Sociotechnical Systems in the Textile Industry

i-com ◽  
2017 ◽  
Vol 16 (2) ◽  
pp. 153-164 ◽  
Author(s):  
Andrea Altepost ◽  
Mario Löhrer ◽  
Nenja Ziesen ◽  
Marco Saggiomo ◽  
Niklas Strüver ◽  
...  
Keyword(s):  
Textile Industry ◽  
New Technologies ◽  
Holistic Approach ◽  
Sociotechnical Systems ◽  
Assistance System ◽  
Shop Floor ◽  
Organizational Changes ◽  
Learning Techniques ◽  
Organizational Demands ◽  
Assistance Systems

AbstractThis article delineates the work of an interdisciplinary research group concerning the implementation of a digital assistance system in the German textile industry. Using a holistic approach, researchers from different disciplines contribute to the design of an integrated socio-technical method that guides industrial actors in developing and implementing digital assistance systems that are applicable on the shop-floor level and at the same time take into account various social and organizational demands. Following this approach, the development of new technologies is coordinated with innovative social practices, for example, learning techniques or organizational changes. Furthermore, aspired users of the assistance system participate in the project by contributing their expertise of the working progress as well as by defining requirements essential towards addressing the various challenges at hand. The conceptual outline and early findings of the project, including the development of a prototype of the assistance system, are presented in this article.

Digitale Assistenzsysteme in der Produktion*/Innovative assistance systems in production

2017 ◽  
Vol 107 (03) ◽  
pp. 124-128
Author(s):  
L. Merkel ◽  
J, Starz ◽  
C. Schultz ◽  
S. Braunreuther ◽  
G. Prof. Reinhart
Keyword(s):  
New Technologies ◽  
Assistance System ◽  
Individual Worker ◽  
Best Fitting ◽  
Assistance Systems ◽  
Worker Support ◽  
Selection Of

Digitale Assistenzsysteme in der Produktion helfen, zunehmend komplex werdende Arbeitsaufgaben zu beherrschen. Dafür entstehen im Zuge der Digitalisierung der Produktion forschungsseitig zahlreiche neue Möglichkeiten individueller Werkerunterstützung. Das hier vorgestellte entwickelte Modell gestattet eine detaillierte Beschreibung der Fähigkeiten und Technologien von Komponenten eines Assistenzsystems. Durch einen Abgleich von spezifischen Anforderungen eines Anwendungsfalls mit den Fähigkeiten des Assistenzsystems soll die Auswahl eines geeigneten Assistenzsystems ermöglicht werden.   Digital assistance systems help to master tasks with growing complexity in production. Currently, a lot of research aims at developing new technologies for individual worker support. This paper presents a model for a detailed description of capabilities and technologies used for components in assistance systems. By matching a given task’s requirements with the capabilities of an assistance system, the selection of the best fitting assistance system can be achieved.

scholarly journals Geocomputing, New Technologies and Historical Analysis: Tools for a Changing Planet

Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 9
Author(s):  
Sebastiano Trevisani
Keyword(s):  
Quantitative Analysis ◽  
Philosophy Of Science ◽  
New Technologies ◽  
Historical Analysis ◽  
Holistic Approach ◽  
Research Topic ◽  
The Other ◽  
Historical Records ◽  
The Earth ◽  
The Relationship

Modern Earth Scientists need also to interact with other disciplines, apparently far from the Earth Sciences and Engineering. Disciplines related to history and philosophy of science are emblematic from this perspective. From one side, the quantitative analysis of information extracted from historical records (documents, maps, paintings, etc.) represents an exciting research topic, requiring a truly holistic approach. On the other side, epistemological and philosophy of science considerations on the relationship between geoscience and society in history are of fundamental importance for understanding past, present and future geosphere-anthroposphere interlinked dynamics.

Digitalisierung von additiven Fertigungseinheiten/Digitalization of additive manufacturing units

2021 ◽  
Vol 111 (09) ◽  
pp. 633-637
Author(s):  
Maximilian Vogt ◽  
Julian Ulrich Weber ◽  
Vishnuu Jothi Prakash
Keyword(s):  
Additive Manufacturing ◽  
Feasible Solution ◽  
Spare Parts ◽  
Assistance System ◽  
Remote Locations ◽  
Assistance Systems ◽  
Mobile Manufacturing ◽  
Manufacturing Technologies

