Process Design Research Articles

Optimization scheme design in production process based on multi-stage decision-making

This paper studies the control of defective rate in the electronic industry chain, designs a small sample binomial distribution sampling detection scheme to verify the supplier 's defective rate statement and optimize the detection cost. Based on the defective rate, the linear programming and dynamic programming / decision tree model are used to optimize the multi-stage production process, including parts inspection, finished product inspection and unqualified product treatment, so as to maximize the profit of the enterprise. A phased optimization strategy is proposed for complex multi-process situations. Finally, according to the sampling test results, the defect rate estimation is adjusted, the problem model is re-optimized, and the cost control reference scheme is provided.

Design and multiperformance evaluation of the ternary azeotrope separation process via extractive distillation based on different extractants

Resource utilization and sustainable wastewater treatment have received widespread attention because of their efficient use of energy. In this study, an ethanol (EtOH)/ethyl tert-butyl ether/water ternary azeotropic system was used to explore the separation efficiency of various extractants. The relative volatility, toxicity, and process modeling of extractants were analyzed to provide a theoretical basis and practical guidance for screening the optimal extractant among nine commonly used extractants. Extractive distillation (ED) was optimized for six processes with a focus on total energy consumption (TEC) and total annual cost (TAC). The ED-EtOH process was the most economical, whereas the extractive ED-DMSO process had the lowest TEC. After heat integration (HI) treatment, the TAC and TEC of each process were reduced, among which HI-ED-EtOH and HI-ED-glycerol (GLY) had the best and lowest economy, respectively. Although high-boiling point and high latent heat extractants (such as GLY and EtOH) increase the heat demand and operating costs, their high latent heat characteristics can effectively recycle heat energy during the HI process. The optimal balance between economy and energy consumption was determined through multi objective optimization considering the physical and chemical properties, environmental impact, and adaptability of extractants.

Control and Modelling of Laser Shock Peening without Coating (LSPwC) Texture of AISI 9310 Steel.

LSPwC is an important development of Laser shock peening (LSP) technology, and surface texturing is an effective method to improve tribological properties. The combination of these is expected to innovate a new surface texturing technology with a strengthing effect, but no one has attempted it. In this paper, a new LSPTwC technology combining them is innovatively proposed and validated on AISI 9310 steel, which is commonly used in helicopter transmission components for surface texturing. The LSPTwC surface was studied using an optical microscope, electron microscope, energy dispersive spectrometer, and so on. The results proved that LSPTwC is an effective texturing method of AISI 9310 steel, which modulates the texture and improves the properties, such as the microhardness increased by more than 10%. A model for calculating the texture and process parameters is also constructed on a statistical basis, and a modeling method for textured surfaces is proposed. It is verified that the calculation results and the constructed model are highly consistent with the test, with a diameter deviation <3% and depth deviation <4%. The above results can provide the experimental basis, process design method, and calculation model for single-point LSPwC texturing of AISI 9310 steel parts for helicopters, which have application value.

Hot Torsion Tests of AA6082 Alloy

Materials characterization and the knowledge of their elastic-plastic behavior are of fundamental importance for the design of industrial manufacturing processes. Nowadays, FEM simulation is the main tool used to optimize product quality and minimize scraps, and the numerical codes have evolved over the years to obtain accurate solutions with reduced computational times. Nevertheless, in order to perform reliable simulations, it is necessary to include accurate modeling of the material flow stress. Hot torsion is a powerful method for the characterization of the material flow stress because, tests can be carried out at constant speeds and temperatures, reaching large strain values, and thus getting over the limits of compression and tensile tests. In this paper the hot torsion characterization applied to AA6082 alloy is presented: tests were performed with equivalent strain rates of 0.01, 0.1, 1, and 10 s-1, in the temperature range from 440 to 550 °C (from 713.15 to 823.15 K). The results are presented in terms of equivalent stress vs equivalent strain. Finally, the material flow stress curve was predicted by the Hyperbolic sine model and Hensel-Spittel law, and the material parameters A, m1-9 are provided for the temperature expressed in °C and K.

