Electrochemical analyzers incorporate voltammetric analysis (VA) to perform trace speciation of inorganic ions in a sample based on a current-voltage relationship. Along with VA, cyclic voltammetric stripping (CVS) and cyclic pulse voltammetric stripping (CPVS) can aid in quantifying organic additives to provide continuous and interference-free operation of plating baths. These analyzers use a multi-mode electrode (MME) or a rotating disk electrode (RDE) to perform VA or CVS/CPVS applications.
As Industry 4.0 concepts continue to be implemented, «Smart Factories» that rely heavily on data to be more efficient and adaptive are realized. Petabytes of data flood into the control rooms of Smart Factories. However, getting valuable data that can lead to actual process improvement can be challenging. Process Analytics 4.0 introduces new modernizations such as Process Analytical Technology (PAT) to provide high-quality data and guide critical business decisions.
Industry 4.0 and Process Analytics 4.0
Industry 4.0 (the Fourth Industrial Revolution) is the current automation and data collection movement in the manufacturing sector. The heart of Industry 4.0 focuses on the concepts of connectivity, automation, system integration, and big data, to name just a few.
By implementing Industry 4.0 solutions, manufacturers can increase their efficiency, productivity, and profitability while remaining competitive and improving the customer experience. In a study completed by McKinsey & Company, it was noted that across industries, a 15–30% improvement in labor productivity and a 10–30% increase in throughput could be observed if Industry 4.0 solutions are successfully implemented .
Process Analytics 4.0 is a term analogous to Industry 4.0, centering on the evolution of process analytics. Dhanuka P. Wasalathanthri first coined the term in the journal Biotechnology Progress . In the paper, Wasalathanthri defined Process Analytics 4.0 as including the «utility of process analytical technology (PAT), assay automation, data management, visualization, augmented reality (AR) and IoT.»
This article covers how to successfully implement a Process Analytics 4.0 solution, including choosing the right PAT, ensuring proper sample preconditioning, and acquiring reliable data.
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Choosing the right PAT
When evaluating Process Analytical Technology, the most crucial factor is whether the chosen solution is fit-for-purpose. Numerous process analyzer solutions can solve a single problem. However, understanding which technology is best utilized will provide results that will ensure all critical quality attributes (CQAs) can be monitored and controlled properly.
Compared to the other PAT solutions discussed in this article, pH sensors are the simplest to install, use, and maintain. Process pH sensors typically have a small overall footprint and provide more accurate results compared to pH measurements performed in a laboratory, since the measurement occurs at process temperatures. They are also low-maintenance PAT sensors, with calibration being the primary upkeep activity for operators.
Process pH sensors can be installed in almost every manufacturing plant location—from general-purpose areas to explosion-proof zones. While pH sensors can be helpful, their data can be limited since they only offer one measurement value: pH.
Wet chemical analyzers utilize analytical methodologies such as titration, dynamic standard addition, photometry (colorimetry), and ion chromatography to measure the analytes of interest. With these analysis techniques, automatically measuring multiple analytes using different methods allows operators to track various CQAs simultaneously with one instrument.
The most significant advantage of wet chemical analyzers is that they can be designed to use the same method as the laboratory, allowing for a direct comparison between lab and process results, thereby providing a consistent correlation with historical data.
Spectroscopic techniques, such as near-infrared (NIR) and Raman spectroscopy, provide operators with rapid and accurate information about solid, gaseous, or liquid samples without needing sample preparation or chemical reagents. With multiplexing (MUX) options, these analyzers can measure multiple sample points—even analyzing different CQAs at each sample location.
Chemometric model development can be accomplished on similar laboratory or process systems and then easily transferred to the analyzer without disturbing process measurements. While the analyzer is collecting data, internal standards and automated diagnostic functions are used to continuously monitor the analyzer performance, ensuring that the data can be collected continuously.
The final consideration in choosing the right PAT is taking into account the capabilities of the software integrated to control the process analyzer.
PAT software needs to provide data processing, integrity, and traceability while remaining user-friendly. Software for PAT also goes beyond typical laboratory software because it needs to be able to communicate with the distributed control system (DCS) or supervisory control and data acquisition (SCADA) system. By integrating into these systems, the process analyzer can communicate directly with manufacturing control room, providing data that can be immediately used to maintain process control.
Check out our on-demand webinar, blog post, and IMPACT software brochure below to learn more about these PAT solutions.
Webinar: Process Analytics 4.0: Creating Data You Can Use
Blog: Automation beyond the lab – Integrating the most precise lab pH measurements into production processes
Brochure: Intelligent Metrohm Process Analytics Control Technology «IMPACT» Software
One of the most common challenges with implementing PAT solutions, especially for wet chemical analysis, is consistently delivering a representative sample to the process analyzer. It is estimated that 80% of PAT complications are due to sampling issues . One way to mitigate this obstacle is to design a robust preconditioning system that is separate from the rest of the process.
