid growth in the diversity and number of devices connected to the internet, which is not designed to provide high availability, real-time data delivery, scalability, security, resilience, and low latency. To address these issues, this paper proposes a novel blockchain-based distributed cloud architecture with a Software Defined Networking (SDN) enable controller fog nodes at the edge of the network to meet the required design principles. The proposed model is a distributed cloud architecture based on blockchain technology, which provides low-cost, secure, and on-demand access to the most competitive computing infrastructures in an IoT network. By creating a distributed cloud infrastructure, the proposed model enables cost-effective high-performance computing. Furthermore, to bring computing resources to the edge of the IoT network and allow low latency access to large amounts of data in a secure manner, we provide a secure distributed fog node architecture that uses SDN and blockchain techniques. Fog nodes are distributed fog computing entities that allow the deployment of fog services, and are formed by multiple computing resources at the edge of the IoT network. We evaluated the performance of our proposed architecture and compared it with the existing models using various performance measures. The results of our evaluation show that performance is improved by reducing the induced delay, reducing the response time, increasing throughput, and the ability to detect real-time attacks in the IoT network with low performance overheads.
Conference Paper
Full-text available
Blockchain, the foundation of Bitcoin, has received extensive attentions recently. Blockchain serves as an immutable ledger which allows transactions take place in a decentralized manner. Blockchain-based applications are springing up, covering numerous fields including financial services, reputation system and Internet of Things (IoT), and so on. However, there are still many challenges of blockchain technology such as scalability and security problems waiting to be overcome. This paper presents a comprehensive overview on blockchain technology. We provide an overview of blockchain architechture firstly and compare some typical consensus algorithms used in different blockchains. Furthermore, technical challenges and recent advances are briefly listed. We also lay out possible future trends for blockchain.
Article
In the automotive domain, the development of all safety-critical systems has to comply with safety standards such as ISO 26262. These standards require established traceability, the ability to relate artifacts created during development of a system, to ensure resulting systems are well-tested and therefore safe. This paper contrasts general traceability challenges and solutions with those specific to the automotive domain, and investigates how they manifest in practice. We combine three data sources: a tertiary literature review to identify general challenges and solutions; a case study with an automotive supplier as validation for how the challenges and solutions are experienced in practice; and a multi-vocal literature review to identify challenges and solutions specific to the automotive domain. We found 22 challenges and 16 unique solutions in the reviews. 17 challenges were identified in the case study; six remain unsolved. We discuss challenges and solutions from the perspectives of academia, tool vendors, consultants and users, and identify differences between scientific and “grey” literature. We discuss why challenges remain unsolved and propose solutions. Our findings indicate that there is a significant overlap between general traceability challenges and those in the automotive domain but that they are experienced differently.