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Digital Analytical Sciences
(2019)
Based on inductive reasoning scientific inquiry in Analytical Sciences has a long tradition. The talk addresses in which way the digital transformation will change the scientific paradigm in Analytical Sciences to a data-driven discipline. Three main areas, integration, instruments, and methods, are discussed in their transformation through machine learning and other digital tools. Finally, some shortcomings and pitfalls in the deployments of algorithmic shortcuts are illustrated.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. The potential of digital technologies belongs to these.
A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. At the same time, we need to move towards knowledge-based production that takes into account all essential equipment, process and control data from plants and laboratories and makes valuable expertise available and transferable. The potential of data from production together with its contextual information is often not yet consistently used today for a comprehensive understanding of production.
By giving examples this paper outlines a possible more holistic approach to digitalisation and the use of machine-based methods in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Companies in the chemical industry have to tread new paths in order to survive successfully in a changed environment. This includes, in particular, the potential of digital technologies. The full integration and intelligent networking of systems and processes is making slow progress.
This talk is a tribute to the field level. It wants to encourage a more holistic approach to the digitalisation of the process industry based on smart sensors, actuators and communication and provides information on current technical perspectives, such as the "one-network paradigm", ad-hoc networking, edge computing, FPGAs, virtual machines or blockchain. These give smart sensors, actuators and communication a completely new perspective.
The talk gives an introduction into gas metal arc welding and its relation to plasma science as well as current challenges in welding research concerning research data management and the application of the FAIR principles.
The WelDX project is introduced and the main goals are discussed and contrasted with the current features of the weldx API.
Different internal and public facing use cases focusing on research data management and their implementation using weldx are presented.
The interactive part of the presentation displays some advanced multi layer use cases and data analysis using the weldx API as well as the integration of materials properties into weldx.
The talk motivates and introduces the WelDX project and the proposed solutions for current challenges in the field of research data management and Open Science practices in welding research.
Using an exemplary welding dataset based on the joint and welding process design of offshore structures, advanced data fusion and analysis capabilities are demonstrated.
The dataset shown consists of a complex welding sequence covering multiple weld layers with varying process parameters and adaptive weaving motions to cover manufacturing tolerances. In the presentation, an interactive exploration of the dataset contents in the spatial domain is presented. Furthermore, transformation between spatial and time domain of the data is demonstrated.
In addition to data gathered during the welding process, the integration of downstream testing data and results is also explained. For demonstration, integration of weld seam cross section images and Vickers hardness mapping test results into the dataset are explained an demonstrated. The testing data is set into context with the welding process information.
Finally, implications for advancements in research data management for WAAM and AI applications are discussed.
Global Status and Trends in Digital Transformation and Conformity Assessment – The Case of Germany
(2022)
This presentation summarizes findings from the first comprehensive study on digitalization in conformity assessment worldwide. The reults are based on data from a survey among conformity assessment bodies (CABs) in Germany conducted in 2022, as well as some first insights from Latin American countries. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
The study on CABs is part of a global project that covers various countries (see www.qi-fokus.de).
This presentation summarizes major findings from an international study in 16 countries and regions on digital transformation in conformity assessment bodies such as testing and calibration laboratories or certification and inspection bodies. It draws from survey data of 1.476 participants and specifically highlights findings on the digital maturity of the organizations, providing an international comparison.