The intelligent solution: automation, the skills shortage and cyber-security

Smith, Graham

doi:10.1016/s1361-3723(18)30073-3

Cited by 20 publications

(11 citation statements)

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“…Further, the development of novel technologies such as smart sensors, intelligent assistant, robots, and automation will continue to demand change in the types of skills as well as the labour landscape [199]. Eventually, there will be a great transition for job demand from lower-skilled to highly-skilled jobs [200,201]. In order to clearly describe the skill requirements for industry 4.0, the present study broadly categorized the required skills in two groups: technical and personal (soft) skills.…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

Bongomin

Ocen

Nganyi

et al. 2020

Journal of Engineering

135

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The 21st century has witnessed precipitous changes spanning from the way of life to the technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where science fictions have become science facts, and technology fusion is the main driver. Thus, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this study, disruptive technologies of industry 4.0 were explored and quantified in terms of the number of their appearances in published literature. The study aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enumerate the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management was done in multidisciplinary databases: Google Scholar, Science Direct, Scopus, Sage, Taylor & Francis, and Emerald Insight. From the electronic survey, 35 disruptive technologies were quantified and 13 key technologies: Internet of Things, Big Data, 3D printing, Cloud computing, Autonomous robots, Virtual and Augmented reality, Cyber-physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones, and Biotechnology were identified. Both technical and personal skills to be imparted into the human workforce for industry 4.0 were reported. The review identified the need to investigate the capability and the readiness of developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. This study proposes the need to address the integration of industry 4.0 concepts into the current education system.

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Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

Bongomin

Ocen

Nganyi

et al. 2020

Journal of Engineering

135

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“…The main feature of tool is that it is used for functional, regression and service testing. It helps to improve user actions on a web or client based computer application and test and identify bugs on the same actions for different users, different data set, on various Windows operating systems and/or different browsers [9].…”

Section: Unified Functional Testing (Uft)mentioning

confidence: 99%

“…The graphical interface is userfriendly and has a simple design and use. Some testing function features allow user to protect the website from hackers and viruses [12].…”

Section: Soapuimentioning

confidence: 99%

Information Systems for Machine Intelligence to Automated Software Testing

Seralina¹

2021

Herald of KBTU

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The methods of development software develop rapidly. The testing of software has a great role in developing a good product. Many technologies assembled into all aspects of performance, based on software testing. Many advanced automation tools use in a set of test design and validation tests based on the artificial intelligence. The important thing is to focus on changes, to work on basis of collective reasoning of the test command and other commands analogues. The methods of the quality testing are based on the information provided in the modern digital world. The business is relying on new fast processes to provide automatic testing of software. Applying approaches of solutions to financial organization allows increase the transparency of all steps of software development. These steps can help systems show more percentage of the test case rate, can save time and money, but also effectively solves the problem of scaling the process and errors. In this paper, we research information systems for machine intelligence to automated software testing. The aim is divided to tasks: the importance of artificial intelligence, the necessary stage of Software Development - Testing and Quality Controlling System, research of main automation tools. We concluded that use of intellectual intelligence and machine learning: allows automating the repeating process and usage of the database; delivers superb intellectual product; adapts to the progressive algorithm of learning; adds more depth analysis of multiple objects; allows retrieving the maximum amount of data from the databases.

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“…Furthermore, the exponential development of the novel technology such as smart sensors, intelligent assistant, robots and automation will continue to change the need for new types of skills as well as labour landscape [199]. Eventually, there will be great transition for job demand from lower-skilled to highly-skilled jobs [200], [201].…”

Section: Required Skillsmentioning

confidence: 99%

Exponential Disruptive Technologies and the Required Skills of Industry 4.0: A Review

Bongomin¹,

Ocen²,

Nganyi³

et al. 2019

Preprint

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The 21st century has witnessed a number of incredible changes ranging from the way of life and the technologies that emerged. Currently, we have entered a new paradigm shift called industry 4.0 where science fictions have become science facts, and technology fusion is the main driver. Therefore, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this paper, disruptive technologies of industry 4.0 have been explored and quantified in terms of the number of their appearances in literature. This research mainly aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enlighten the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management from both academia and business was done from publication databases: Google scholar, ScienceDirect, Scopus, Sage, Taylor & Francis and Emerald insight. The results of the study show that 35 disruptive technologies were quantified and 13 key technologies: Internet of things, Big data, 3D printing, Cloud computing, Autonomous robots, Virtual and augmented reality, Cyber physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones and Biotechnology were identified. Moreover, both technical and personal skills to be imparted into the human workforce for industry 4.0 were identified. The study reveals the need to investigate the capabilities and the readiness of some developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. In addition, the study proposes the need to address the ways for integration of industry 4.0 concepts into the current education system.

show abstract

The intelligent solution: automation, the skills shortage and cyber-security

Cited by 20 publications

References 0 publications

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

Information Systems for Machine Intelligence to Automated Software Testing

Exponential Disruptive Technologies and the Required Skills of Industry 4.0: A Review

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