Changes In Process Parameters Research Articles

Electrokinetic remediation of cadmium-contaminated soil using polarity reversal method: Optimization analysis and mechanism exploration

Electrokinetic remediation (EKR) has been applied for in-situ removal of Cd from contaminated soil, and the EKR enhanced with polarity reversal has achieved a higher Cd removal efficiency. However, the migration and accumulation mechanisms of Cd in the EKR process have not been investigated. In this paper, the cross-impacts of the voltage gradient, citric acid concentration in the electrolyte, and polarity reversal frequency on the removal efficiency by EKR of Cd and the optimization conditions were investigated. The migration and accumulation mechanisms of Cd were explored by analyzing the changes in electrokinetic process parameters, experimental phenomena, and X-ray diffraction (XRD) analysis. The results showed that the maximum removal efficiency of Cd reached 82.26%. The optimal conditions were determined by fitting the RSM model using the BBD design. In the EKR experiment with polarity reversal, Cd accumulated mainly in the middle part of the soil, attributed to the formation of chemical precipitation focusing area caused by soil pH transition, ion-induced potential gradient well trapping effect (IIPGWTE), or soil compaction induced by water loss. In conclusion, the various parameters have cross-impacts on the EKR of Cd-contaminated soil, and efficient in-situ removal of Cd from the contaminated soil can be achieved by adjusting the parameter conditions.

Study on Laser Transmission Welding Technology of TC4 Titanium Alloy and High-Borosilicate Glass.

As the demand for high-performance dissimilar material joining continues to increase in fields such as aerospace, biomedical engineering, and electronics, the welding technology of dissimilar materials has become a focus of research. However, due to the differences in material properties, particularly in the welding between metals and non-metals, numerous challenges arise. The formation and quality of the weld seam are strongly influenced by laser process parameters. In this study, successful welding of high-borosilicate glass to a TC4 titanium alloy, which was treated with high-temperature oxidation, was achieved using a millisecond pulsed laser. A series of process parameter comparison experiments were designed, and the laser welding behavior of the titanium alloy and glass under different process parameters was investigated using scanning electron microscopy (SEM) and a universal testing machine as the primary analysis and testing equipment. The results revealed that changes in process parameters significantly affect the energy input and accumulation during the welding process. The maximum joint strength of 60.67 N was obtained at a laser power of 180 W, a welding speed of 3 mm/s, a defocus distance of 0 mm, and a frequency of 10 Hz. Under the action of the laser, the two materials mixed and penetrated into the molten pool, thus achieving a connection. A phase, Ti5Si3, was detected at the fracture site, indicating that both mechanical bonding and chemical bonding reactions occurred between the high-borosilicate glass and the TC4 titanium alloy during the laser welding process.

Investigating amplitude amplification in optimization-based control for a continuous stirred tank reactor

Quantum computers, which utilize quantum states called ‘qubits’ to process information, are becoming of increased interest in a variety of fields because they have the potential to outperform classical computers in certain situations. However, many challenges and hurdles remain, including the development of quantum algorithms that offer a speedup and can be applied to practical problems (some quantum algorithms that offer a speedup may only be applicable in specific and sometimes contrived circumstances). Our previous works have studied the use of quantum computers and quantum algorithms for process control applications. Our prior work evaluated the use of a gate-based quantum amplitude amplification algorithm when applied to a model predictive control optimization problem, specifically evaluating a linear systems example. The results suggested that the algorithm may be suited for the specific linear problem studied (meaning that there is a high probability of obtaining the desired result when measuring the quantum state after the algorithm has been applied). However, the results cannot be generalized to a wider class of systems or to systems containing nonlinearities. To begin to gain an understanding of how the amplitude amplification algorithm might be generalized, this work evaluates the use of the algorithm for the optimization-based control of a nonlinear dynamic system (specifically, a continuous stirred tank reactor). We seek to understand aspects of the problem, such as the development of a solution space, the effects of changing process and control parameters, and the operation of the amplitude amplification algorithm itself. The results demonstrate the challenges that still exist, and demonstrate a method involving inverse sampling transformations to potentially aid in addressing these issues.