Design and analysis of negative CO2 emission methanol synthesis process incorporating green hydrogen and blue hydrogen

Methanol (MeOH) production by integration of green and blue hydrogen is evaluated herein. From 2018 to 2023, methanol demand increased by 3.6 % due to its use in various chemical industries as an eco-friendly fuel and as a method of transporting hydrogen and capturing renewable CO2. Moreover, due to the continual decrease in the cost of renewable energy, research into the use of green hydrogen from electrolysis is being conducted. Most of this research has focused on producing methanol from the green hydrogen obtained from proton-exchange membrane (PEM) electrolysis along with CO2 emissions from power plants. The present study examines processes based on oxyfuel combustion with oxygen obtained from either the PEM or an air separation unit (ASU) to produce methanol. By using oxyfuel combustion, the carbon capture process (which accounts for 30–50 % of the blue hydrogen cost) and pure (>98.75 %) 7.45 tCO2/tH2 can be obtained by separating H2O from the flue gas. By using the PEM, green hydrogen can capture 0.35 tCO2/tMeOH of external CO2. Furthermore, a carbon techno-economic analysis (CTEA) and a sensitivity analysis are conducted to evaluate the sustainability and feasibility of the proposed processes. As a result, the levelized cost of methanol (LCOM) is $373.91/tMeOH for the Blue process and $428.78/tMeOH for the Blue + Green process, each of which is below the current market price of $500/tMeOH. If the PEM price continues to decrease, and the carbon credit increases by €300/tCO2, after 2030, the Blue + Green process will become more lucrative than the Blue-only process. Thus, by considering the continuous decrease in renewable energy prices, the production of methanol via a hybrid Blue + Green process is suitable for a sustainable future.

Temperature Cycling Induced Deracemization of p-Synephrine in the Presence of Degradation.

The acquisition of enantioenriched organic molecules is crucial in processes where the enantiomeric purity of active ingredients impacts efficacy and safety. Temperature cycling-induced deracemization (TCID) can achieve deracemization, but its effectiveness can be hindered by degradation reactions that influence the kinetics and the achievable enantioenrichment. This work characterizes the impact of degradation on the dynamic development of enantiomeric excess during the TCID process for the p-synephrine hydrochloride salt. The pilot study demonstrates that a maximum enantiomeric excess of 86% R-(-)-p-synephrine can be achieved at an intermediate batch time among all tested conditions. Degradation promoted the crystallization of a dimer with novel solid-state form, disynephrine ether dihydrochloride, which led to a substantial decrease in the slurry density of synephrine, potentially contributing to the observed decline in enantiomeric excess during the TCID process. Batch-to-batch variability in process dynamics and maximum attainable enantiomeric excess was observed, potentially attributable to the sensitivity of the process to uncontrolled initial conditions. These findings underscore the importance of accounting for degradation kinetics in the design and optimization of TCID processes for enantioenrichment.

Assessment of Nylon-6 Depolymerization for Circular Economy: Kinetic Modeling, Purification, Sustainable Process Design, and Industrial Practice

Assessment of Nylon-6 Depolymerization for Circular Economy: Kinetic Modeling, Purification, Sustainable Process Design, and Industrial Practice

Numerical Analysis in Double-Sided Polishing: Mechanism Exploration of Edge Roll-Off

Understanding the mechanism of stress concentration effects on the surface of semiconductor substrate materials—silicon wafers—in Double-Sided Polishing (DSP) is particularly important for improving polishing quality. In this study, a two-dimensional finite element model is established to study the effect of contact state and stress concentration during polishing on edge roll-off (ERO) and polishing rate uniformity. The variation in this contact state is influenced by changes in wafer thickness and the gap between it and the carrier. The model is validated by experiments and helps to further analyze and interpret the experimental results, identifying six stages of contact states during the polishing process. The research indicates that the phenomenon of stress concentration at the edge of a wafer is caused by the pads creating a large amount of compression at the edge of the wafer. Additionally, there appears to be a threshold value during the polishing process, below which the stress concentration on the wafer changes, thereby altering the magnitude of edge roll-off and, ultimately, affecting overall flatness. This study provides a basis for optimizing the process design.

