# Machine Vision--Moving from Industry 4.0 to Industry 5.0
## 5 Discussion
### Contribution of Machine Vision in Industry 4.0  
#### 5.2.1 Main Uses and Application Sectors  
In what follows, all application sectors and main uses of machine vision in Industry 4.0 are identified. In the field of the _automotive industry_, the assistance of machine vision is reported to be of great importance. Every mechanical or electrical part or component produced in this field needs to pass quality and performance tests before any construction is completed. The cost invested each time is huge and any human error or defect could cause irreparable damage both in terms of money, human lives, and the reputation of the company/brand. For this reason, the funds invested in the automation of such processes are huge. According to the findings, the first priority in Industry 4.0 is the use of machine vision for quality control [37; 75; 94; 98], with a percentage that even reaches 29%. This is followed by monitoring and detection of surface anomalies with a rate of 24% and 21%, respectively. An important area that encompasses machine vision in many tasks in Industry 4.0, with a percentage of 10% according to our findings, is _Robots_. Usually, Machine Vision Inspection (MVI) systems are used for component quality inspection, monitoring, manufacturing and assembly supervision, as well as for robot guidance [70]. By acquiring visual perception, robots are more capable of efficient motion planning as well as of manipulative actions in a workplace, even in less orderly spaces or in unstructured conditions [81]. In fact, from the findings of this work, monitoring is also a high-priority task in this field. Another important application of machine vision in robots is the one that focuses on object detection, especially for robots that need to work in procedures that require object manipulation by robotic arms [90]. More generally, machine vision application tasks such as product accuracy assessment [83], localization [67], and recognition [75] are also included in Industry 4.0. It is worth mentioning, even at an early stage, the effort made for the automated assembly process with the help of machine vision-based robots. However, problems related to the way of placing the cameras are one of the factors that affect the accuracy of the procedures, as well as the high costs. Unfortunately, the scientific knowledge of automated assembly power supply is not yet ready compared to other manufacturing sectors or assembly operations. Also, the framework that supports this type of work is not yet available, but it is expected to give further impetus to the'smart' industry in the coming years [124]. The _manufacturing industry_ is another sector that gives significant value to the use of machine vision. In the manufacturing industry, problems such as tool wear come to add further stress and maintenance costs to industries in cases of general damage. The time spent on corrections and repair actions is often detrimental, and in many cases, locating the source of the problem can cause long delays. In cases where machine vision was employed in Industry 4.0, the methods followed were intact, and managed to have high measurement speeds and even carry out the measurements online, providing high accuracies [80]. Based on the findings of this research, quality control is the priority application, since, in the manufacturing sector, the quality of the products is decisive. Detection is also a fundamental task, such as detection, e.g., of surface irregularities [72], measurement, e.g., wear measurement [80], recognition, e.g., of materials [8], and monitoring [94]. The _agriculture sector_ is another sector that takes advantage of machine vision. In the field of agriculture, Industry 4.0 comes to contribute dynamically, by promoting autonomy and novel technologies, introducing the corresponding Agriculture 4.0.