Study on the automatic control method for evaporation treatment of wet flue gas desulfurization wastewater in power plants

ABSTRACT DRFNN is used to predict the evaporation state of wastewater, and incremental PID algorithm is combined to adjust the control quantity. By real-time monitoring the state and parameter changes of wastewater evaporation treatment process, online adjusting and optimizing the parameters of DRFNN and incremental PID, the automatic control of desulfurization wastewater evaporation treatment is completed. The experimental results show that this method can achieve more accurate and reliable automatic control, short control time, strong ability to deal with emergencies, and can converge to stability in a short time. This method can effectively reduce the number of early alarms and failures of the system and save maintenance costs. The IAE values of chloride ion (Cl) and mercury (Hg) in this method are 0.3558 and 0.3872, respectively, which proves that the difference between the actual output and the expected output of this method is very small, which proves that the system in this paper has high accuracy.

Transformer and cross-attention-based multi-sensor in-situ monitoring of molten pool stability and part quality in laser powder bed fusion

The fluctuations in process parameters, as a random phenomenon in the laser powder bed fusion (LPBF) process, is occasional. These subtle variations can lead to defects such as porosity if not monitored and corrected promptly. Therefore, monitoring the stability of the molten pool and small changes in process parameters is significant. For process monitoring, the commonly used Transformer architectures have demonstrated remarkable performance in single-sensor signal processing. However, as the core component of the Transformer, the self-attention mechanism has limitations in data fusion of multi-sensor signals. To this end, a novel Transformer-based deep learning method associated with the cross-attention mechanism (Trans-Cross) is proposed. Trans-Cross leverages the collected photodiode and acoustic signals to monitor the fluctuation of process parameters as well as the quality of parts. Specifically, the cross-attention mechanism is introduced to enhance representative feature extraction from photodiode and acoustic signals, exploiting their complementary information. To better characterize the raw signals, an improved adaptive variational mode decomposition (VMD) algorithm is proposed for data preprocessing. The proposed Trans-Cross achieves impressive prediction accuracies of 97.41 % for identifying the fluctuations in the process parameters and 99.73 % for part quality classification. Trans-Cross exhibits superior performance and strong robustness when dealing with constraints such as limited input signal length and training data ratio. These results validate the feasibility of the proposed method in accurately identifying the fluctuations in process parameters as well as the part quality. This work provided data guidance to enhance the stability of the LPBF process.

RSM-BASED STATISTICAL APPROACH TO ENHANCE THE COMPRESSIVE PERFORMANCE OF ABS P400 PARTS FABRICATED VIA FDM TECHNOLOGY

This research investigates the performance of ABS P400 parts under compressive loading. These ABS P400 parts are fabricated by fused deposition modeling (FDM) process using omnidirectional printing. The effects of three critical parameters, raster angle (A), air gap (B), and raster width (C), each at three different levels, were analyzed on three different performance measures, i.e. total deformation up to failure ([Formula: see text]) measured in %, maximum energy ([Formula: see text]) in MJ/m3 and break energy ([Formula: see text]) in MJ/m3. Results of experimentations were analyzed using analysis of variance (ANOVA), perturbation curve and 3D surface plots. The research established the anisotropic nature, durability and less brittleness of the FDM fabricated ABSP400 part, which leads to lower strength and also influence the energy absorbing behavior while deformation under compression. Complex relationships were exhibited between the chosen parameters and studied measures. It was also observed that [Formula: see text] is noticeable due to less brittleness of ABS P400 however, [Formula: see text] and [Formula: see text] vary in a contradictory fashion with changes in process parameters. The models were validated using normality plots. Multi-objective optimization was done using the desirability approach to determine the optimal combination of FDM process parameters for optimum responses. The desirability result showed that the optimized input parameter is [Formula: see text][Formula: see text]mm, and [Formula: see text][Formula: see text]mm which yield maximized optimum responses as [Formula: see text]%, [Formula: see text][Formula: see text]MJ/m3, and [Formula: see text][Formula: see text]MJ/m3. The work not only reflects the effect of three FDM parameters on the total deformation up to failure ([Formula: see text] in %) but, in addition, energy absorption behavior of FDM parts under compression is also investigated. The study on the behavior of energy at ultimate stress or ultimate load and breaking stress or breaking load were rarely investigated in earlier research which reflects the novelty of our research.

