135
Smart Machining Processes
Based on their literature survey, the authors find the most frequent implementation of
AR-assisted tools takes place in the manufacturing operation of assembly/disassembly. A majority of deployed AR applications involve multiple solution functions and
intelligence sources to deal with current complex manufacturing problems. Visual
clue/perception is a major sensory channel to communicate with users of AR. The
objective is to increase the human operator’s situational awareness in the manufacturing environment. The authors conclude that AR is an interfacing technology able
to exchange information with humans in real time and its technical merits become
evident when AR is applied to tasks in which humans and computational intelligence
can complement each other (Baroroh et al., 2020).
Emerging digital technologies of Industry 4.0 provide applicability of the Internet of
Things, virtual reality (VR), and augmented reality in remanufacturing. A study by Kerin
and Pham (2019) suggests there is still a need to explore the connection of cyber-physical
systems to the IoT to support smart remanufacturing, while aligning with evolving information and communication infrastructures and circular economy business models.
Smart devices like the IoT and CPS have now emerged as a universal paradigm
that can drastically transform any industries equipped with sensing, identification,
remote control, and automated control capabilities. The concepts and programs like
Industry 4.0, Society 5.0, Made in China 2025, and Industrial Internet are all based
on the internet and interconnected devices and basically have as their theme process
control through less human intervention and smart decisions, with a huge impact on
the global market (Phuyal et al., 2020).
3.3 “SMART” TOOLS AND MATERIALS
Cheng et al. (2017) express the opinion that smart tooling has tremendous potential as a generation precision machining technology of particular importance in the
Industry 4.0 context. Zhao, Liu et al. (2021) point out that a new field of smart cutting
tools has emerged from the integration of sensors into traditional cutting tools to
reduce chatter, to measure cutting force and cutting temperature, and to monitor tool
wear and damage. Möhring et al. (2020) divide monitoring methods into two areas:
1. Direct monitoring via camera systems or microscopes
2. Indirect monitoring through force measurement, acoustic emission, and
vibrations
In their review, Hopkins and Hosseini (2019) indicated three main directions in the
development of smart metal cutting tools, namely:
1. Self-regulation of regenerative vibration (chatter) through monitoring of
vibrations, predicting stability lobes of a milling tool, semi-active damping
control, or process simulations.
2. Monitoring of work conditions in order to determine the point at which a
tool becomes no more useful, to prevent excessive increase of the cutting
forces, or to predict tool wear. Cutting forces, temperature, and changes in
spindle acceleration are among the measured parameters.
Smart Machining Processes
Based on their literature survey, the authors find the most frequent implementation of
AR-assisted tools takes place in the manufacturing operation of assembly/disassembly. A majority of deployed AR applications involve multiple solution functions and
intelligence sources to deal with current complex manufacturing problems. Visual
clue/perception is a major sensory channel to communicate with users of AR. The
objective is to increase the human operator’s situational awareness in the manufacturing environment. The authors conclude that AR is an interfacing technology able
to exchange information with humans in real time and its technical merits become
evident when AR is applied to tasks in which humans and computational intelligence
can complement each other (Baroroh et al., 2020).
Emerging digital technologies of Industry 4.0 provide applicability of the Internet of
Things, virtual reality (VR), and augmented reality in remanufacturing. A study by Kerin
and Pham (2019) suggests there is still a need to explore the connection of cyber-physical
systems to the IoT to support smart remanufacturing, while aligning with evolving information and communication infrastructures and circular economy business models.
Smart devices like the IoT and CPS have now emerged as a universal paradigm
that can drastically transform any industries equipped with sensing, identification,
remote control, and automated control capabilities. The concepts and programs like
Industry 4.0, Society 5.0, Made in China 2025, and Industrial Internet are all based
on the internet and interconnected devices and basically have as their theme process
control through less human intervention and smart decisions, with a huge impact on
the global market (Phuyal et al., 2020).
3.3 “SMART” TOOLS AND MATERIALS
Cheng et al. (2017) express the opinion that smart tooling has tremendous potential as a generation precision machining technology of particular importance in the
Industry 4.0 context. Zhao, Liu et al. (2021) point out that a new field of smart cutting
tools has emerged from the integration of sensors into traditional cutting tools to
reduce chatter, to measure cutting force and cutting temperature, and to monitor tool
wear and damage. Möhring et al. (2020) divide monitoring methods into two areas:
1. Direct monitoring via camera systems or microscopes
2. Indirect monitoring through force measurement, acoustic emission, and
vibrations
In their review, Hopkins and Hosseini (2019) indicated three main directions in the
development of smart metal cutting tools, namely:
1. Self-regulation of regenerative vibration (chatter) through monitoring of
vibrations, predicting stability lobes of a milling tool, semi-active damping
control, or process simulations.
2. Monitoring of work conditions in order to determine the point at which a
tool becomes no more useful, to prevent excessive increase of the cutting
forces, or to predict tool wear. Cutting forces, temperature, and changes in
spindle acceleration are among the measured parameters.