| 1. |
- Bleser, Gabriele, et al.
(författare)
-
Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks
- 2015
-
Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:6
-
Tidskriftsartikel (refereegranskat)abstract
- Today, the workflows that are involved in industrial assembly and production activities are becoming increasingly complex. To efficiently and safely perform these workflows is demanding on the workers, in particular when it comes to infrequent or repetitive tasks. This burden on the workers can be eased by introducing smart assistance systems. This article presents a scalable concept and an integrated system demonstrator designed for this purpose. The basic idea is to learn workflows from observing multiple expert operators and then transfer the learnt workflow models to novice users. Being entirely learning-based, the proposed system can be applied to various tasks and domains. The above idea has been realized in a prototype, which combines components pushing the state of the art of hardware and software designed with interoperability in mind. The emphasis of this article is on the algorithms developed for the prototype: 1) fusion of inertial and visual sensor information from an on-body sensor network (BSN) to robustly track the user’s pose in magnetically polluted environments; 2) learning-based computer vision algorithms to map the workspace, localize the sensor with respect to the workspace and capture objects, even as they are carried; 3) domain-independent and robust workflow recovery and monitoring algorithms based on spatiotemporal pairwise relations deduced from object and user movement with respect to the scene; and 4) context-sensitive augmented reality (AR) user feedback using a head-mounted display (HMD). A distinguishing key feature of the developed algorithms is that they all operate solely on data from the on-body sensor network and that no external instrumentation is needed. The feasibility of the chosen approach for the complete action-perception-feedback loop is demonstrated on three increasingly complex datasets representing manual industrial tasks. These limited size datasets indicate and highlight the potential of the chosen technology as a combined entity as well as point out limitations of the system.
|
|
| 2. |
- David, Romero, et al.
(författare)
-
TOWARDS AN OPERATOR 4.0 TYPOLOGY: A HUMAN-CENTRIC PERSPECTIVE ON THE FOURTH INDUSTRIAL REVOLUTION TECHNOLOGIES
- 2016
-
Ingår i: International Conference on Computers & Industrial Engineering CIE 46.
-
Konferensbidrag (refereegranskat)abstract
- This paper presents early concepts and future projections of the so-called ‘Operator 4.0’, understood as a smart, skilled operator who performs not only cooperative work with robots but also aided work by machines as and if needed by means of human cyber-physical systems, advanced human-machine interaction technologies and adaptive automation towards achieving human-automation symbiosis work systems. This research introduces an Operator 4.0 typology as well as exploring a set of key enabling technologies that can support the development of human-automation symbiosis work systems for the Operator 4.0 in the Factory of the Future defined within the Industry 4.0 framework.
|
|
| 3. |
- Romero, David, et al.
(författare)
-
Digitalizing Occupational Health, Safety and Productivity for the Operator 4.0
- 2018
-
Ingår i: IFIP Advances in Information and Communication Technology. - Cham : Springer International Publishing. - 1868-4238 .- 1868-422X. ; 536, s. 473-481
-
Konferensbidrag (refereegranskat)abstract
- Industry 4.0 technologies, such as enterprise wearables, can foster better industrial hygiene to keep operators healthy, safe, and motivated within emerging cyber-physical production systems. This paper provides an optimistic perspective on opportunities evolving from wearable devices in an Industry 4.0 workplace environment to support occupational health, safety and productivity for the Operator 4.0. Examples of technical solutions, and their associated application scenarios, are presented showcasing how enterprise wearables may foster detection of situations that involve potential occupational risks before they actually occur at smart shopfloors.
|
|
| 4. |
- Romero, David, et al.
(författare)
-
Social factory architecture: Social networking services and production scenarios through the social internet of things, services and people for the social operator 4.0
- 2017
-
Ingår i: IFIP Advances in Information and Communication Technology. - Cham : Springer International Publishing. - 1868-4238 .- 1868-422X. - 9783319669229 ; 513, s. 265-273
-
Konferensbidrag (refereegranskat)abstract
- The prevailing industrial digitalisation flagship initiative, Industrie 4.0, gathers a substantial part of its functionality from the human in the system. This will drive a need for focus on both human and social dimensions of technology. The paper explores the roles of the Social Operator 4.0 in smart and social factory environments, where humans, machines and software systems will cooperate (socialise) in real-time to support manufacturing and services operations. A Social Factory Architecture based on adaptive, collaborative and intelligent multi-agent system is proposed for enabling such cooperation. Further, production scenarios are proposed, to show how social operators, social machines, and social software systems will communicate and cooperate via enterprise social networking services to accomplish production goals in the Social Internet of Things, Services and People.
|
|