Exploration of TiMn/Ti anode for optimizing the structure and performance of electrolytic manganese dioxide

With the deepening application of manganese based cathode materials in new energy vehicle power batteries and wind solar energy storage batteries, diversified application scenarios also demand higher and more diverse performance of manganese based cathodes. This work adopts a new type of TiMn/Ti anode to replace traditional Ti anode preparing electrolytic manganese dioxide (EMD), to meet the requirements of manganese based batteries. Results show that the electrolysis process based on TiMn/Ti anode successfully achieves controllable adjustment of EMD structure by changing process parameters. Besides, the relationship between EMD structure and battery performance was studied. Meanwhile, density functional theory (DFT) calculation reveals that the existence of Mn (III) in EMD is the key to prepare a optimized non-stoichiometry Li1+yMn2-yO4. This work improves the performance of the cathodes of manganese based batteries by optimizing the quality of raw materials, providing a new perspective for the development of high-quality manganese based batteries.

Stability analysis of rolling mill system for flexible rolling process based on maximum Lyapunov exponent

Flexible rolling technology is the current development trend of strip production industry. However, due to the simultaneous change of mechanical, process and strip specification parameters in the flexible rolling process, the motion state of the system is difficult to analyze and stability control is hard to achieve. In this paper, the active motion characteristics of rolls in flexible rolling technology are considered, and the dynamic rolling process model is established to reflect the influence mechanism of process and specification parameters on the dynamic rolling force. The dynamic model of a 4-high rolling mill was developed and the structure-process-strip coupling strategy was applied to couple the models. The Runge-Kutta method was applied to solve the dynamic equation to obtain the maximum Lyapunov exponential spectrum for a single parameter variation. It is noteworthy that the two-parameter dynamics method was adopted to solve the dynamics on the two-parameter plane considering the nature of simultaneous variation of the system parameters, which solves the limitations of the traditional analytical method and is suitable for the application of the flexible rolling system. The results suggest that the parameters influence the motion state in the form of coupling, the influence pattern of each parameter on the stability is clarified, the evolution of the stable domain under the effect of parameter coupling is revealed, and the parameter matching strategy is determined. The results will provide a solution for the system parameter setting of flexible rolling technology and a theoretical reference for enhancing the stability of the rolling mill.

An automated approach for carbon integration in industrial park

Industrial park is a hub for various industrial activities. Industrial emissions are one of the main sources of carbon emissions. The reduction of carbon emissions is crucial to achieve carbon neutrality for industrial parks. This paper presents an automated approach to maximize the utilization of CO2 among different plants in industrial parks through carbon allocation network. The minimum target of external fresh CO2 is determined based on automated composite table algorithm (ACTA), which is then materialized with the detailed design of carbon allocation network. A case study with four scenarios were analyzed to systematically guide the carbon reduction process towards its carbon neutrality target. Direct utilization scenario refers to CO2 utilization between sources and sinks in the parks without any purification scheme. Sink manipulation and source reduction scenarios indicate that process parameter changes, equipment modifications and other measures in the sinks or sources lead to the reduction of CO2 demands or supplies. In the purification scenario, CO2 is purified to different concentrations to maximize its allocations among different plants. A case study based on chemical industrial park in Fuyang, China is presented to illustrate the approach. Four factories (coal-fired power, cement, ammonia, ethanol) were identified as carbon sources, while three others (urea, methanol, dimethyl ether) as carbon sinks. By implementing sink manipulation and source reduction, the fresh CO2 resources and CO2 emissions are effectively reduced to 205.25 t/h and 149.61 t/h, respectively. The result for purification scenario indicates that CO2 emissions can be decreased from 317.33 t/h to 105.72 t/h, with an overall reduction of 66.68 %, while the fresh carbon requirement is reduced from 357.41 t/h to 161.34 t/h. This work provides a useful tool for the utilization of excess CO2 within an industrial park.

Influence of dual axial magnetic field and welding parameters on weld characteristics in GTAW process