Autoencoder-based inverse design and surrogate-based optimization of an integrated wet granulation manufacturing process

In pharmaceutical manufacturing, integrating model-based design and optimization can be beneficial for accelerating process development. This study explores the utilization of Machine Learning (ML) techniques as a surrogate model for the optimization of a three-unit wet-granulation based flowsheet model for solid dosage form manufacturing. First, a reduced representation of a wet granulation flowsheet model is developed, incorporating a granulation and milling process, along with a novel dissolution model that accounts for the effect of particle size, porosity, and microstructure on dissolution rate. Two optimization approaches are compared, including an autoencoder-based inverse design and a surrogate-based forward optimization. Both methods address the bi-objective problem of maximizing dissolution time and product yield by identifying the optimal granulation and mill process parameters. For this case study, both approaches were effective and incurred a similar computational cost, averaging under 4 s. However, the autoencoder approach offers an advantage through dimensionality reduction, a feature not available in surrogate-based optimization. Dimensional reduction is particularly beneficial for complex process designs with numerous inputs and outputs. The lower dimensional representation helps improve process understanding through enhanced visualization of the process design space and facilitates feasibility studies involving multiple constraints. The autoencoder-based inverse design introduced in this work showcases an implementation of AI and ML in pharmaceutical process development, demonstrating the potential to enhance process efficiency and product quality in complex manufacturing scenarios.

Targeting carbon-neutral waste reduction: Novel process design, modelling and optimization for converting medical waste into hydrogen

This study proposes a novel system designed to turn waste masks (WM) into hydrogen while aiming at carbon neutrality. The system utilizes plasma gasification to primarily convert WM into syngas, which is subsequently upgraded through water gas shift to enhance hydrogen fraction. To mitigate carbon emissions, carbon capture techniques including monoethanolamine-based carbon absorption and oxy-fuel combustion are incorporated into the system. A high-fidelity model of the designed process is developed in Aspen Plus. Machine learning-driven optimization is applied to identify the optimal operating conditions. Utilizing Gaussian process regression-based surrogate optimization, the system achieves around 0.5 kg CO2 eq/kg H2 of levelized emissions per unit hydrogen (LEH) in the reaction stage and the execution time required for optimization is only 4 s, outperforming detailed process models-based optimization. Energy assessment highlights plasma gasification and CO2 absorption as the primary sources of energy loss. Furthermore, life cycle analysis indicates that CO2 absorption is the primary contributor to carbon emissions, accounting for approximately 60% of the total emissions. With levelized emissions of 1.27 kg CO2 eq/kg WM and 5.18 CO2 eq/kg H2, the designed system demonstrates superiority over conventional medical waste treatment and hydrogen production methods.

Developing a novel anticipated inherent risk assessment approach applicable in early stages of process design

Inherently Safer Design (ISD), as one of the most fundamental approaches to process safety, focuses on the innate design features. Numerous tools have been developed to assess ISD and risk-based indices are one of the most elevated of them. Existing indices are limited in modelling consequences or are challenging to adapt in terms of probability. This study introduces the Anticipated Inherent Risk Index (AIRI), a robust tool for rapid risk assessment of the worst anticipated scenarios. It incorporates Furthest Effect Distance of the release from the largest connection, by software, and Representative Failure frequency, which is a relative dataset calculated from renown databases. This presents a relative risk map upon major consequences and their likelihood. AIRI applied to a PDH Fractionation Subunits shows that Heat Pump Compressor Suction Drum (AIRI≈3399) in PP Splitter Section, followed by Propylene Trim Condenser (AIRI≈1931) and PP Splitter Reboiler/Condenser (AIRI≈1798) are the equipment with the highest risk. AIRI is a competent tool for early high-level analysis of equipment risk, which gives useful indications on design and how to improve it. This tool also has the potential to be equipped with vaster frequency datasets and effects analysis and to be incorporated into other process safety studies.

