Novel Approach of an Intelligent and Flexible Manufacturing System: A Contribution to the Concept and Development of Smart Factory

Sawangsri, Worapong; Suppasasawat, Pattranit; Thamphanchark, Vorakrit; Pandey, Santosh

doi:10.1109/icsse.2018.8520029

Cited by 11 publications

(6 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some simple choice problems one may reduce to mathematical models that allow finding the optimal solution for the problems. Unfortunately, the number of well-formalized problems is significantly inferior to the number of poorly formalized or non-formalized ones, for the solution of which the operation analysis methods are not suitable [8,19]. The poor formalizability of many choice problems is associated with the presence of socalled uncertainty, which means that decision-making is influenced by factors that cannot be unambiguously defined and described for one reason or another [1,18].…”

Section: Problem Analysis and Research Goals Settingmentioning

confidence: 99%

“…Indeed, recent years one may characterize by [6][7][8][9][10][11][12] Features of the modern stage of development of society such as [13][14][15][16]:…”

Section: Introductionmentioning

confidence: 99%

“…In these conditions, it is increasingly necessary to use hybrid intelligence technologies and attract highly qualified specialists for expert assessment of possible scenarios for the sustainable development of production, society, region, state [1,8,17].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Expert assessment systems to support decision-making for sustainable development of complex technological and socio-economic facilities

et al. 2020

View full text Add to dashboard Cite

In this paper, we investigate problems of decision making in management systems for the sustainable development of complex technological and socio-economic facilities. We show both the limitations of traditional expert systems and decision support systems, and the necessity of using expert evaluation technologies to find possible development strategies. Based on that we substantiate the need of creating a new class of systems, i.e. Automated eXpert Assessment Systems, and propose their organizational structure and design principles. We substantiate the level of automation of the work performed during the examinations and describe the composition of models and computer programs we recommend for creating effective automated expert assessment systems and corresponding technology. In the paper, we give examples of using the proposed method for various areas of human activity, in the management of urban infrastructure and e-learning at the universities, and show the effectiveness of the developed approach.

show abstract

Section: Problem Analysis and Research Goals Settingmentioning

confidence: 99%

“…Indeed, recent years one may characterize by [6][7][8][9][10][11][12] Features of the modern stage of development of society such as [13][14][15][16]:…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Expert assessment systems to support decision-making for sustainable development of complex technological and socio-economic facilities

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In addition to 3D reconstruction, intelligent robot arms can play an essential role in other applications. For example, in smart factories [7], intelligent robot arms can be used in production, manufacturing, assembly, and packing in various industries. Moreover, in smart hospitals, robot-assisted surgery allows doctors to perform many types of complex procedures with higher precision, flexibility, and control than is possible with conventional techniques.…”

Section: Introductionmentioning

confidence: 99%

Computer Vision-Based Path Planning for Robot Arms in Three-Dimensional Workspaces Using Q-Learning and Neural Networks

Abdi

Ranjbar

Park

2022

Sensors

View full text Add to dashboard Cite

Computer vision-based path planning can play a crucial role in numerous technologically driven smart applications. Although various path planning methods have been proposed, limitations, such as unreliable three-dimensional (3D) localization of objects in a workspace, time-consuming computational processes, and limited two-dimensional workspaces, remain. Studies to address these problems have achieved some success, but many of these problems persist. Therefore, in this study, which is an extension of our previous paper, a novel path planning approach that combined computer vision, Q-learning, and neural networks was developed to overcome these limitations. The proposed computer vision-neural network algorithm was fed by two images from two views to obtain accurate spatial coordinates of objects in real time. Next, Q-learning was used to determine a sequence of simple actions: up, down, left, right, backward, and forward, from the start point to the target point in a 3D workspace. Finally, a trained neural network was used to determine a sequence of joint angles according to the identified actions. Simulation and experimental test results revealed that the proposed combination of 3D object detection, an agent-environment interaction in the Q-learning phase, and simple joint angle computation by trained neural networks considerably alleviated the limitations of previous studies.

show abstract

“…Intelligent systems come in a variety of shapes and sizes, including autonomous vacuums like the iRobot, Amazon's customized shopping recommendations, facial recognition software, etc. The three different forms of intelligent systems are: Artificial Narrow Intelligence (ANI) which has a constrained set of skills, Artificial General Intelligence (AGI) which is on par with human abilities and Artificial Super-Intelligence (ASI) which is more intelligent than humans (Mokesioluwa et al 2021;Sawangsri et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Exploring the Intelligent Attributes of Industrial 4.0: The Next Revolution and Beyond

Omoregbee¹,

Olanipekun²

2022

ICONIC

View full text Add to dashboard Cite

Industry 4.0 places a strong emphasis on connection, automation, machine learning and real-time data. With these descriptions, intelligent/smart manufacturing that incorporates people, technology, and other resources has undergone a significant revolution leading the globe to the new era of Industry 5.0. Responding to disruption by employing intuition to decide what to do in a changing circumstance has grown to be highly attractive and exciting, even when it has never been utilized before. The domains of modern intelligent systems and computers have also made major strides in recent years. Examples include soft computing, computational intelligence, which encompasses evolutionary computing, neural networks, fuzzy systems, and the fusion of various paradigms. Others include immune-based systems, ambient intelligence, cognitive science, computational neuroscience and systems, perspective and vision, DNA, intelligent decision-making, and support etc. This technological breakthrough has also made room for new and emerging technologies that offer important advantages including extreme low latency, highly reliable connections, sufficient bandwidth, ample data storage, and powerful processing capabilities. This paper provides a comprehensive overview of what smart/intelligent systems include, as was observed in an ongoing project where such devices were designed, and what to anticipate from the 4.0, 5.0, and 6.0 industrial revolutions.

show abstract

Novel Approach of an Intelligent and Flexible Manufacturing System: A Contribution to the Concept and Development of Smart Factory

Cited by 11 publications

References 3 publications

Expert assessment systems to support decision-making for sustainable development of complex technological and socio-economic facilities

Expert assessment systems to support decision-making for sustainable development of complex technological and socio-economic facilities

Computer Vision-Based Path Planning for Robot Arms in Three-Dimensional Workspaces Using Q-Learning and Neural Networks

Exploring the Intelligent Attributes of Industrial 4.0: The Next Revolution and Beyond

Contact Info

Product

Resources

About