Energetics Systems and artificial intelligence: Applications of industry 4.0

AbstractThis paper presents a new design for artificial intelligence in cyber-physical systems. We present a survey of principles, policies, design actions and key technologies for CPS, and discusses the state of art of the technology in a qualitative perspective. First, literature published between 2010 and 2021 is reviewed, and compared with the results of a qualitative empirical study that correlates world leading Industry 4.0 frameworks. Second, the study establishes the present and future techniques for increased automation in cyber-physical systems. We present the cybersecurity requirements as they are changing with the integration of artificial intelligence and internet of things in cyber-physical systems. The grounded theory methodology is applied for analysis and modelling the connections and interdependencies between edge components and automation in cyber-physical systems. In addition, the hierarchical cascading methodology is used in combination with the taxonomic classifications, to design a new integrated framework for future cyber-physical systems. The study looks at increased automation in cyber-physical systems from a technical and social level.

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Artificial intelligence methods used in industry 4.0 in particular industrial control systems

10.1063/5.0041610 ◽

2021 ◽

Author(s):

Georgi Tsochev ◽

Maksim Sharabov

Keyword(s):

Artificial Intelligence ◽

Control Systems ◽

Industry 4.0 ◽

Industrial Control ◽

Industrial Control Systems ◽

Artificial Intelligence Methods

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Big Data and Artificial Intelligence in the Development of Industry 4.0; A Bibliometric Analysis

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1154/1/012008 ◽

2021 ◽

Vol 1154 (1) ◽

pp. 012008

Author(s):

E González-Sarmiento ◽

J Roa-Perez ◽

L Ortiz-Ospino

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Bibliometric Analysis ◽

Industry 4.0

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ProBot – A Procedure Chatbot for Digital Procedural Adherence

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181320641054 ◽

2020 ◽

Vol 64 (1) ◽

pp. 224-228

Author(s):

Nilesh Ade ◽

Noor Quddus ◽

Trent Parker ◽

S.Camille Peres

Keyword(s):

Artificial Intelligence ◽

Deep Learning ◽

Natural Language ◽

Industry 4.0 ◽

Natural Language Generation ◽

Conversational Agent ◽

Safe Distance ◽

Process Industries ◽

Language Generation ◽

Plastic Pellets

One of the major implications of Industry 4.0 will be the application of digital procedures in process industries. Digital procedures are procedures that are accessed through a smart gadget such as a tablet or a phone. However, like paper-based procedures their usability is limited by their access. The issue of accessibility is magnified in tasks such as loading a hopper car with plastic pellets wherein the operators typically place the procedure at a safe distance from the worksite. This drawback can be tackled in the case of digital procedures using artificial intelligence-based voice enabled conversational agent (chatbot). As a part of this study, we have developed a chatbot for assisting digital procedure adherence. The chatbot is trained using the possible set of queries from the operator and text from the digital procedures through deep learning and provides responses using natural language generation. The testing of the chatbot is performed using a simulated conversation with an operator performing the task of loading a hopper car.

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An Artificial Intelligence of Things-Based Picking Algorithm for Online Shop in the Society 5.0’s Context

Sensors ◽

10.3390/s21082813 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2813

Author(s):

Muslikhin Muslikhin ◽

Jenq-Ruey Horng ◽

Szu-Yueh Yang ◽

Ming-Shyan Wang ◽

Baiti-Ahmad Awaluddin

Keyword(s):

Artificial Intelligence ◽

System Performance ◽

Industry 4.0 ◽

Online Shopping ◽

Robotic Manipulators ◽

Data Driven ◽

Key Points ◽

Detection And Localization ◽

Picking System

In this study, an Artificial Intelligence of Things (AIoT)-based automated picking system was proposed for the development of an online shop and the services for automated shipping systems. Speed and convenience are two key points in Industry 4.0 and Society 5.0. In the context of online shopping, speed and convenience can be provided by integrating e-commerce platforms with AIoT systems and robots that are following consumers’ needs. Therefore, this proposed system diverts consumers who are moved by AIoT, while robotic manipulators replace human tasks to pick. To prove this idea, we implemented a modified YOLO (You Only Look Once) algorithm as a detection and localization tool for items purchased by consumers. At the same time, the modified YOLOv2 with data-driven mode was used for the process of taking goods from unstructured shop shelves. Our system performance is proven by experiments to meet the expectations in evaluating efficiency, speed, and convenience of the system in Society 5.0’s context.

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