Robotic process automation with increasing productivity and improving product quality using artificial intelligence and machine learning

Author(s):  
Anand Singh Rajawat ◽  
Romil Rawat ◽  
Kanishk Barhanpurkar ◽  
Rabindra Nath Shaw ◽  
Ankush Ghosh
2022 ◽  
pp. 35-58
Author(s):  
Ozge Doguc

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.


Author(s):  
Ozge Doguc

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.


Author(s):  
Rashmi Jha ◽  
Govind Murari Upadhyay

Robotic Process Automation (RPA) is one of the smartest technology evolutions in recent years. It is, a software installed on a system. RPA can be implemented in a well-defined environment with defined procedures and clarity with reference to decision making. RPA’s limitation is that it cannot be automated if it involves decision making supported by knowledgebased application. Highly invasive and intertwined supply chains are now confronted by producers, which reduce manufacturing life cycles and raise product sophistication. You therefore sense the need, at all stages of value formation, to change and adjust more rapidly. The theory of self-optimization is a positive method to coping with uncertainty and unexpected delays within supply chains, devices and processes. It would also boost manufacturing industries' stability and productivity. This paper explores the idea of development processes that are self-optimized. Following a quick historical analysis and understanding the particular needs, specifications and self-optimizing criteria of the various stages of value generation from supply chain planning and management to manufacture and assembly. Examples at both stages are used to demonstrate the self-optimization principle and to explain its simplicity and efficiency ability.. We proposed Novel approach for Robotic Process Automation with increasing productivity and improving product quality using machine learning


Author(s):  
Andrea M. Prud’homme ◽  
John V. Gray ◽  
Andrew C. Barley

This chapter looks at emerging technologies and their use in supply management processes as a means to improve effectiveness through improved speed and accuracy, at a reduced cost. Many technologies are finding their way into supply management, with differing levels of penetration and application and with mixed results. It may be challenging for supply management professionals to understand how, when, and where these technologies are likely to yield positive results. This chapter reviews several technologies, including artificial intelligence/machine learning, big data/advanced analytics, blockchain, cloud computing, conversational things (e.g., chatbots), immersive technologies (e.g., virtual and augmented reality), and robotic process automation. Findings indicate that the primary advantages are achieved by improving current processes and workflows, rather than that these technologies are currently disrupting or will fundamentally change supply management. Another important finding is the importance of “clean data” inputs, something that artificial intelligence can help with and that is foundational for successful robotic process automation.


2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Nedeljko Šikanjić ◽  
Zoran Ž. Avramović ◽  
Esad Jakupović

In today’s world, devices with possibility to communicate, are emerging and growing daily. This advanced technology is bringing ideas of how to use these devices, in order to gain financial benefits for enterprises, business and economy in general. Purpose of research in this scientific paper is to discover, what are the trends in connecting these devices, called internet of things (IoT), what are financial aspects of implementing IoT solutions and how leaders in area of cloud computing and IoT, are implementing additional advanced technologies such as machine learning and artificial intelligence, to improve processes and gain increase in revenue, while bringing automation in place for the end users. Development of informational society is not only bringing innovation to everyday life, but is also providing effect on the economy. This effect reflects on various business platforms, companies and organizations while increasing the quality of the end product or service that is being provided.


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