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The successful shift to NDE 4.0 will not only require developing and embracing new technologies associated with the fourth industrial revolution or becoming an integral part of the overall Industry 4.0, but also developing and adopting new ways of working. It is undoubtful that people will remain in charge of the inspections. However, it is arguable if the current “procedure-following” “level I-III” paradigm can withstand the changes that come along NDE 4.0. With the increased autonomy and interconnectedness expected with NDT 4.0, the majority of traditional NDE tasks will no longer be needed. Instead, different skills, such as that of programming and adapting systems, as well as problem solving, will become vital for the inspections. Therefore, we suggest that a new paradigm is needed—one in which inspector roles and, thus, also the requirements will have to be reinvented. We expect the inspectors to be relieved from the tedious and error prone aspects of the current system and to take responsibility for increasingly complex automated systems and work in closer collaboration with other experts. Thus, we propose that the traditional inspector roles will be transformed into that of the system developer, caretaker and problem solver, each requiring a specific set of skills and assuming different responsibilities. In this talk, we will present the new roles and discuss the challenges that may arise with them.
Typically, the near-eutectic Al-Si alloys consist of highly interconnected three-dimensional network of the eutectic Silicon (Si) and intermetallics embedded into Aluminium (Al) matrix. For further improvement of the mechanical properties of such alloys, often, one single ceramic reinforcement phase, e.g. silicon carbide (SiC) or aluminium oxide (Al2O3) in the form of fibres or particles is added. However, hybrid reinforcements (fibres and particles) can further improve wear resistance and fracture toughness, and additionally, reduce anisotropy of the material. The engineering of metal matrix composites (MMC) for specific application requirements benefits from a comprehensive knowledge of the failure behaviour. Therefore, damage evolution under compression was investigated on:
- pure near-eutectic AlSi12CuMgNi matrix alloy
- type I: matrix reinforced with random-planar oriented Al2O3 short fibres (15 vol.%)
- type II: matrix reinforced with random-planar oriented Al2O3 short fibres (7 vol.%) and additional SiC particles (15 vol.%)
The analysis of damage mechanism was carried out in two rather independent but complementary studies. First, selected sister samples of every material were exposed to quasi-static compression (traverse control). The compression tests were interrupted at different strain levels. Miniature cylinders with a diameter of 1mm were extracted from the pre-strained samples and investigated by synchrotron computed tomography (SX-µCT) with a spatial resolution of about 0.7 µm. For the pure matrix alloy, microcracks are confined to the intermetallic particles and to the eutectic Si, hence no damage was observed in the Aluminium. The composite type II revealed a more effective strain accumulation (less damage) than type I at low plastic strain (up to 5 %), but a more catastrophic damage development due to cracking of the SiC clusters at higher strain levels.
The second approach to study the damage initiation and accumulation in the materials subjected to compressive load was Acoustic Emission (AE) analysis. In this case the in-situ monitoring of the acoustic emission signal was performed during compression tests on specimens with dimension of several mm. For all three material types, AE activity set at 2% strain. Differences in AE behaviour of the three materials was proven based on AE hitrate, signal peak amplitudes as well as weighted peak frequencies (WPF). Future work focuses on combination of AE and SX-µCT aiming for more detailed knowledge on damage mechanism of metal matrix composites.
Nanomaterials bring various benefits and have become a part of our daily lives. However, the risks emerging from nanotechnology need to be minimized and controlled at the regulatory level and therefore, there is a need for nanorisk governance. One of the prerequisites for successful nanorisk governance is the availability of high-quality data on nanomaterials and their impact with the human body and the environment. In recent decades, a countless number of publications and studies on nanomaterials and their properties have been produced due to the fast development of nanotechnology. Despite such a vast amount of data and information, there are certain knowledge gaps hindering an efficient nanorisk governance process. Knowing the state of the available data and information is an important requirement for any decision maker in dealing with risks. In the specific case of nanotechnology, where most of the risks are complex, ambiguous, and uncertain in nature, it is essential to obtain complete data and metadata, to fill knowledge gaps, and to transform the available knowledge into functional knowledge. This can become possible using a novel approach developed within the NANORIGO project (Grant agreement No. 814530) – the Knowledge Readiness Level (KaRL). In analogy to NASA’s Technology Readiness Levels (TRLs), we define KaRLs as a categorization system of data, information, and knowledge which enables transformation of data and information into functional knowledge for nanorisk governance. Our approach goes beyond the technical curation of data and metadata and involves quality and completeness filters, regulatory compliance requirements, nanorisk-related tools, and most importantly, human input (inclusion of all stakeholder groups). With the KaRL approach we also address key issues in nanotechnology such as societal and ethical concerns, circular economies and sustainability, the Green Deal, and the traceability of data, knowledge, and decisions. The KaRL approach could be used for nanorisk governance by a nanorisk governance council (NRGC), which is currently under development by three EU projects (NANORIGO, GOV4NANO, and RISKGONE).