A methodology has been proposed that is capable of altering arc shape as per the requirement using an external magnetic field. Eight magnetic configurations were explored, out of which the N-S-S-N configuration yielded a wider bead width and lower penetration without any change in process parameters, which is more suitable for cladding and hard-facing applications. The central composite design technique has optimized the process parameters to achieve the maximum cladding width. Further, the effect of the selected configuration on the characteristics of claddings in terms of bonding strength, microhardness, and metallurgical properties have been investigated at optimal parameters. This investigation selected the SA 516 grade 70 as a substrate and SS 308 L as a cladding material. It was observed that bead width increases with increased excitation current and decreased travel speed. The maximum bead width (10.89 mm) was achieved at a 1.8 A excitation current and 1 mm/sec travel speed. The experiment has been conducted on the optimized value of process parameters to validate the developed model. A comparative study between magnetically controlled (MC-GTAW) and conventional GTAW processes. The result revealed that the MC-GTAW process has wider bead width (9.95 mm) and higher average hardness (391.45 HV), which is 67% and 15% more than that of the conventional GTAW process, respectively. The microstructure analysis has revealed that the MC-GTAW process yielded more granular bainite and refined grains. The claddings were subjected to a side bend test, which showed a good bonding strength between the substrate and the deposited metal.

Production of 5-fluorouracil-loaded PLGA nanoparticles with toroidal microfluidic system and optimization of process variables by design of experiments

In recent decades, microfluidics has presented new opportunities for the production of nanoparticles (NPs). However, to achieve rapid clinical translation, the production of PLGA NPs in a single microfluidic channel for both the pharmaceutical research and industry without the need for scaling is still limited. The aim of this study was to accomplish the production of reproducible and stable 5-FU loaded Poly(lactic-co-glycolic acid) (PLGA) NPs, using an innovative toroidal microfluidic system, for cancer therapy. The toroidal microfluidic system enabled the production of spherical NPs ranging from 100 to 150 nm by adjusting both the TFR within the range of 5–15 mL/min and FRR between 1:3 and 1:7. A systematic assessment of critical process variables (total flow rate; TFR, flow rate ratio; FRR) for the production of PLGA NPs was conducted using Design of Experiment (DoE). The NPs, which exhibit a uniform size distribution, remained stable even after centrifugation and storage for 3 months at 4 °C. The encapsulation efficiency of drug and the concentration of NPs were not affected by changing process parameters. The effective 5-FU encapsulation into NPs resulted in a controlled in vitro drug release. Due to the controlled release profile of the 5-FU loaded PLGA NPs, the formulation was a promising candidate for mitigating the toxic side effects of free 5-FU and improving cancer treatment. In conclusion, toroidal microfluidic system enables high-volume production of stable PLGA NPs, both with and without 5-FU.

Investigating process parameters to enhance (hemi)cellulolytic enzymes activity produced by Trichoderma reesei RUT-C30 using deoiled oil palm mesocarp fiber in solid-state fermentation

This study investigates the synthesis of (hemi)cellulolytic enzymes, including endoglucanase (CMCase), xylanase, and β-glucosidase, employing Trichoderma reesei RUT-C30 and deoiled oil palm mesocarp fiber (OPMF) through solid-state fermentation (SSF). The objective was to determine the optimal process conditions for achieving high enzyme activities through a one-factor-at-a-time approach. The study primarily focused on the impact of the solid-to-liquid ratio, incubation period, initial pH, and temperature on enzyme activity. The effects of OPMF pretreatment, particularly deoiling and fortification, were explored. This approach significantly improved enzyme activity levels compared to the initial conditions, with CMCase increasing by 111.6 %, xylanase by 665.2 %, and β-Glucosidase by 1678.1 %. Xylanase and β-glucosidase activities, peaking at 1346.75 and 9.89 IU per gram dry substrate (GDS), respectively, under optimized conditions (1:4 ratio, pH 7.5, 20 °C, 9-day incubation). With lower moisture levels, CMCase reached its maximum activity of 227.84 IU/GDS. The study highlights how important it is for agro-industrial byproducts to support environmentally sustainable practices in the palm oil industry. It also emphasizes how differently each enzyme reacts to changes in process parameters.

In-situ monitoring of the small changes in process parameters with multi-sensor fusion during LPBF

Abstract The small changes in process parameters have significant influences on the stability of laser powder bed fusion (LPBF). Therefore, monitoring the small changes in process parameters is particularly important. This paper proposed a machine learning (ML)-based multi-sensor fusion approach to monitor the LPBF processing state by combining photodiode, acoustic, and visual signals. In order to extract the motion features of the melt pool more accurately and describe its transient changes, an ellipse adjustment algorithm is proposed to segment the melt pool images, eliminating the interference of spatters. The motion features combined with preprocessed acoustic signals and photodiode signals to identify melting states during small changes in process parameters. The proposed ML-based multi-sensor fusion approach achieves impressive prediction accuracies of 99.9% for identifying the fluctuations in the process parameters. The results demonstrate that the proposed method can accurately identify small changes in process parameters, which is of great significance for improving the process stability and providing reliable guidance in subsequent work.

