282
D. Mishra et al.
are many other ML models available for data engineering. However, the task is to
identify the best suitable model applicable to a specific problem in real time.
8.3.5.6 Robots and Additive Manufacturing
Robots are critical to welding automation. In the present context, robots are required
not only for large business, but also for “micro, small, and medium enterprises”
(MSMEs), considering the advent of Industry 4.0. Among a handful of advantages,
the following are crucial: (a) robot-assisted welding increases productivity, (b) the
application of robot will bring in consistency and repeatability, (c) superior weld
quality by enhancing the accuracy in case of robot-assisted welding, (d) minimizing
the cost overhead, and (e) higher level of customization is possible with the use of
robots because of flexibility [110]. Transforming the factory floor operations from
analog to digital is a challenging process. The major challenges are: (a) handling
huge volume of data with the existing plant capacity, (b) insufficient resources and
experience to analyse this volume of data and (c) the inherent complexity. However,
to build a smart factory, industry will seek assistance from robots, who will be
the best-suited physical and cognitive assistant. Robots have the ability to perform
uninterruptedly, collect and analyse data simultaneously and also help in attaining a
superior weld quality. This makes them indispensable.
Additive manufacturing (AM) is the process of making components by deposition
of materials in layers. It differs from the conventional way of component manufacturing which includes removal of material from a stock to eventually achieve the
desired form. The AM technology allows users to manufacture components without
using any tool, and thus, any complicated geometry can be fabricated. Owing to this,
the AM process substantially reduces the lead time and increases the production
efficiency by reducing the loss of material. Since the arc welding technique utilizes a
filler material to deposit the molten material in the groove, research is being carried
out in this direction and is being referred as “arc welding-based AM” [111].
8.3.6 A Concept Block Diagram for Implementing Industry
4.0 in Welding
Figure 8.10 depicts a possible block diagram for implementing Industry 4.0 in a
welding process. The cloud/edge connectivity would drive tele-welding. While the
edge platform can be utilized for small computations such as initial screening of the
data, the cloud platform will contain the database of the welding operations being
performed. The cloud platform will also have real-time data processing scripts, which
will be continuously operating on the data for extracting useful information such as
predicting the quality of the weld. The reference quality can be plugged into the
script, which will be utilized for real-time evaluation, forming a closed-loop control
D. Mishra et al.
are many other ML models available for data engineering. However, the task is to
identify the best suitable model applicable to a specific problem in real time.
8.3.5.6 Robots and Additive Manufacturing
Robots are critical to welding automation. In the present context, robots are required
not only for large business, but also for “micro, small, and medium enterprises”
(MSMEs), considering the advent of Industry 4.0. Among a handful of advantages,
the following are crucial: (a) robot-assisted welding increases productivity, (b) the
application of robot will bring in consistency and repeatability, (c) superior weld
quality by enhancing the accuracy in case of robot-assisted welding, (d) minimizing
the cost overhead, and (e) higher level of customization is possible with the use of
robots because of flexibility [110]. Transforming the factory floor operations from
analog to digital is a challenging process. The major challenges are: (a) handling
huge volume of data with the existing plant capacity, (b) insufficient resources and
experience to analyse this volume of data and (c) the inherent complexity. However,
to build a smart factory, industry will seek assistance from robots, who will be
the best-suited physical and cognitive assistant. Robots have the ability to perform
uninterruptedly, collect and analyse data simultaneously and also help in attaining a
superior weld quality. This makes them indispensable.
Additive manufacturing (AM) is the process of making components by deposition
of materials in layers. It differs from the conventional way of component manufacturing which includes removal of material from a stock to eventually achieve the
desired form. The AM technology allows users to manufacture components without
using any tool, and thus, any complicated geometry can be fabricated. Owing to this,
the AM process substantially reduces the lead time and increases the production
efficiency by reducing the loss of material. Since the arc welding technique utilizes a
filler material to deposit the molten material in the groove, research is being carried
out in this direction and is being referred as “arc welding-based AM” [111].
8.3.6 A Concept Block Diagram for Implementing Industry
4.0 in Welding
Figure 8.10 depicts a possible block diagram for implementing Industry 4.0 in a
welding process. The cloud/edge connectivity would drive tele-welding. While the
edge platform can be utilized for small computations such as initial screening of the
data, the cloud platform will contain the database of the welding operations being
performed. The cloud platform will also have real-time data processing scripts, which
will be continuously operating on the data for extracting useful information such as
predicting the quality of the weld. The reference quality can be plugged into the
script, which will be utilized for real-time evaluation, forming a closed-loop control