Nanomaterials bring various benefits and have become a part of our daily lives. However, the risks emerging from nanotechnology need to be minimized and controlled at the regulatory level and therefore, there is a need for nanorisk governance. One of the prerequisites for successful nanorisk governance is the availability of high-quality data on nanomaterials and their impact with the human body and the environment. In recent decades, a countless number of publications and studies on nanomaterials and their properties have been produced due to the fast development of nanotechnology. Despite such a vast amount of data and information, there are certain knowledge gaps hindering an efficient nanorisk governance process. Knowing the state of the available data and information is an important requirement for any decision maker in dealing with risks. In the specific case of nanotechnology, where most of the risks are complex, ambiguous, and uncertain in nature, it is essential to obtain complete data and metadata, to fill knowledge gaps, and to transform the available knowledge into functional knowledge. This can become possible using a novel approach developed within the NANORIGO project (Grant agreement No. 814530) – the Knowledge Readiness Level (KaRL). In analogy to NASA’s Technology Readiness Levels (TRLs), we define KaRLs as a categorization system of data, information, and knowledge which enables transformation of data and information into functional knowledge for nanorisk governance. Our approach goes beyond the technical curation of data and metadata and involves quality and completeness filters, regulatory compliance requirements, nanorisk-related tools, and most importantly, human input (inclusion of all stakeholder groups). With the KaRL approach we also address key issues in nanotechnology such as societal and ethical concerns, circular economies and sustainability, the Green Deal, and the traceability of data, knowledge, and decisions. The KaRL approach could be used for nanorisk governance by a nanorisk governance council (NRGC), which is currently under development by three EU projects (NANORIGO, GOV4NANO, and RISKGONE).
In the field of non-destructive testing (NDT) in civil engineering, a large number of measurement data are collected. Although they serve as a basis for scientific analyses, there is still no uniform representation of the data. An analysis of various distributed data sets across different test objects is therefore only possible with high manual effort.
We present a system architecture for an integrated data management of distributed data sets based on Semantic Web technologies. The approach is essentially based on a mathematical model - the so-called ontology - which represents the knowledge of our domain NDT. The ontology developed by us is linked to data sources and thus describes the semantic meaning of the data. Furthermore, the ontology acts as a central concept for database access. Non-domain data sources can be easily integrated by linking them to the NDT construction ontology and are directly available for generic use in the sense of digitization. Based on an extensive literature research, we outline the possibilities that this offers for NDT in civil engineering, such as computer-aided sorting, analysis, recognition and explanation of relationships (explainable AI) for several million measurement data.
The expected benefits of this approach of knowledge representation and data access for the NDT community are an expansion of knowledge through data exchange in research (interoperability), the scientific exploitation of large existing data sources with data-based methods (such as image recognition, measurement uncertainty calculations, factor analysis, material characterization) and finally a simplified exchange of NDT data with engineering models and thus with the construction industry.
Ontologies are already the core of numerous intelligent systems such as building information modeling or research databases. This contribution gives an overview of the range of tools we are currently creating to communicate with them.
X-ray back scatter imaging is rarely applied compared to classical X-ray projection imaging. 20 years ago the company Philips developed “COMSCAN”, a first application case in the aircraft industry, which allowed even a depth resolution using back scatter imaging. The company AS&E in Boston offers back scatter imaging solutions for the security market. Their principle is to scan the object with a highly collimated X-ray needle beam from one side only and detect the backscattered radiation by a large area detector side by side with the collimation wheel. A new prototype is investigated at BAM for application and optimization in non-destructive testing. As modern industrial application field in-situ testing in additive manufacturing is targeted. The accessibility of the printed part during the production process is very limited. This prevent the application of a two sided X-ray inspection or Computed Tomography, were an rotation of the object is required to acquire projections from 360 degrees. An important advantage for the X-ray back scatter technique are also the materials used in additive manufacturing (polymers, ceramics, light metals like Aluminum or Titanium). These materials with lower density and lower Z values give better scatter signals than metals with higher densities and Z values. The back scatter intensity decreases with increasing density and Z value of the material. But the requirements on spatial resolution and contrast sensitivity are more stringent for non-destructive testing of additive manufactured parts compared to the security area. In NDT sizes of indications smaller than 1 mm have to be detected clearly. The investigation of these limits on a stateof-the-art prototype for X-ray back scattering using rotating collimated X-ray needle beams is a part of the BAM project “ProMoAM”. The contribution shows first results of the optimization for NDT and the achieved application limits for several example cases.
