Special Session on Industry 4.0

No abstract available

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

CYBEREDUCATION-BY-DESIGN™: DEVELOPING A FRAMEWORK FOR CYBERSECURITY EDUCATION AT SECONDARY EDUCATION INSTITUTIONS IN ARIZONA

Most survey results agree that there is a current and ongoing shortage of skilled cybersecurity workers that places our privacy, infrastructure, and nation at risk. Estimates for the global Cybersecurity Workforce Gap range from 2.72 million (ISC2, 2021) to 3.5 million (Cyber Academy, 2021) for 2021 and the United States estimates range from 465,000 (Brooks, 2021) to over 769,000 (Cyber Seek, 2022) open jobs as of November 2022. The most optimistic estimates still demonstrate a critical issue. As cybersecurity threats continue to grow in sophistication, scope, and scale, the ability to secure the United States from these threats lies in the ability to develop cybersecurity professionals with the knowledge, skills, and abilities (KSAs) to accomplish the tasks associated with their cyber roles. The ability to supply qualified cybersecurity professionals is outpaced by the growing demand as previously outlined. This study proposes that conducting a case study of existing cybersecurity programs at secondary education institutions can identify the critical elements of these programs. These elements can be codified into program profiles and further refined into a comprehensive cybersecurity education framework for secondary education institutions. This framework can be used by school districts throughout Arizona to develop cybersecurity programs and ultimately develop qualified and competent cybersecurity professionals to overcome the cybersecurity workforce gap

Redesigning the Information Assurance Undergraduate Curriculum at Regis University

When Regis University created the eSecurity curriculum in 2003, the lessons were pertinent to the then-current threats. Although the curriculum has slightly changed since then, the courses needed a major facelift to meet the ever changing cyber threats. The question of can Information Assurance courses at Regis University be refreshed to include virtual labs so they are based on ethical standards will be answered in this paper. Utilizing the Design Science methodology and incorporating Bloom â„¢s Taxonomy and the Jesuit educational approach, curriculum was identified and developed for the classroom and online students. By working with the Regis Distance Learning department, the thesis project was submitted for publication as part of the Regis Computer Networking courses

Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Cyber-security of Cyber-Physical Systems (CPS)

This master's thesis reports on security of a Cyber-Physical System (CPS) in the department of industrial engineering at UiT campus Narvik. The CPS targets connecting distinctive robots in the laboratory in the department of industrial engineering. The ultimate objective of the department is to propose such a system for the industry. The thesis focuses on the network architecture of the CPS and the availability principle of security. This report states three research questions that are aimed to be answered. The questions are: what a secure CPS architecture for the purpose of the existing system is, how far the current state of system is from the defined secure architecture, and how to reach the proposed architecture. Among the three question, the first questions has absorbed the most attention of this project. The reason is that a secure and robust architecture would provide a touchstone that makes answering the second and third questions easier. In order to answer the questions, Cisco SAFE for IoT threat defense for manufacturing approach is chosen. The architectural approach of Cisco SAFE for IoT, with similarities to the Cisco SAFE for secure campus networks, provides a secure network architecture based on business flows/use cases and defining related security capabilities. This approach supplies examples of scenarios, business flows, and security capabilities that encouraged selecting it. It should be noted that Cisco suggests its proprietary technologies for security capabilities. According to the need of the project owners and the fact that allocating funds are not favorable for them, all the suggested security capabilities are intended to be open-source, replacing the costly Cisco-proprietary suggestions. Utilizing the approach and the computer networking fundamentals resulted in the proposed secure network architecture. The proposed architecture is used as a touchstone to evaluate the existing state of the CPS in the department of industrial engineering. Following that, the required security measures are presented to approach the system to the proposed architecture. Attempting to apply the method of Cisco SAFE, the identities using the system and their specific activities are presented as the business flow. Based on the defined business flow, the required security capabilities are selected. Finally, utilizing the provided examples of Cisco SAFE documentations, a complete network architecture is generated. The architecture consists of five zones that include the main components, security capabilities, and networking devices (such as switches and access points). Investigating the current state of the CPS and evaluating it by the proposed architecture and the computer networking fundamentals, helped identifying six important shortcomings. Developing on the noted shortcomings, and identification of open-source alternatives for the Cisco-proprietary technologies, nine security measures are proposed. The goal is to perform all the security measures. Thus, the implementations and solutions for each security measure is noted at the end of the presented results. The security measures that require purchasing a device were not considered in this project. The reasons for this decision are the time-consuming process of selecting an option among different alternatives, and the prior need for grasping the features of the network with the proposed security capabilities; features such as amount and type of traffic inside the network, and possible incidents detected using an Intrusion Detection Prevention System. The attempts to construct a secure cyber-physical system is an everlasting procedure. New threats, best practices, guidelines, and standards are introduced on a daily basis. Moreover, business needs could vary from time to time. Therefore, the selected security life-cycle is required and encouraged to be used in order to supply a robust lasting cyber-physical system

Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0

Graduate School of Engineering and Management Catalog 2018-2019

The Graduate Catalog represents the offerings, programs, and requirements in effect at the time of publication