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Remanufacturing and Advanced Machining
keywords for IM are Industrial Internet, smart factory, cloud computing, and CPSs,
while the most recent keywords associated with SM are CPSs, smart factory, cloud
computing, big data, and IoT. The authors conclude that expanding the application
of Industry 4.0 concepts and practices is likely driving keyword usage in both SM
and IM concepts.
In general, smart manufacturing describes the technology-driven ability of a system to solve both existing and future problems in a collaborative manufacturing
infrastructure which responds to changing demands in real time. However, many
industrial enterprises are still unsure what smart manufacturing entails and which
potential benefits and challenges it holds (Zenisek et al., 2021). Maggi et al. (2021)
state that the complexity of smart manufacturing systems makes it futile to provide
any comprehensive definition of the concept of smart manufacturing itself. They
only conclude that smart manufacturing systems are the modern implementation of
the previous totally integrated automation (TIA) concept, while from the standpoint
of cybersecurity research, smart manufacturing represents the frontier of industrial
control systems (ICSs).
According to Wang et al. (2021), the application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the
world. While the terms “smart manufacturing” and “intelligent manufacturing”
(IM) are similar, they are not identical. After a thorough bibliometric analysis of
publication sources, annual publication numbers, keywords frequency, and top
regions of research and development, the authors conclude that under various definitions, different concepts and research topics can be associated with SM or IM in
different development phases. The development of digitalization, networking, and
intelligentization in manufacturing is common for both paradigms. Since manufacturing enterprises are the main implementers of SM and IM, the authors suggest
more attention should be paid to key technologies such as CPS, big data, cloud
computing, IoT, and AI, and human/staff education must be undertaken based on
their unique actual situation, no matter which of the two paradigms, SM or IM, is
adopted (Wang et al., 2021). A better understanding of the potential of smart manufacturing also requires investigation of an additional subset of smart manufacturing
technologies, including mixed reality, additive manufacturing, and predictive maintenance (Zenisek et al., 2021).
Maggi et al. (2021) draw attention to the fact that the concept of a “reference”
smart manufacturing system does not really exist. They emphasize security issues
are of paramount importance for both the cybersecurity and ICS communities.
Despite the trend to integrate and interconnect, smart factory systems are still relatively closed, so there is little chance that conventional mass attacks will hit the
“closed world” of the smart factory. However, the main drawback is that a single
security flaw may allow an attacker to gain full access to a factory machine, posing
a serious threat to the rest of the network (Maggi et al., 2021).
Decision-making is an important component of any intelligent system. According
to Assad et al. (2021), it is a repetitive procedure that takes place in a manufacturing facility at all levels and is executed by humans or industrial controllers. In both
cases, a “condition” that initiates the decision-making has to be reported and then a
Remanufacturing and Advanced Machining
keywords for IM are Industrial Internet, smart factory, cloud computing, and CPSs,
while the most recent keywords associated with SM are CPSs, smart factory, cloud
computing, big data, and IoT. The authors conclude that expanding the application
of Industry 4.0 concepts and practices is likely driving keyword usage in both SM
and IM concepts.
In general, smart manufacturing describes the technology-driven ability of a system to solve both existing and future problems in a collaborative manufacturing
infrastructure which responds to changing demands in real time. However, many
industrial enterprises are still unsure what smart manufacturing entails and which
potential benefits and challenges it holds (Zenisek et al., 2021). Maggi et al. (2021)
state that the complexity of smart manufacturing systems makes it futile to provide
any comprehensive definition of the concept of smart manufacturing itself. They
only conclude that smart manufacturing systems are the modern implementation of
the previous totally integrated automation (TIA) concept, while from the standpoint
of cybersecurity research, smart manufacturing represents the frontier of industrial
control systems (ICSs).
According to Wang et al. (2021), the application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the
world. While the terms “smart manufacturing” and “intelligent manufacturing”
(IM) are similar, they are not identical. After a thorough bibliometric analysis of
publication sources, annual publication numbers, keywords frequency, and top
regions of research and development, the authors conclude that under various definitions, different concepts and research topics can be associated with SM or IM in
different development phases. The development of digitalization, networking, and
intelligentization in manufacturing is common for both paradigms. Since manufacturing enterprises are the main implementers of SM and IM, the authors suggest
more attention should be paid to key technologies such as CPS, big data, cloud
computing, IoT, and AI, and human/staff education must be undertaken based on
their unique actual situation, no matter which of the two paradigms, SM or IM, is
adopted (Wang et al., 2021). A better understanding of the potential of smart manufacturing also requires investigation of an additional subset of smart manufacturing
technologies, including mixed reality, additive manufacturing, and predictive maintenance (Zenisek et al., 2021).
Maggi et al. (2021) draw attention to the fact that the concept of a “reference”
smart manufacturing system does not really exist. They emphasize security issues
are of paramount importance for both the cybersecurity and ICS communities.
Despite the trend to integrate and interconnect, smart factory systems are still relatively closed, so there is little chance that conventional mass attacks will hit the
“closed world” of the smart factory. However, the main drawback is that a single
security flaw may allow an attacker to gain full access to a factory machine, posing
a serious threat to the rest of the network (Maggi et al., 2021).
Decision-making is an important component of any intelligent system. According
to Assad et al. (2021), it is a repetitive procedure that takes place in a manufacturing facility at all levels and is executed by humans or industrial controllers. In both
cases, a “condition” that initiates the decision-making has to be reported and then a