The detection of cracks before the failure is highly significant when it comes to safety-relevant structures. Crack detection in metallic samples at high surface temperature is one of the challenging situation in manufacturing industries. Laser thermography has already proved its detection capability of surface cracks in metallic samples at room temperature. In this work a continuous wave (CW) laser use to generate a laser, which is using to scan the metal surface with notch. The corresponding heat distribution on the surface monitored using infrared thermal (IR) camera. A simplified 3D model for laser thermography is developed and validated with experimental results. A dedicated image processing algorithm developed to improve the detectability of the cracks. To understand the dependency of surface temperature, laser power, laser scanning speed etc. in defect detection, we carried out parametric studies with our validated model. Here we report the capability of laser thermography in crack detection at elevated temperature.
qNMR provides the most universally applicable form of direct concentration or purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties.
The workshop presents basic terms of statistics and uncertainty analysis, which are the basis for qNMR spectroscopy and data analysis such as, e.g., standard deviations, linear regression, significance tests, etc. and gives typical examples of applications in qNMR spectroscopy.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control.
The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs.
The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control and gives also an overview on direct dissolution studies of API cocrystals.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors will simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. This is particularly important for concepts like self-diagnostics, self-calibration and self-configuration/parameterization. Intelligent field devices as parts of digital field networks, Inter-net Protocol (IP)-based connectivity and web interfaces, as well as advanced data analysis soft-ware will provide the basis for future projects like Industrie 4.0, Factory of the Future, or Industrial Internet of Things (IIoT). The talk summarizes the currently discussed general requirements for process sensors 4.0 and introduces an online NMR sensor as example. This sensor was developed to provide integrated control and sensing for sustainable operation of flexible intensified processes (CONSENS) funded by the European Union’s Horizon 2020 research and innovation programme.
Smart functions of sensors simplify their use and enable plug-and-play, even though they are more complex. This is particularly important for, self-diagnostics, self-calibration and self-configuration/parameterization. Intelligent field devices, digital field networks, Internet Protocol (IP)-enabled connectivity and web services, historians, and advanced data analysis software are providing the basis for the future project “Industrie 4.0” and Industrial Internet of Things (IIoT).
Important smart features include connectivity and communication ability according to a unified protocol (OPC-UA currently most widely discussed), maintenance and operating functions, traceability and compliance, virtual description to support a continuous engineering, and well as interaction capabilities between sensors. This is a prerequisite for the realization of Cyber Physical Systems (CPS) within these future automation concepts for the process industry. Therefore, smart process sensors enable new business models for users, device manufacturers, and service providers.
The departure from current automation to smart sensor has already begun. Further development is based on the actual situation over several steps. Possible perspectives will be via additional communication channels to mobile devices, bidirectional communication, integration of the cloud and virtualization. The integration of virtual runtime environments can provide a more flexible topology for process control environments.
The talk summarizes the currently discussed requirements to process sensors 4.0 and introduces an online NMR sensor as an example, which was developed in the EU project CONSENS.
The talk reflects how PAT could be applied in future developments ofpharma manufacturing. It shows the benefits, increase quality, size and increasing speed of production with significant reduction of quality costs, which are possible. Using Smart Sensors and model based data evaluation methods are the key to reduce set-up times and costs. Industry 4.0 will help shape the Pharmaceutical industry of tomorrow. This is demonstrated by an example using modular production units for Continuous Manufacturing. The development of a smart online NMR analyser is shown.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analysers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack.
Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. If these are not available, there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS (Integrated Control and Sensing) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups.
The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method.
The Royal Society of Chemistry NMR Discussion Group and Molecular Spectroscopy Group would like to invite you to the 2017 Spring Meeting, which will be held at GlaxoSmithKline (GSK), Stevenage. The theme for the meeting is “Low level detection and quantification by NMR” and different NMR technologies, including solution state NMR, solid state NMR and benchtop/low field NMR will be discussed. The presentations will cover a range of NMR related disciplines, including conventional low level detection and quantification, the use of cryoprobes, quantification of polymorphism using ssNMR and also methods for spectral simplification. Recent developments and applications of hyperpolarisation techniques, within both solution state and solid state NMR, will be presented in conjunction with the effect these sensitivity enhancements have with respect to quantification and limits of detection.
