8 Industry 4.0 in Welding
255
more flexible and reliable. Earlier, machine downtime used to affect the rate of
production. However, the predictive maintenance which uses sensors attached to the
mechanical components, monitors machine health constantly, thereby reducing the
machine downtime.
In the context of welding, maintaining the product quality is crucial, or in simple
words, the product should be free from defects. In the sequence of manufacturing
operations, welding is the last process. Thus, automation along with monitoring
and control of welding is inevitable. Automation in welding includes the use of
robots integrated with other infrastructures. The prime objective of automating the
welding technique is to reduce the process variation, which often occurs with manual
handling of the jobs. For instance, in case of the manual arc welding technique,
a lot of spatter may be generated because of improper setting of parameters, or
variations in the parameters during welding. This will degrade the job and may
require time-consuming cleaning of the surface. Automation of the process will
help in avoiding the formation of spatter to a greater extent with elimination of
manual intervention. Thus, the robotic system for welding is essential because of the
following: (a) elimination of human errors, (b) less variation in the parameters which
is ensured by the use of a feedback system, (c) superior weld quality with almost no
need of any rework and (d) higher productivity.
8.1.2 Focus of This Chapter
“Industry 4.0” or in other words, the “fourth industrial revolution” has been a
buzzword in the recent times [1–3]. Conceptualized by Germans, it aims at digitalizing the traditional manufacturing process. The objective of this chapter is to
highlight the pertinence of Industry 4.0 in welding. Figure 8.1 shows a “Google
Trends” analysis on the keyword, Industry 4.0, from 2014 to 2019 [4]. The interest
can be seen to be increasing over the years.
The remainder of the chapter is organized in the following manner: “Sect. 8.2”
presents the evolution of the manufacturing (industrial revolutions) chronologically
which is inclusive of the history of welding. “Monitoring and control” of manufacturing is a bottom line in the success of Industry 4.0. This has been discussed in
“Sect. 8.3” for different welding processes. This section also describes the role of
Industry 4.0, and its “digital tools” for implementation in welding. Few important
concepts such as (a) data mining, (b) machine learning (ML)/deep learning (DL) and
(c) artificial intelligence (AI) have been addressed in this section. “Sect. 4” presents
a case study to highlight the utility of data in online process monitoring and control
of friction stir welding (FSW) technique. Finally, the concluding remarks have been
presented in “Sect. 5".
255
more flexible and reliable. Earlier, machine downtime used to affect the rate of
production. However, the predictive maintenance which uses sensors attached to the
mechanical components, monitors machine health constantly, thereby reducing the
machine downtime.
In the context of welding, maintaining the product quality is crucial, or in simple
words, the product should be free from defects. In the sequence of manufacturing
operations, welding is the last process. Thus, automation along with monitoring
and control of welding is inevitable. Automation in welding includes the use of
robots integrated with other infrastructures. The prime objective of automating the
welding technique is to reduce the process variation, which often occurs with manual
handling of the jobs. For instance, in case of the manual arc welding technique,
a lot of spatter may be generated because of improper setting of parameters, or
variations in the parameters during welding. This will degrade the job and may
require time-consuming cleaning of the surface. Automation of the process will
help in avoiding the formation of spatter to a greater extent with elimination of
manual intervention. Thus, the robotic system for welding is essential because of the
following: (a) elimination of human errors, (b) less variation in the parameters which
is ensured by the use of a feedback system, (c) superior weld quality with almost no
need of any rework and (d) higher productivity.
8.1.2 Focus of This Chapter
“Industry 4.0” or in other words, the “fourth industrial revolution” has been a
buzzword in the recent times [1–3]. Conceptualized by Germans, it aims at digitalizing the traditional manufacturing process. The objective of this chapter is to
highlight the pertinence of Industry 4.0 in welding. Figure 8.1 shows a “Google
Trends” analysis on the keyword, Industry 4.0, from 2014 to 2019 [4]. The interest
can be seen to be increasing over the years.
The remainder of the chapter is organized in the following manner: “Sect. 8.2”
presents the evolution of the manufacturing (industrial revolutions) chronologically
which is inclusive of the history of welding. “Monitoring and control” of manufacturing is a bottom line in the success of Industry 4.0. This has been discussed in
“Sect. 8.3” for different welding processes. This section also describes the role of
Industry 4.0, and its “digital tools” for implementation in welding. Few important
concepts such as (a) data mining, (b) machine learning (ML)/deep learning (DL) and
(c) artificial intelligence (AI) have been addressed in this section. “Sect. 4” presents
a case study to highlight the utility of data in online process monitoring and control
of friction stir welding (FSW) technique. Finally, the concluding remarks have been
presented in “Sect. 5".