Additive Fertigungstechnologien erlauben die bedarfsgerechte Produktion von individuellen Ersatzteilen. Durch Einsatz mobiler Fertigungseinheiten lässt sich mithilfe dieser Verfahren die Resilienz von isolierten Produktionsstätten erhöhen. Um auch außerfachliches Personal zur Bedienung an entlegenen Einsatzorten zu befähigen, stellen digitale Assistenzsysteme eine mögliche Lösung dar. In diesem Beitrag wird ein solches Assistenzsystem zur Begleitung der manuellen Tätigkeiten beim roboterbasierten DED-Prozess in einer mobilen Fertigungseinheit diskutiert.   Additive manufacturing technologies enable the demand-driven production of individual spare parts. By using mobile manufacturing units, these processes can be used to increase the resilience of isolated production sites. In order to enable non-specialized personnel to operate at remote locations, digital assistance systems are a feasible solution. This paper discusses such an assistance system to accompany manual operations of the robot-based DED process in a mobile manufacturing unit.

Assessing the Accuracy of Fault Interpretation using Machine Learning Techniques when Risking Faults for CO2 Storage Site Assessment

2021 ◽  
pp. 1-55
Author(s):  
Emma A. H. Michie ◽  
Behzad Alaei ◽  
Alvar Braathen
Keyword(s):  
Deep Learning ◽  
New Technologies ◽  
Co2 Storage ◽  
Fault Reactivation ◽  
Machine Learning Techniques ◽  
Close Similarity ◽  
Storage Site ◽  
Site Assessment ◽  
Learning Techniques ◽  
Fault Interpretation

Generating an accurate model of the subsurface for the purpose of assessing the feasibility of a CO2 storage site is crucial. In particular, how faults are interpreted is likely to influence the predicted capacity and integrity of the reservoir; whether this is through identifying high risk areas along the fault, where fluid is likely to flow across the fault, or by assessing the reactivation potential of the fault with increased pressure, causing fluid to flow up the fault. New technologies allow users to interpret faults effortlessly, and in much quicker time, utilizing methods such as Deep Learning. These Deep Learning techniques use knowledge from Neural Networks to allow end-users to compute areas where faults are likely to occur. Although these new technologies may be attractive due to reduced interpretation time, it is important to understand the inherent uncertainties in their ability to predict accurate fault geometries. Here, we compare Deep Learning fault interpretation versus manual fault interpretation, and can see distinct differences to those faults where significant ambiguity exists due to poor seismic resolution at the fault; we observe an increased irregularity when Deep Learning methods are used over conventional manual interpretation. This can result in significant differences between the resulting analyses, such as fault reactivation potential. Conversely, we observe that well-imaged faults show a close similarity between the resulting fault surfaces when both Deep Learning and manual fault interpretation methods are employed, and hence we also observe a close similarity between any attributes and fault analyses made.

scholarly journals Predicting Academic Course Preference using Hadoop

2019 ◽  
Vol 8 (4) ◽  
pp. 2527-2530
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
New Technologies ◽  
Parallel Applications ◽  
Distributed File System ◽  
Industrial Training ◽  
Effective Learning ◽  
Meaningful Information ◽  
Learning Techniques ◽  
Mining Tools

These days new technologies have been introduced by this new academic trends also have been came into existence into the education system. And this leads to huge amounts of data which makes a big challenge for the students to store the preferred course. For this many data mining tools have been invented to convert the unregulated data into structured format to understand the meaningful information. As we know that Hadoop is a distributed file system which is used to hold huge amounts of data this stores the files in a redundant fashion across multiple machines. Due to this it leads to failure and parallel applications do not work. To avoid this problem we are using Mapreduce for decision making of students in order to choose their preferred course for industrial training purpose for their effective learning techniques to increase their knowledge and capability.

Strengthening radiation protection education and training of health professionals: conclusions from an IAEA meeting

2021 ◽  
Author(s):  
Jenia Vassileva ◽  
Kimberly E Applegate ◽  
Graciano Paulo ◽  
Eliseo Vano ◽  
Ola Holmberg
Keyword(s):  
Radiation Protection ◽  
Health Professionals ◽  
New Technologies ◽  
Holistic Approach ◽  
Education And Training ◽  
Energy Agency ◽  
Train The Trainer ◽  
International Consultation ◽  
Training Programmes ◽  
And Training