For reaction monitoring and process control using NMR instruments, in particular, after acquisition of the FID the data needs to be corrected in real-time for common effects using fast interfaces and automated methods. Conventionally, sensors have to be calibrated in a first step to find a response curve between the sensor signal and physical or chemical properties of the sample. In a second step, a model of the response between these parameters (e.g., concentrations) and the targeted quality specifications is needed. Thanks to the direct proportionality of the molar concentrations and the NMR signal, it could directly be used in the near future to relate the process target quality specification to sensor data – also in combination with multiple other sensor or process information.
Low field NMR spectroscopy for sustainable and flexible production of high quality chemical products
(2017)
The main development goal of process industries is to advance the continuous production of high-value products that meet high quality demands in flexible intensified continuous plants by introducing novel online sensing equipment and closed-loop control (CONSENS – integrated control and sensing- is funded from the European Union’s Horizon 2020 research and innovation programme). Therefore, we present the field integration of a benchtop NMR instrument into a modular production environment, focussing on suitable equipment for operation in hazardous areas with risk of explosive atmospheres.
We investigated a pharmaceutical reaction step in order to describe challenges for the experimental design, the evaluation of complex NMR spectra and demonstrate automated data analysis tools.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analysers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack.
Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. If these are not available, there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS (Integrated Control and Sensing [3]) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups.
The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method.
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. An increasing number of applications are reported. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. Tis paves the way for industrial automation in real process environments.
Automated data preparation and analysis are cornerstones for a breakthrough of NMR techniques for process control. Particularly, robust chemometrics as well as automated signal processing methods have to be (further) developed especially for NMR spectroscopy in process control. This becomes even more important for so called “smart sensors” providing the basis for the future project “Industrie 4.0”, and Industrial Internet of Things (IIoT), along with current requirements to process control, model based control, or soft sensing. Data analysis techniques are available but currently mostly used for off-line data analysis to detect the causes of variations in the product quality.
The talk presents current research activities towards process control with compact NMR and reflects “cultural differences” between the interdisciplinary parties involved.
Ugly Spectra and Lousy interfaces – Challenges for Compact NMR Spectroscopy in Process Control
(2016)
With the introduction of advanced process analytical technology, the closeness of key process variables to their limits can be directly controlled and the product can be classified or even released in real time.
Compact NMR instruments can make NMR spectroscopy accessible in industrial and harsh environments for process control.
Online NMR spectroscopy is an excellent tool to study complex reacting multicomponent mixtures and gain process insight and understanding. For online studies under process conditions, flow NMR probes can be used in a wide range of temperature and pressure. This paper compiles the most important aspects towards quantitative process NMR spectroscopy in complex multicomponent mixtures and provides examples. After NMR spectroscopy is introduced as an online method and for technical samples without sample preparation in deuterated solvents, influences of the residence time distribution, pre-magnetization, and cell design are discussed. NMR acquisition and processing parameters as well as data preparation methods are presented and the most practical data analysis strategies are introduced.
Online low-field NMR spectroscopy of an industrial lithiation reaction step for process control
(2016)
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing benchtop NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes.
This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Furthermore, first online spectra of the lithiation reaction in batch mode were acquired in lab scale. The reaction was performed in a 25 mL glass reactor with thermal jackets for temperature control of the reaction mixture. The Li-HMDS was dosed stepwise by using a glass syringe. First spectra in the proton and fluorine domain were recorded online using a flowrate of 3.5 mL min–1 and a simple 5 mm polytetrafluoroethylene tube (PTFE) as a flow cell.
Benchtop nuclear magnetic resonance spectroscopy currently develops to an important analytical tool for both quality control and process monitoring. In contrast to high resolution online NMR (HR-NMR), benchtop NMR can be operated under rough environmental conditions. A continuous re-circulating stream of reaction mixture from the reaction vessel to the NMR spectrometer enables a non-invasive, volume integrating online analyses of reactants and products. Here we investigated the esterification of 2,2,2-trifluoroethanol with acetic acid to 2,2,2-trifluoroethyl acetate both by 1H HR-NMR (500 MHz) and 1H and 19F MR NMR (43 MHz and 40 MHz) as a model system. The parallel online measurement was realized by splitting the flow, which allowed the adjustment of quantitative and independent flow rates, both in the benchtop NMR probe as well as in the HR-NMR probe, in ad-dition to a fast bypass line back to the reactor.