A forming method of variable-diameter tubes straightforward from sheet metals

Variable-diameter metallic tubes are extensively used in many industrial applications. They are generally made of pre-formed raw tubes by using the existing processing methods, during which obvious non-uniformity in tube wall thickness inevitably occurs. In this work, a novel method is proposed to form variable-diameter tubes directly from sheet metals by means of the roll-stamp forming technique. A three-pass roll-stamp forming process and corresponding die blocks are designed and implemented to form a demonstrative conical tube. The finite element model of the roll-stamp forming process is established and forming quality is quantitatively evaluated. The initial blank configuration, which is the most important factor for process design, is determined by combining machine learning and multi-objective optimization. The forming experiment is performed, and the conical tube is successfully formed with no significant thinning/thickening of tube wall. The influences of forming direction and conical ratio on the forming process are numerically investigated. The proposed roll-stamp technique provides a novel and effective approach to manufacturing variable-diameter tubes.

High recovery design of reverse osmosis process with high permeate water quality and low wastewater discharge for ultra-pure water production

Ultra-pure water (UPW) for electronic industry is produced via many unit processes including reverse osmosis (RO), pretreatments, membrane degasifier, and ion exchange processes. Generally, 2-pass RO system is adopted in UPW production process to remove ionic and organic matters to meet water quality requirements of post-treatments. Since RO concentrate occupies most of wastewater discharged from UPW production process, high recovery design is beneficial to reduce wastewater discharge. According to the solution-diffusion model, permeate concentrations increase at higher feed concentrations, which may limit to increase RO recovery. Interestingly, the bench-scale 2-pass RO test using five commercial membrane modules revealed permeate concentrations were not affected by feed concentrations below a critical value (35 mg/L as NaCl in this work). This means the first-pass RO recovery can be increased without decreasing permeate water quality as far as second-pass RO feed concentrations are below the critical values. Various 2-pass UPW-RO system designs (250 mg/L as NaCl of feed concentration) were analyzed using an industrial RO system simulator to investigate the effect of the first- and second-pass recovery. The simulation works found that increasing the first- and second-pass recovery decreased wastewater discharge, energy consumption, and the number of membrane modules without degrading permeate water quality.

The Photoredox Paradox: Electron and Hole Upconversion as the Hidden Secrets of Photoredox Catalysis.

Although photoredox catalysis is complex from a mechanistic point of view, it is also often surprisingly efficient. In fact, the quantum efficiency of a puzzlingly large portion of photoredox reactions exceeds 100% (i.e., the measured quantum yields (QYs) are >1). Hence, these photoredox reactions can be more than perfect with respect to photon utilization. In several documented cases, a single absorbed photon can lead to the formation of >100 molecules of the product, behavior known to originate from chain processes. In this Perspective, we explore the underlying reasons for this efficiency, identify the nature of common catalytic chains, and highlight the differences between HAT and SET chains. Our goal is to show why chains are especially important in photoredox catalysis and where the thermodynamic driving force that sustains the SET catalytic cycles comes from. We demonstrate how the interplay of polar and radical processes can activate hidden catalytic pathways mediated by electron and hole transfer (i.e., electron and hole catalysis). Furthermore, we illustrate how the phenomenon of redox upconversion serves as a thermodynamic precondition for electron and hole catalysis. After discussing representative mechanistic puzzles, we analyze the most common bond forming steps, where redox upconversion frequently occurs (and issometimes unavoidable). In particular, we highlight the importance of 2-center-3-electron bonds as a recurring motif that allows a rational chemical approach to the design of redox upconversion processes.