Abstract In March 2021 the International Atomic Energy Agency (IAEA) organised an online Technical Meeting on Developing Effective Methods for Radiation Protection Education and Training of Health Professionals with attendance of 230 participants representing 66 Member States and 24 international organizations, professional bodies and safety alliances. By means of a pre-meeting survey, presentations by experts, topical panel discussions and post-meeting feedback to the meeting summary, the meeting identified strengths, common weaknesses and possible solutions and actions for improving radiation protection education and training of health professionals. Available guidelines and resources for radiation protection training were also reviewed. The meeting discussion resulted in a strong consensus for the need of: (a) international guidance on education and training in radiation protection and safety for health professionals, (b) an international description of minimum standards of initial and ongoing competence and qualification in radiation protection for relevant professional groups, considering the available recommendations at international and regional levels. The proposed actions include provisions for train-the-trainer credentialing and facility training accreditation, balance between the online and face-to-face training, improved on-the job training, as well as improved inclusion in training programmes of aspects related to application of new technologies, ethical aspects, development of communication skills, and use of software tools for improving justification and optimisation. The need for making the ongoing training practical, applicable, and useful to the trainee was highlighted. The international consultation initiated by the IAEA was appreciated as a good approach to understand and promote coordination and collaboration at all levels, for best results in education and training in radiation protection of health professionals. Implementing such a holistic approach to education and training in radiation protection would contribute towards qualification and competence of health professionals needed to ensure application of high standards for quality and safety in medical uses of ionizing radiation.

/Digitale Assistenzsysteme in der ProduktionDigital assistance systems in the production area – Specifying the relevant functions

2020 ◽  
Vol 110 (03) ◽  
pp. 103-107
Author(s):  
Christian Bayer ◽  
Rami Makhlouf ◽  
Joachim Metternich
Keyword(s):  
Assistance System ◽  
Production Area ◽  
Assistance Systems

Die Diversifikation von Produkten erhöht die Komplexität in der Produktion, wodurch die Anforderungen an die Beschäftigten steigen. Durch den Einsatz digitaler Assistenzsysteme kann die menschliche Arbeit in der Produktion unterstützt werden. Dieser Beitrag beschäftigt sich mit den relevanten Funktionen eines digitalen Assistenzsystems als Diskussionsgrundlage bei deren Einführung.   The diversification of products makes production more complex and jobs more demanding. Digital assistance systems can support human work in the production area. This article deals with the relevant functions of a digital assistance system as a basis for discussion when implementing them.

Coda: Learning to Let Go and Love Other Worlds

2018 ◽  
pp. 159-174
Author(s):  
Jesse Goldstein
Keyword(s):  
New Technologies ◽  
Profit Maximization ◽  
Ways Of Knowing ◽  
Sociotechnical Systems ◽  
Hard Work ◽  
Political Struggle ◽  
Smart Money ◽  
Uncertain Future ◽  
New Policies ◽  
Deep Sense

To the extent that investors, entrepreneurs and businesspeople – or anyone else who has internalized the smarts of smart money – act as representatives of our collectively creative capacities, then new technologies, and perhaps even new policies and forms of governance, will be oriented around greening what we have – improving our lives and our planet – without ever questioning whether it is precisely these lives in possession of this planet that need to be challenged and ultimately transformed. This chapter points towards evaluating sociotechnical systems within what decolonial scholars would call a pluriversal context, one in which modern technological knowledge is considered to be one out of many legitimate ways of knowing and engaging with the world. Is it possible that there exists a green spirit that goes beyond capitalism; that we are more and better than this relatively simplistic, inward-looking and self-obsessed logic of profit-maximization? Liberating this green spirit will require hard work, political struggle, unexpected alliances and a deep sense of humility; we face a messy and uncertain future as we engage with the long and hard work of transforming our socio-ecological lives.

Human Resources as Manager of the Human Imprint

2009 ◽  
pp. 457-463
Author(s):  
Charmine E.J. Härtel
Keyword(s):  
Human Resources ◽  
Human Resource ◽  
Technological Innovation ◽  
Intellectual Capital ◽  
New Technologies ◽  
Holistic Approach ◽  
Pivotal Role ◽  
Organizational Systems ◽  
Use Of Technology ◽  
Effective Use

Knowledge is the currency of the new economy and consequently information is power. For this reason, it is a business imperative to grow and shape intellectual capital. Human resource management (HRM) plays a pivotal role in creating and growing intellectual capital and embedding it within organizational systems. Previous studies in HRM have demonstrated the connection between technological innovation and HRM in two conspicuously different ways. Specifically, some have illustrated how HR strategies can enhance technological innovation in organizations (Gloet & Terziovski, 2004; Jiménez-Jiménez & Sanz-Valle, 2005) while others have shown ways in which HR functions can be aligned and made more efficient by the effective use of technology (Ashbaugh & Miranda, 2002; Broderick & Boudreau, 1992; Bussler & Davis, 2001/2002). In this article, a more holistic approach is taken in viewing technology as both an input and an outcome of effective HRM. To this end, the aim here is to provide a description of some of the key ways in which HRM can enhance the development, implementation, and success of new technologies as well as how HRM can enhance its own value through the use of new technologies.

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