Cognitive Manufacturing in Industry 4.0 towards Cognitive Load reduction: A Conceptual Framework

Cognitive manufacturing utilizes cognitive computing, the industrial Internet of things (IoT), and advanced analytics to upgrade manufacturing processes in manners that were not previously conceivable. It enables associations to improve major business measurements, for example, productivity, product reliability, quality, and safety, while decreasing downtime and lowering costs. Considering all the facts that can prejudice the manufacturing performance in Industry 4.0, the cognitive load has received more attention, since it was previously neglected with respect to manufacturing industries. This paper aims to investigate what causes cognitive load reduction in manufacturing environments, i.e., human–computer interaction technologies that reduce the identified causes and the applications of cognitive manufacturing that use the referred technologies. Thus, a conceptual framework that links cognitive manufacturing to a reduction of the cognitive load was developed.This research was funded by the project 026653|POCI-01-0247-FEDER-026653—INDTECH—New technologies for smart manufacturing, co-financed by the Portugal 2020 Program (PT 2020), Compete 2020 Program, and the European Union through the European Regional Development Fund (ERDF). The authors wish to thank the relevant bodies for the opportunity and financial support that permitted carrying out this project: Fundação para a Ciência e Tecnologia (FCT) and C-MAST (Center for Mechanical and Aerospace Science and Technologies), under project UIDB/00151/2020.info:eu-repo/semantics/publishedVersio

A Feasible Framework for Maintenance Digitalization

The entire industry is changing as a result of new developments in digital technology, and maintenance management is a crucial procedure that may take advantage of the opportunities brought about by industrial digitalization. To support digital innovation in maintenance management, this study intends to meet the cutting-edge necessity of addressing a transformation strategy in industrial contexts. Setting up a customized pathway with adequate methodologies, digitalization tools, and collaboration between the several stakeholders involved in the maintenance environment is the first step in this process. The results of a previous conference contribution, which revealed important digitalization variables in maintenance management, served as the foundation for the research approach herein suggested. We lead a thorough assessment of the literature to categorize the potential benefits and challenges in maintenance digitalization to be assessed in conjunction with the important digitalization aspects previously stated. As a starting point for maintenance management transformation, we offer a feasible framework for maintenance digitalization that businesses operating in a variety of industries can use. As industrial processes and machines have become more sophisticated and complex and as there is a growing desire for more secure, dependable, and safe systems, we see that this transition needs to be tailored to the specific application context

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology, Volume 1

These proceedings are organized in the same manner as the conference's contributed sessions, with the papers grouped by topic area. These areas are as follows: VE (virtual environment) training for Space Flight, Virtual Environment Hardware, Knowledge Aquisition for ICAT (Intelligent Computer-Aided Training) & VE, Multimedia in ICAT Systems, VE in Training & Education (1 & 2), Virtual Environment Software (1 & 2), Models in ICAT systems, ICAT Commercial Applications, ICAT Architectures & Authoring Systems, ICAT Education & Medical Applications, Assessing VE for Training, VE & Human Systems (1 & 2), ICAT Theory & Natural Language, ICAT Applications in the Military, VE Applications in Engineering, Knowledge Acquisition for ICAT, and ICAT Applications in Aerospace

Going one step further: towards cognitively enhanced problem-solving teaming agents

Operating current advanced production systems, including Cyber-Physical Systems, often requires profound programming skills and configuration knowledge, creating a disconnect between human cognition and system operations. To address this, we suggest developing cognitive algorithms that can simulate and anticipate teaming partners' cognitive processes, enhancing and smoothing collaboration in problem-solving processes. Our proposed solution entails creating a cognitive system that minimizes human cognitive load and stress by developing models reflecting humans individual problem-solving capabilities and potential cognitive states. Further, we aim to devise algorithms that simulate individual decision processes and virtual bargaining procedures that anticipate actions, adjusting the system’s behavior towards efficient goal-oriented outcomes. Future steps include the development of benchmark sets tailored for specific use cases and human-system interactions. We plan to refine and test algorithms for detecting and inferring cognitive states of human partners. This process requires incorporating theoretical approaches and adapting existing algorithms to simulate and predict human cognitive processes of problem-solving with regards to cognitive states. The objective is to develop cognitive and computational models that enable production systems to become equal team members alongside humans in diverse scenarios, paving the way for more efficient, effective goal-oriented solutions

