Current and future requirements to industrial analytical infrastructure—part 1: process analytical laboratories

Eisen, Kristina; Eifert, Tobias; Herwig, Christoph; Maiwald, Michael

doi:10.1007/s00216-020-02420-2

Cited by 32 publications

(13 citation statements)

References 4 publications

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“…Another field where vibrational spectroscopy demonstrated to have a great impact is in the so-called process analytical technologies (PAT) [21][22][23][24]. This approach has not only been used to collect chemical information about the process (e.g., spatial and temporal information) to monitor the composition of the product, but also to provide information about the process itself, such as yield, energy input, faults and quality assurance [21][22][23][24]. The implementation of vibrational spectroscopy based on the utilization of different type of sensors has provided a platform for process data analysis and process sensor technology [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…This approach has not only been used to collect chemical information about the process (e.g., spatial and temporal information) to monitor the composition of the product, but also to provide information about the process itself, such as yield, energy input, faults and quality assurance [21][22][23][24]. The implementation of vibrational spectroscopy based on the utilization of different type of sensors has provided a platform for process data analysis and process sensor technology [21][22][23][24]. The data collected by the sensor could be also utilised to provide useful information about other aspects of the process, such as occupational safety, sustainable protection of employees, plant safety, hazardous operating conditions, and to assure environmental protection, providing feedback about the conditions of the industry [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…The implementation of vibrational spectroscopy based on the utilization of different type of sensors has provided a platform for process data analysis and process sensor technology [21][22][23][24]. The data collected by the sensor could be also utilised to provide useful information about other aspects of the process, such as occupational safety, sustainable protection of employees, plant safety, hazardous operating conditions, and to assure environmental protection, providing feedback about the conditions of the industry [21][22][23][24]. The incorporation of these technologies and the development of applications of PAT has increased the demands for a knowledge-based approach [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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The Sample, the Spectra and the Maths—The Critical Pillars in the Development of Robust and Sound Applications of Vibrational Spectroscopy

Cozzolino

2020

Molecules

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The last two decades have witnessed an increasing interest in the use of the so-called rapid analytical methods or high throughput techniques. Most of these applications reported the use of vibrational spectroscopy methods (near infrared (NIR), mid infrared (MIR), and Raman) in a wide range of samples (e.g., food ingredients and natural products). In these applications, the analytical method is integrated with a wide range of multivariate data analysis (MVA) techniques (e.g., pattern recognition, modelling techniques, calibration, etc.) to develop the target application. The availability of modern and inexpensive instrumentation together with the access to easy to use software is determining a steady growth in the number of uses of these technologies. This paper underlines and briefly discusses the three critical pillars—the sample (e.g., sampling, variability, etc.), the spectra and the mathematics (e.g., algorithms, pre-processing, data interpretation, etc.)—that support the development and implementation of vibrational spectroscopy applications.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Sample, the Spectra and the Maths—The Critical Pillars in the Development of Robust and Sound Applications of Vibrational Spectroscopy

Cozzolino

2020

Molecules

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“…We are convinced that the benefits of establishing and operating smart (process) analytical labs, as mentioned in Part 1 [3] will become easier accessible via use of PAT along the whole asset life cycle together with connectivity to smart sensors. But PAT does not provide isolated measurements alone.…”

Section: Introductionmentioning

confidence: 99%

Current and future requirements to industrial analytical infrastructure—part 2: smart sensors

Eifert¹,

Eisen

Maiwald

et al. 2020

Anal Bioanal Chem

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Complex processes meet and need Industry 4.0 capabilities. Shorter product cycles, flexible production needs, and direct assessment of product quality attributes and raw material attributes call for an increased need of new process analytical technologies (PAT) concepts. While individual PAT tools may be available since decades, we need holistic concepts to fulfill above industrial needs. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (Part 1) and smart sensors (Part 2). Part 2 of this feature article series describes the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality. The smart sensor consists of (i) chemical and process information in the physical twin by smart field devices, by measuring multiple components, and is fully connected in the IIoT 4.0 environment. In addition, (ii) it includes process intelligence in the digital twin, as to being able to generate knowledge from multi-sensor and multi-dimensional data. The cyber-physical system (CPS) combines both elements mentioned above and allows the smart sensor to be self-calibrating and self-optimizing. It maintains its operation autonomously. Furthermore, it allows-as central PAT enabler-a flexible but also target-oriented predictive control strategy and efficient process development and can compensate variations of the process and raw material attributes. Future cyber-physical production systems-like smart sensors-consist of the fusion of two main pillars, the physical and the digital twins. We discuss the individual elements of both pillars, such as connectivity, and chemical analytics on the one hand as well as hybrid models and knowledge workflows on the other. Finally, we discuss its integration needs in a CPS in order to allow its versatile deployment in efficient process development and advanced optimum predictive process control.

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“…TD-NMR was also recently applied to the online analysis of several liquid materials during different processes, such as fatty acid mixing [15,16], starch gelatinization [17] and black liquor evaporation [18]. Moreover, there is a high demand on process analytical tools in various industrial areas nowadays, and novel sensors, developed on the basis of NMR technology, could be beneficial [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Real-time measurement system for determining metal concentrations in water-intensive processes

2020

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AbstractThe main purpose of this paper is to demonstrate the potential of time-domain nuclear magnetic resonance (TD-NMR) technology for monitoring the concentrations of metal ions in water-based solutions. The main focus of this work was paramagnetic ions, such as Mn2+, Cu2+, Fe3+, Fe2+, Zn2+ and Ni2+, which are often the principal metal components in mining waters. Laboratory samples of different concentrations of single metals and mixtures of them and samples of real mining water were used in the relaxation rate (R2) measurements. The measurements of single metal ions were used for the determination of the relaxivities of those ions. The concentrations of the ions in the mining water as a function of pH were also estimated by means of the X-ray fluorescence (XRF) method and ChemEQL software for calculating chemical speciation equilibria. Using these concentration values and the relaxivities of the metal ions, the total relaxation rate (R2) results were then calculated. Principally, the results of these three different determinations are in relatively good agreement. It can be concluded that TD-NMR has great potential for monitoring metal ion concentrations during water treatment.

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Current and future requirements to industrial analytical infrastructure—part 1: process analytical laboratories

Cited by 32 publications

References 4 publications

The Sample, the Spectra and the Maths—The Critical Pillars in the Development of Robust and Sound Applications of Vibrational Spectroscopy

The Sample, the Spectra and the Maths—The Critical Pillars in the Development of Robust and Sound Applications of Vibrational Spectroscopy

Current and future requirements to industrial analytical infrastructure—part 2: smart sensors

Real-time measurement system for determining metal concentrations in water-intensive processes

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