The sigma factor σB is required for the development of the growth phase- and temperature-dependent increases in thermoresistance and membrane rigidity in Staphylococcus aureus

The aim of this study is to determine the role that σB factor plays in the development of growth phase- and temperature-dependent thermoresistance in Staphylococcus aureus cells and its possible relationship with membrane fluidity. Cells of S. aureus strain Newman and its isogenic ΔsigB mutant (strain IK184) were grown at different temperatures to exponential and stationary growth phases, and the relationship between σB activity (estimated by RT-qPCR), heat resistance, and membrane fluidity (fatty acid profiles and DPH fluorescence anisotropy) was assessed. σB was required for the development of the growth phase- and temperature-dependent increases in thermoresistance and membrane rigidity (up to 37 °C), although a direct correlation between σB activity and heat resistance or membrane fluidity in S. aureus could not be established. Results obtained also revealed the existence of σB-independent growth phase and temperature (>37 °C) heat adaptation mechanisms. Moreover, it was demonstrated that σB does not control the fatty acid synthesis in S. aureus. Results obtained in this work contribute to a deeper knowledge of S. aureus physiology and to the development and design of more effective processes used by the food industry for microbial inactivation.

Extractive distillation using salt-based deep eutectic solvent as entrainer for separating acetonitrile-water mixture

Salt-based deep eutectic solvents (DESs) have been proposed in this work for the separation of the azeotrope of acetonitrile and water (H2O). The vapor–liquid equilibrium experiments indicated that (ChCl:U:CaCl2)1:2:0.36 exhibits an higher selectivity among all of the entrainers investigated and eliminates the azeotropic point of acetonitrile and water mixture. Moreover, the calculated values by NRTL model coincide well with the experimental data for the systems (acetonitrile + H2O + (ChCl:U:CaCl2)1:2:0.36). Based on the thermodynamic study, the conceptual process design was established to evaluate the competitiveness of the suggested entrainers for the separation of acetonitrile and water. It was determined that the thermodynamic efficiency (η) in the extractive distillation (ED) process utilizing the new salt-based DESs entrainers increases 60.31 % compared with the benchmark entrainer ethylene glycol (EG). Conversely, the ED process using (ChCl:U:CaCl2)1:2:0.36) entrainer can reduce the total annual cost (TAC) by about 7.81 % and the CO2 emissions (ECO2) by 14.74 %. The ED process using (ChCl:U:CaCl2)1:2:0.36) as entrainer shows the high energy efficiency, low economy cost and low CO2 emissions with a great industrial application prospect when compared to the bench marked process.

The importance of both catalyst and process design in unlocking sustainable carbon feedstocks through syngas

As part of its move towards net zero, the chemical industry, over time, will transition away from fossil-based chemical feedstocks towards more sustainable, ‘green’ carbon—biomass, recycled waste and captured carbon dioxide. One gateway to transforming these feedstocks into the vital chemicals and fuels society relies on is via synthesis gas or ‘syngas’—a gaseous mixture of chemical building blocks (H 2 , CO and CO 2 ). While today the majority of syngas is produced via steam reforming of natural gas, commercially available technologies are enabling syngas production and transformation from sustainable feedstocks. The optimization of sustainable syngas technologies would not be possible without the integrated development of both catalyst and process technology and the associated skills in chemistry and chemical engineering. This paper covers three example technologies that are unlocking the role of syngas as a gateway to sustainable fuels and chemicals and highlights the innovative developments in catalyst and process design that have enabled their optimization and commercialization. This article is part of the discussion meeting issue ‘Green carbon for the chemical industry of the future’.