Efficient and distribution-free charts for monitoring the process location for individual observations

Sudden and sequential variations are crucial in industrial and production processes. To track these consistent changes in process parameters, effective charting methods are needed. The generally weighted moving average (GWMA) chart outperforms the exponentially weighted moving average (EWMA) chart in detecting small changes under various design parameters. However, its application relies on process distribution normality assumptions. This study presents new distribution-free GWMA control charts for individual measurements when the central limit theorem doesn't apply under simple random sampling. The charts' robustness and performance are evaluated under symmetric, skewed, and contaminated process environments, using run length properties, relative mean index (RMI), and extra quadratic loss (EQL) for overall assessment. The proposed chart outperforms existing charts in detecting specific and over-the-range shifts with appropriate design parameter choices. It's been applied to an electronics dataset where voltage on constant capacitance serves as a key quality characteristic, validating the theoretical findings.

Mechanical Properties of Ti Grade 2 Manufactured Using Laser Beam Powder Bed Fusion (PBF-LB) with Checkerboard Laser Scanning and In Situ Oxygen Strengthening

Additive manufacturing (AM) technologies have advanced from rapid prototyping to becoming viable manufacturing solutions, offering users both design flexibility and mechanical properties that meet ISO/ASTM standards. Powder bed fusion using a laser beam (PBF-LB), a popular additive manufacturing process (aka 3D printing), is used for the cost-effective production of high-quality products for the medical, aviation, and automotive industries. Despite the growing variety of metallic powder materials available for the PBF-LB process, there is still a need for new materials and procedures to optimize the processing parameters before implementing them into the production stage. In this study, we explored the use of a checkerboard scanning strategy to create samples of various sizes (ranging from 130 mm3 to 8000 mm3 using parameters developed for a small 125 mm3 piece). During the PBF-LB process, all samples were fabricated using Ti grade 2 and were in situ alloyed with a precisely controlled amount of oxygen (0.1–0.4% vol.) to enhance their mechanical properties using a solid solution strengthening mechanism. The samples were fabricated in three sets: I. Different sizes and orientations, II. Different scanning strategies, and III. Rods for high-cycle fatigue (HCF). For the tensile tests, micro samples were cut using WEDM, while for the HCF tests, samples were machined to eliminate the influence of surface roughness on their mechanical performance. The amount of oxygen in the fabricated samples was at least 50% higher than in raw Ti grade 2 powder. The O2-enriched Ti produced in the PBF-LB process exhibited a tensile strength ranging from 399 ± 25 MPa to 752 ± 14 MPa, with outcomes varying based on the size of the object and the laser scanning strategy employed. The fatigue strength of PBF-LB fabricated Ti was 386 MPa, whereas the reference Ti grade 2 rod samples exhibited a fatigue strength of 312 MPa. Our study revealed that PBF-LB parameters optimized for small samples could be adapted to fabricate larger samples using checkerboard (“island”) scanning strategies. However, some additional process parameter changes are needed to reduce porosity.

A Gaussian Process-Based extended Goldak heat source model for finite element simulation of laser powder bed fusion additive manufacturing process

Laser powder bed fusion (L-PBF) additive manufacturing (AM) is a key enabling technology to manufacture highly complex and integrated metallic structures. In L-PBF AM process, the melting of the metal powders and the layers underneath can be governed by either “conduction mode” or “keyhole mode”, with the keyhole mode reportedly leading to porosity and decreased strength and ductility by many studies. In part scale simulations, finite element (FE) model is often used to study the temperature distribution during printing and to predict the residual stress, where a volumetric heat flux with a Gaussian or a double ellipsoidal (Goldak) distribution is often applied as the laser heat source. However, the above heat source models can only capture the melt pool shape in the conduction mode, and fail to capture the transition to keyhole melting mode when the process parameters change. To overcome this inaccuracy, an extended Goldak heat source model is proposed by introducing a laser penetration term as a function of laser parameters obtained from a Gaussian-Process (GP) model. The model is validated by “2D pad” AlSi10Mg L-PBF experiments under a wide range of laser power, scan speed, and laser focus offset, and the results show the model successfully captures the measured melt pool shape in all conditions.