Aviation 4.0: More Safety through Automation and Digitization

The world is talking about the Industry 4.0 or the fourth industrial revolution, that is, the current trend of higher level of automation, digitalization and data exchange in manufacturing technologies. It includes cyber-physical systems, Internet of Things and cloud computing among other technological assets. With more than 5000 sensors, which generate up to 10 GB of data per second, modern aircraft engines are an exponent of what digitalization and the Internet of Aircraft Things could furnish, as part of the upcoming Industry 4.0 revolution, in the aviation industry. This new era has the potential to improve air transport key performance areas. Particularly, in an industry where safety levels are so high and the margins for improvement are extremely tight, this upcoming era might imply a shift in safety improvement. In an attempt to define Aviation 4.0, this chapter discusses the stages of aviation development from basic VFR flight rules at Aviation 1.0 up to Aviation 4.0 where cyber-physical systems are designed to assist humans’ unkind or hazardous work, to take decisions and to complete tasks autonomously. It illustrates the current and future cases of application of Aviation 4.0 to increase the aviation safety, while outlines how they might increase aviation safety levels

Introduction to artificial intelligence and expert systems : a special report developed for CPAs seeking to become familiar with artificial intelligence and expert systems technology; Management advisory services special report

https://egrove.olemiss.edu/aicpa_guides/1155/thumbnail.jp

Uses and applications of artificial intelligence in manufacturing

The purpose of the THESIS is to provide engineers and personnels with a overview of the concepts that underline Artificial Intelligence and Expert Systems. Artificial Intelligence is concerned with the developments of theories and techniques required to provide a computational engine with the abilities to perceive, think and act, in an intelligent manner in a complex environment. Expert system is branch of Artificial Intelligence where the methods of reasoning emulate those of human experts. Artificial Intelligence derives it\u27s power from its ability to represent complex forms of knowledge, some of it common sense, heuristic and symbolic, and the ability to apply the knowledge in searching for solutions. The Thesis will review : The components of an intelligent system, The basics of knowledge representation, Search based problem solving methods, Expert system technologies, Uses and applications of AI in various manufacturing areas like Design, Process Planning, Production Management, Energy Management, Quality Assurance, Manufacturing Simulation, Robotics, Machine Vision etc. Prime objectives of the Thesis are to understand the basic concepts underlying Artificial Intelligence and be able to identify where the technology may be applied in the field of Manufacturing Engineering

CONCEPTUAL DESIGN OF THE USMC FUTURE VERTICAL LIFT (FVL) LIVING LAB

The United States Marine Corps (USMC) is developing the Future Vertical Lift (FVL) system that will rely heavily on Marine-machine teaming, a complex process that requires further development. The development of a living lab (LL)—a multi-function network of simulators that will serve as the platform for testing, experimenting, and training new technologies and ideas for how the FVL will operate—will help mitigate Marine-machine collaboration and trust issues. This capstone studies the options and requirements for developing a LL through interviews, research that focuses on existing technologies and operational concepts, and Model-Based Systems Engineering tools using a systems engineering approach. The report includes a detailed needs and requirements analysis, stakeholder analysis, and functional design. The team presents a conceptual design, that includes the system architecture, comprising of system, function and physical views, system lifecycle, and the evaluation criteria for a LL. The final product is a set of use cases and concepts of operation. The USMC needs a new approach that supports rapid and relevant upgrades that optimizes the system lifecycle and keeps the Marine in mind. This team recommends the USMC consider these findings and continue researching and developing a LL.ONR Arlington, VA 22203Civilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design