scholarly journals Industrial Assistance Systems to Enhance Human–Machine Interaction and Operator’s Capabilities in Assembly

2021 ◽  
pp. 129-161
Author(s):  
Benedikt G. Mark ◽  
Erwin Rauch ◽  
Dominik T. Matt
Keyword(s):  
Industry 4.0 ◽  
Human Machine Interaction ◽  
Daily Production ◽  
Industrial Assembly ◽  
Future Challenges ◽  
Lot Sizes ◽  
Assistance Systems ◽  
Technical Systems ◽  
Machine Interaction ◽  
Insight Into

AbstractIn the context of digitalization and Industry 4.0, the world of work is changing comprehensively. Smaller lot sizes and increasing variability of products in the modern industrial production present new challenges for operators working in manual assembly. Industrial assistance systems help the worker during these production tasks to enhance their capabilities. The development of these systems is not only characterized by questions of the potential feasibility of new technical systems but also by the possibilities of a closer cooperation between humans and machines with the aim to synergize the outstanding abilities of humans with the special features of machines to bring together the best from both worlds. This chapter presents solutions for human–machine interaction and automation and delivers insight into different possibilities to enhance the various types of operator’s skills in industrial assembly. With this knowledge, each worker can be individually equipped with suitable supporting systems in order to be best prepared for future challenges in the daily production.

Industry 4.0: Some Challenges and Opportunities for Reliability Engineering

2019 ◽  
Vol 2 (1) ◽  
pp. 23-34
Author(s):  
Mohammad Ali Farsi ◽  
Enrico Zio
Keyword(s):  
Industry 4.0 ◽  
Health Management ◽  
System Modeling ◽  
Cyber Physical System ◽  
Reliability Engineering ◽  
Human Machine Interaction ◽  
New Directions ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
Machine Interaction

According to the development of Industry 4.0 and increase the integration of digital, physical and human worlds, reliability engineering must evolve for addressing the existing and future challenges about that. In this paper, the principle of Industry 4.0 is presented and some of these challenges and opportunities for reliability engineering are discussed. New directions for research in system modeling, big data analysis, health management, cyber-physical system, human-machine interaction, uncertainty, jointly optimization, communication, and interfaces are proposed. Each topic can be investigated individually, but this paper summarizes them and prepared a vision about reliability engineering for consideration and discussion by the interested scientific community.

Evaluation Of Human Errors And Malfunctions For Minimal Invasive Surgeries In Conventional and Integrated OR Solutions

2013 ◽  
Vol 2 (1) ◽  
pp. 90-91
Author(s):  
A - M Von Saucken ◽  
J Prümper ◽  
M Kraft
Keyword(s):  
Medical Devices ◽  
Minimal Invasive ◽  
Design Guidelines ◽  
Human Machine Interaction ◽  
German Research Foundation ◽  
Human Errors ◽  
German Research ◽  
Technical Systems ◽  
Integrated Or ◽  
Machine Interaction

This German Research Foundation project aims to investigate the human-machine interaction of the operating theatre as a work system and from the results deduce measures and, using consolidated medical devices as an example, develop design guidelines for a prospective development of complex integrated technical systems.

scholarly journals sEMG Based Human Motion Intention Recognition

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Li Zhang ◽  
Geng Liu ◽  
Bing Han ◽  
Zhe Wang ◽  
Tong Zhang
Keyword(s):  
Human Motion ◽  
Human Machine Interaction ◽  
Existing Problems ◽  
Model Based ◽  
Wearable Robots ◽  
Intention Recognition ◽  
Future Challenges ◽  
Bioelectrical Signal ◽  
Machine Interaction ◽  
Motion Intention

Human motion intention recognition is a key to achieve perfect human-machine coordination and wearing comfort of wearable robots. Surface electromyography (sEMG), as a bioelectrical signal, generates prior to the corresponding motion and reflects the human motion intention directly. Thus, a better human-machine interaction can be achieved by using sEMG based motion intention recognition. In this paper, we review and discuss the state of the art of the sEMG based motion intention recognition that is mainly used in detail. According to the method adopted, motion intention recognition is divided into two groups: sEMG-driven musculoskeletal (MS) model based motion intention recognition and machine learning (ML) model based motion intention recognition. The specific models and recognition effects of each study are analyzed and systematically compared. Finally, a discussion of the existing problems in the current studies, major advances, and future challenges is presented.

Integration of Human Factors to Safety Assessments by Human Barrier Interaction

2012 ◽  
pp. 327-339
Author(s):  
Markus Talg ◽  
Malte Hammerl ◽  
Michael Meyer zu Hörste
Keyword(s):  
Human Factors ◽  
Human Error ◽  
Strong Impact ◽  
Human Machine Interaction ◽  
Safety Measures ◽  
Technical Systems ◽  
Safety Assessments ◽  
Error Probabilities ◽  
Machine Interaction ◽  
Sufficient Precision

Human factors have a strong impact on railways safety. However, the assessments of these factors still follow traditional and inadequate approaches. While failure probabilities of technical systems can be measured in sufficient precision, human error probabilities are still estimated in a very rough and vague way. Upon this motivation, the contribution presents a method analyzing human influence in railway applications. The approach of human-barrier-interaction relies on a new model of human behavior, a classic model of human-machine-interaction and a model of safety measures by barriers. Applying the method, human reliability can be assessed in comparative way. An advantage over existing approaches is the substantial combination of cognitive psychology and engineering expertise without unpractical complexity.

scholarly journals The Application of Augmented Reality in the Automotive Industry: A Systematic Literature Review

2020 ◽  
Vol 10 (12) ◽  
pp. 4259 ◽  
Author(s):  
Răzvan Gabriel Boboc ◽  
Florin Gîrbacia ◽  
Eugen Valentin Butilă
Keyword(s):  
Systematic Review ◽  
Augmented Reality ◽  
Automotive Industry ◽  
New Technology ◽  
Human Machine Interaction ◽  
Main Research ◽  
Potential Applications ◽  
Research Questions ◽  
Machine Interaction ◽  
Insight Into

Augmented reality (AR) is a fairly new technology enabling human machine interaction by superimposing virtual information on a real environment. Potential applications can be found in many areas of research from recent years. This study presents a systematic review of existing AR systems in the automotive field, synthesizing 55 studies from 2002 to 2019. The main research questions are: where AR technology has been applied within the automotive industry, what is the purpose of its application, what are the general characteristics of these systems, and what are the emphasized benefits and challenges of using AR in this field? The aim of this paper is to provide an insight into the AR applications and technologies in the automotive field.

Sign in / Sign up

Export Citation Format

Share Document