Evaluation of Different ZX Tensile Coupon Designs in Additive Manufacturing of Amorphous and Semi-Crystalline Polymer Composites

The layer-by-layer deposition of molten polymer filament in fused deposition modeling (FDM) has evolved as a disruptive technology for building complex parts. This technology has drawbacks such as the anisotropic property of the printed parts resulting in lower strength for parts printed in the vertical Z direction compared with the other two planes. In this manuscript, we attempt to address these challenges as well as the lack of standardization in sample preparation and mechanical testing of the printed parts. The paper focuses on process parameters and design optimization of the ZX build orientation. Type I tensile bars in ZX orientation were printed as per the ASTM D638 standard using two (2B) and four (4B) tensile bar designs. The proposed design reduces material loss and post-processing to extract the test coupons. Printing a type I tensile bar in the ZX orientation is more challenging than type IV and type V due to the increased length of the specimen and changes in additional heat buildup during layer-by-layer deposition. Three different polymer composite systems were studied: fast-crystallizing nanofiller-based high-temperature nylon (HTN), slow-crystallizing nanofiller-based polycyclohexylene diethylene terephthalate glycol-modified (PCTG), and amorphous carbon fiber-filled polyetherimide (PEI-CF). For all the polymer composite systems, the 2B showed the highest strength properties due to the shorter layer time aiding the diffusion in the interlayers. Further, rheological studies and SEM imaging were carried out to understand the influence of the two designs on fracture mechanics and interlayer bonding, providing valuable insights for the field of additive manufacturing and material science.

How Far Is the Nanocellulose Chip and Its Production in Reach? A Literature Survey.

The slowdown of Moore's Law necessitates an exploration of novel computing methodologies, new materials, and advantages in chip design. Thus, carbon-based materials have promise for more energy-efficient computing systems in the future. Moreover, sustainability emerges as a new concern for the semiconductor industry. The production and recycling processes associated with current chips present huge environmental challenges. Electronic waste is a major problem, and sustainable solutions in computing must be found. In this review, we examine an alternative chip design based on nanocellulose, which also features semiconductor properties and transistors. Our review highlights that nanocellulose (NC) is a versatile material and a high-potential composite, as it can be fabricated to gain suitable electronic and semiconducting properties. NC provides ideal support for ink-printed transistors and electronics, including green paper electronics. Here, we summarise various processing procedures for nanocellulose and describe the structure of exclusively nanocellulose-based transistors. Furthermore, we survey the recent scientific efforts in organic chip design and show how fully automated production of such a full NC chip could be achieved, including a Process Design Kit (PDK), expected variation models, and a standard cell library at the logic-gate level, where multiple transistors are connected to perform basic logic operations-for instance, the NOT-AND (NAND) gate. Taking all these attractive nanocellulose features into account, we envision how chips based on nanocellulose can be fabricated using Electronic Design Automation (EDA) tool chains.

Effective lateral dispersion of momentum, heat and mass in bubbling fluidized beds

The lateral dispersion of bed material in a bubbling fluidized bed is a key parameter in the prediction of the effective in-bed heat transfer and transport of heterogenous reactants, properties important for the successful design and scale-up of thermal and/or chemical processes. Computational fluid dynamics simulations offer means to investigate such beds in silico and derive effective parameters for reduced-order models. In this work, we use the Eulerian-Eulerian two-fluid model with the kinetic theory of granular flow to perform numerical simulations of solids mixing and heat transfer in bubbling fluidized beds. We extract the lateral solids dispersion coefficient using four different methods: by fitting the transient response of the bed to (1) an ideal heat or (2) mass transfer problem, (3) by extracting the time-averaged heat transfer behavior and (4) through a momentum transfer approach in an analogy with single-phase turbulence. The method (2) fitting against a mass transfer problem is found to produce robust results at a reasonable computational cost when assessed against experiments. Furthermore, the gas inlet boundary condition is shown to have a significant effect on the prediction, indicating a need to account for nozzle characteristics when simulating industrial cases.