The purpose of any sample preconditioning system is to provide safe and efficient sample handling, protect the instrumentation from damage, increase uptime, and provide seamless integration into the process. The most common issues a sample preconditioning system must address are pressure, solids, and temperature. In most cases, sample panels can be constructed to simultaneously manage multiple parameters. Sample panels can be designed to reduce sample pressure, guard against large particles entering the analyzer, and reduce pulsation from plant equipment that may cause unreliable sample flow. Eliminating these common issues can provide the process analyzer with consistent sample around the clock.
Suppose multiple parameters do not need to be adjusted to meet the PAT specification. In that case, single-function sample conditioning systems can be a great alternative to custom-designed sample panels. These single-function sample conditioning systems include blow-back filters, overflow vessels, or simple inline filtration mechanisms.
PAT software can also be used in conjunction with sample panels to operate valves, pumps, or other devices external to the process analyzer. The software can also collect data from flow meters, pressure devices, or temperature sensors to make further control or diagnostic decisions about the process. It is possible to use external devices to have the process analyzer intelligently determine when to sample, when to increase sample frequency, or even alert operators to problems upstream of the process analyzer. These abilities provide a complete end-to-end solution for PAT solutions.
To learn more about sample preconditioning, watch our on-demand webinar below and check out the different options offered on our website.
Webinar: Process Analytics 4.0: A Comprehensive Solution for Process Monitoring
Acquiring valuable and reliable data
Once the appropriate PAT solution has been chosen and any sample preconditioning risks have been minimized, it is time to acquire valuable and reliable data to optimize and maintain all CQAs.
One example of a successful Process Analytics 4.0 implementation is monitoring moisture in organic solvents, such as propylene oxide (PO), with NIR spectroscopy. If the moisture level in PO is too high, the activity of the catalysts used in the polymerization stage is significantly reduced, leading to a decreased polypropylene yield. Therefore, the measurement of moisture content in PO is critical for profitability.
Typically, the moisture content of any component is measured using Karl Fischer titration (KFT) in the laboratory. While this technique can provide sufficient data to monitor product specifications, it can be influenced by moisture from the ambient environment and by human error. Skilled chemists must perform the measurement multiple times daily, providing results to keep the manufacturing process running smoothly. With inline NIR spectroscopy, the moisture content of incoming PO can be measured within a minute, and safety issues are reduced by making grab sampling of this volatile toxic compound a less frequent task.
Quantitative NIR spectroscopy is dependent on the development of a robust prediction model. To develop such a NIR model, laboratory data is collected using KFT on samples covering the analysis range. Each result is correlated to a NIR spectrum of the same sample.
After developing the prediction model, moisture in PO could be quantified from 11–120 mg/L (ppm) with reduced waste costs and real-time analysis around the clock versus hourly KFT analysis. During routine analysis, the process analyzer software provides immediate data processing for fast result collection and out-of-specification warnings, allowing manufacturers to make proactive process decisions and increase the final product quality.
To learn more about this case study, check out the on-demand webinar link below.
Webinar: Process Analytics 4.0: A Turnkey Solution for Moisture Analysis
Implementing a Process Analytics 4.0 solution can sometimes seem like a daunting task. Still, success can be easily obtained if the right PAT solution and software are chosen, and a robust sample management strategy is used. With these solutions, manufacturing plants can enable autonomous decision-making procedures, monitor processes in real-time, and safeguard product quality, thereby instituting a Smart(er) Factory with Process Analytics 4.0.
Metrohm is one of the world’s most trusted manufacturers of high-precision instruments for chemical analysis. With 45+ years of experience, Metrohm Process Analytics utilizes the same Metrohm laboratory technology, providing dedicated custom process solutions and partnering with manufacturers to help improve their bottom line.
 Gregolinska, E.; Khanam, R.; Lefort, F.; et al. Capturing the true value of Industry 4.0. Industry 4.0: Digital transformation in manufacturing | McKinsey. https://www.mckinsey.com/capabilities/operations/our-insights/capturing-the-true-value-of-industry-four-point-zero (accessed 2023-02-23).
 Wasalathanthri, D. P.; Shah, R.; Ding, J.; et al. Process Analytics 4.0: A Paradigm Shift in Rapid Analytics for Biologics Development. Biotechnology Progress 2021, 37 (4), e3177. DOI:10.1002/btpr.3177
 Phillips, S. 3 Rules for Analyzer Accuracy. Swagelok Fluid System Blog. https://www.swagelok.com/en/blog/sampling-system-issues-that-can-cost-you (accessed 2023-02-27).