CMP characteristics of IGZO thin film with a variety of process parameters

Recently, amorphous indium gallium zinc oxide (a-IGZO) has been studied in the field of 3D transistors as a channel material for high mobility, good uniformity, and low leakage current performance. The CMP process needs to be applied to fully remove surface IGZO in a multilayer film stack structure and achieve the purpose of planarization. As we all know, the CMP characteristics of the desired removal rate with stability and within-wafer non-uniformity (WIWNU%) play an important role in the CMP process. In this paper, the variation of the removal rate and the non-uniformity for IGZO thin film were studied with various process parameters (such as polishing time, slurry flow rate, slurry dilution, head pressure, head and table speed). The results mean that the removal rate and the non-uniformity of IGZO thin film can be tuned by changing process parameters, which can enhance the confidence about the feasibility of IGZO-CMP in the application of advanced technology.

Implementation of inverse method for identification of process parameters in a laser heating process

Changes in process parameters can alter the temperature data of a solid body during the laser heating process. This paper proposes an inverse method to determine the laser heating parameters, namely, sheet width, sheet thickness, laser power, and scan speed of the work specimen for the given temperature response which is assigned by the user. The method uses an analytical tool on moving heat source as a forward model capable of real-time temperature prediction of the sheet under the laser heating process. The effectiveness of the present forward model that incorporated the temperature-dependent material properties is tested by experimental findings performed on Al 6061-T6 sheets. Next, an iterative search process based on heuristic method is carried out for satisfying a prescribed temperature response by the optimization of unknown parameters. To illustrate the implementation and assess the practicality of the inverse method, two examples based on laser heating applications are used. The method proposed herein recover the unknowns for the prescribed temperature response after a few iterations, provides an efficient way to optimize the laser heating process. Additionally, the effect of measurement error on the findings of the inverse problem is addressed.

Tackling P3HT:Y‐Series Miscibility Through Advanced Processing for Tunable Aggregation

AbstractPolymer and small molecule blend thin films are of strong interest for organic electronics and particularly organic solar cells. The high miscibility in blends of ordinary P3HT and state‐of‐the‐art Y‐series non‐fullerene acceptors (NFAs) suppresses phase separation and aggregation challenging successful charge separation and transport. In a recent work, current‐induced doping (CID) is introduced, a method to precisely control the aggregation of Poly(3‐hexylthiophene) (P3HT) in solution. The highly ordered pre‐aggregation in solution is used here to control the P3HT aggregation in neat films and blends with Y12 (BTP‐4F‐12). This results in a 25‐fold increase in hole mobility in P3HT organic field‐effect transistor (OFET) devices and tunability of the P3HT aggregate quality in the presence of Y12 over large ranges. At the same time, particularly the Y12 long‐range ordering is heavily suppressed by increasing P3HT aggregation. However, solvent vapor annealing (SVA) leads to an extraordinarily high Y12 ordering, changes in the crystal orientation of Y12, and a further improvement of P3HT aggregation. A broad range of different degrees of aggregation of both materials can therefore be obtained in the final thin films solely by changing processing parameters without changing the composition of the material system.

Influence of the Parameters of an Agricultural Biogas Plant on the Amount of Power Generated

Energy from biogas is widely available, inexpensive, and often contributes to waste management, making it one of the most promising renewable energy sources. The main factors influencing this process’ efficiency include the substrates’ chemical composition, temperature, and digester load. This paper presents the possibilities offered by a biogas plant built at a farm specialising in dairy cows. The dependence of the power generated in the micro biogas plant on its technical parameters was analysed in detail. Studies carried out by the authors in an agricultural microgas plant (with an electrical output of 40 kW) have shown that they are designed to maintain continuous energy production, despite changing process parameters such as digester mass level, biogas height, temperature or slurry flow into the digester. However, from the point of view of the amount of electricity generated, changes would have to be made to the design of the biogas plant. Firstly, a more powerful generator would have to be installed to cover the electricity requirements of the equipment installed in the biogas plant so that power close to the rated capacity of the biogas plant is still sent to the grid. Secondly, replacing the two existing agitators of the digestion mass (9 kW each) with more agitators of lower power (e.g., four agitators of 4.5 kW each) would be necessary. These should be programmed so that one of the agitators operates at any given time (the operating time of a given agitator should depend on the composition of the digestate).