Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Utilization of Artificial Intelligence by Students in Interdisciplinary Field of Biomedical Engineering
Shigehiro Hashimoto
(pages: 1-5)

Transdisciplinary Applications of Data Visualization and Data Mining Techniques as Represented for Human Diseases
Richard S. Segall
(pages: 6-15)

Beyond Status Quo: Why is Transdisciplinary Communication Instrumental in Innovation?
James Lipuma, Cristo Leon
(pages: 16-20)

How We Can Locate Validatable Foundations of Life Themes
Jeremy Horne
(pages: 21-32)

Bringing Discipline into Transdisciplinary Communications -The ISO 56000 Family of Innovation Standards-
Rick Fernandez, William Swart
(pages: 33-39)

To AI Is Human: How AI Tools with Their Imperfections Enhance Learning
Martin Cwiakala
(pages: 40-46)

Knowledge, Learning and Transdisciplinary Communication in the Evolution of the Contemporary World
Rita Micarelli, Giorgio Pizziolo
(pages: 47-52)

Human Complexity vs. Machine Linearity: Tug-of-War Between Two Realities Coexisting in Precarious Balance
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 53-62)

A Cybernetic Metric Approach to Course Preparation
Russell Jay Hendel
(pages: 63-70)

The Impact of Artificial Intelligence on Education
John Jenq
(pages: 71-76)

Bridging the Gap: Harnessing the Power of Machine Learning and Big Data for Media Research
Li-jing Arthur Chang
(pages: 77-84)

Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?
Richard S. Segall
(pages: 85-92)

Identification – The Essence of Education
Jeremy Horne
(pages: 93-99)

The Greek-Roman Theatre in the Mediterranean Area
Maria Rosaria D’acierno Canonici Cammino
(pages: 100-108)

Examination of AI and Conventional Teaching Approaches in Cultivating Critical Thinking Skills in High School Students
Luis Castillo
(pages: 109-112)

Thoughts, Labyrinths, and Torii
Maurício Vieira Kritz
(pages: 113-119)

Can Two Human Intelligences (HIs or Noes) and Two Artificial Intelligences (AIs) Get Involved in Interlinguistic Communication? – A Transdisciplinary Quest
Ekaterini Nikolarea
(pages: 120-128)


 

Abstracts

 


ABSTRACT


Production Quality of Shaped Surfaces During Milling

Marek Sadilek, Robert Cep, Lenka Cepova, Lukas Kusnir, Patrik Sniehotta, Hana Stverkova, Katarzyna Czerna


In the context of the development of continuous improvement, increasing the level of quality, safety and protection of the ecological environment, it is necessary to deal with the sensitive phases of the production process and to evaluate the efficiency in terms of time and cost. In the paper, the quality of production in milling (method that is using rotary cutters to remove material) of shaped surfaces is pursued. The quality of the production process leads to the satisfaction of customer needs, and it is essential to focus on the quality/price ratio due to non-conformities. In the paper, the authors use the quality method to provide effective solutions and improve production activities, processes, and systems. This approach stands for a quality management system applied as a perpetual improvement tool, where individual activities consist of four steps: Plan, Do, Check, and Action, with returned stages developing a cycle. This cycle starts with minor to examine potential effects on systems and progresses to more extensive and precise improvements. The results of the implementation of effective solution method can be practiced for constant improvement and as a working model in developing a process or system in an organization. The different stages of the method are applied to set the path tolerance in relation to precision in 3-axis milling. The paper describes area computer numeric control milling center programming during 3-axis finishing milling. The article is focusing on setting the tolerance of tool paths during finishing milling in Computer Aided Manufacturing systems to recommend specific tolerance settings in computer aided Manufacturing systems concerning achieved accuracy, machining time, surface roughness, and quantity of blocks of machine tool control program. Finding suitable tool paths during finishing is very time-consuming and can be expensive. The aim is also to compare the practical results of machining with predicted simulation. The methodology for evaluating this problem is based on the following steps: experimental sample design for production, accuracy prediction of machined samples, production of samples using Computer Numeric Control milling center, analysis of accuracy, and surface roughness for the shape of the workpiece. The result is the variance of the shape accuracy deviations from the specified computer-aided design model of the workpiece, focusing on individual areas of its shape. The workpiece (aluminium alloy), focusing on individual areas of its shape. The research results show milled surface errors depending on the tool path tolerances. Using the effective solution method, it is possible to efficiently set up individual processes to improve the quality of production processes for time and cost.

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