scholarly journals Simulation of Human-Machine Interaction in an Automotive Manufacturing Cell Using Digital Factory (DF)

2016 ◽  
Vol 14 (2) ◽  
pp. 133-140
Author(s):  
Guilherme Canuto da Silva ◽  
Leonardo Morais de Souza ◽  
Paulo Carlos Kaminski
2020 ◽  
Vol 13 (2) ◽  
pp. 321
Author(s):  
Mildrend Montoya-Reyes ◽  
Alvaro González-Angeles ◽  
Ismael Mendoza-Muñoz ◽  
Margarita Gil-Samaniego-Ramos ◽  
Juan Ling-López

Purpose: The purpose of this work is to present a method based on the application of method engineering, in order to eliminate downtime and improve the manufacturing cell.Design/methodology/approach: The research strategy employed was a case study applied to a manufacturing company to explore the causes of excessive dead time and low productivity. The methodology used was divided in five steps. The first corresponds to the analysis of the lathe and grinding process; the second is the elaboration of the man-machine diagram to identify dead times; the third is the application of the improvement proposal; the fourth is the redistribution of the cell to optimize the process; the fifth is to conclude from the results obtained.Findings: With the proposed method, the downtime was reduced by 41% and only 50% of the available labor is required, therefore, it is concluded that the method can be used to redesign manufacturing cells.Research limitations/implications: This research was limited to analyzing and improving human-machine interaction, since work is not just the machine, or the individual alone, or the individual manipulating the machine, therefore, no other tools were used to improve the time of machines operation.Practical implications: Designing a manufacturing cell that allows the operator to do his job with less fatigue and not adapt the operator to the job, as commonly happens.Social implications: Companies must show a greater interest in occupational health by including human capital in their optimization plans to avoid future harm to workers.Originality/value: The key contribution of this paper focused on developing a novel and practical methodology to design or re-design manufacturing cells to improve productivity considering the human factor, inspired by the main concepts of method engineering.


2018 ◽  
Vol 16 (1) ◽  
pp. 1-6
Author(s):  
Samilla Thalitta Macedo da Silva ◽  
Guilherme Canuto da Silva ◽  
Paulo Carlos Kaminski

Author(s):  
Miriam Pekarčíková ◽  
Peter Trebuňa ◽  
Marek Kliment ◽  
Michal Dic

We are entering a new era of human-machine interaction and it is essential to underestimate the importance of people in the digital factory. Digital factories require a new way of working, this has several implications. The composition of the workforce wants to change, and companies want to be adequately employed and retain employees accordingly. It is equally important to work with people before and during the implementation of new technologies. The paper addresses the potential that the integration of digital and human labour can offer.


Author(s):  
Che-Wei Huang ◽  
Roland Maas ◽  
Sri Harish Mallidi ◽  
Björn Hoffmeister

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.


Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.


ATZ worldwide ◽  
2021 ◽  
Vol 123 (3) ◽  
pp. 46-49
Author(s):  
Tobias Hesse ◽  
Michael Oehl ◽  
Uwe Drewitz ◽  
Meike Jipp

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.


Small Methods ◽  
2021 ◽  
pp. 2001041
Author(s):  
Faliang He ◽  
Xingyan You ◽  
Weiguo Wang ◽  
Tian Bai ◽  
Gaofei Xue ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document