Simulation Of Process Research Articles

Improving processing efficiency through workflow process reengineering, simulation and value stream mapping: a case study of business process reengineering

PurposeBusiness Process Reengineering (BPR) eliminates non-value-added (NVA) and essential non-value-added (ENVA) waste through radical process redesign to improve organizational operations. Comprehensive research integrating BPR tools is needed to understand their benefits for manufacturing firms. This research presents an integrated BPR-simulation framework tailored to the manufacturing sector to maximize process improvements and operational excellence.Design/methodology/approachThe BPR design methodology adopts a systematic, multi-stage approach. The first phase involves identifying a specific improvement process aligned with BPR's core objectives. This phase analyses and redesigns workflows to optimize task sequences, roles, and stakeholder interactions while eliminating redundancies and inefficiencies via Workflow Process Reengineering. Visual process mapping tools, including VSM and simulation, pinpoint areas of waste, delay, and potential enhancement. The second phase follows the workflow analysis and aims to improve efficiency and effectiveness by redefining roles, rearranging tasks, and integrating automation and technology solutions. The redesigned process undergoes evaluation against key performance indicators to ensure measurable improvements are achieved. The final phase validates the proposed changes through simulation models, assesses the impact on key performance metrics, and establishes the necessary infrastructure for successful implementation. The proposed model is empirically validated through a case study of a leading apparel company in Vietnam, confirming its effectiveness.FindingsThe findings reveal that NVA activities are being eliminated, and ENVA activities in key departments are significantly reduced. This yielded a substantial improvement, reducing 25 out of 186 combined ENVA and NVA operations in the sewing facility, involving a decrease of 15 ENVA operations and the removal of 10 NVA operations. Consequently, this led to an 8.5% reduction in the proportion of ENVA operations, accompanied by a complete 100% elimination of NVA activities.Research limitations/implicationsThe single case study limits generalizability; thus, expanded implementation across diverse manufacturing sub-sectors is required to establish validity and broader applicability of the integrated framework.Originality/valueThe experimental results highlight the proposed model's effectiveness in optimizing resource utilization and its practical implementation potential. This structured BPR methodology enables organizations to validate, evaluate, and establish proposed process changes to enhance operational performance and productivity.

Simulation of non‐Newtonian biopolymer extrusion and fall in the centrifugal microencapsulation process

AbstractWe present high‐fidelity numerical simulations of the centrifugal microencapsulation process, that is of interest for biomedical applications as cell therapy. We provide first a comprehensive rheological characterization of high‐molecular‐weight calcium alginate, a commonly used material in microencapsulation. Building upon this, we employ a fluid model that accurately replicates the relevant non‐Newtonian properties of the fluid. This model is applied to numerical simulations of the first three stages of the centrifugal microencapsulation process: capillary flow, ejection from the capillary, and fall through the air. The results are successfully compared with experiments. Furthermore, this model, which can be adapted to various centrifugal microencapsulation devices, effectively elucidates the physical factors contributing to different capsule shapes that can be achieved at the end of the process. This breakthrough opens the door to precise control of capsule shapes and production rates.

AscentAM: A Software Tool for the Thermo-Mechanical Process Simulation of Form Deviations and Residual Stresses in Powder Bed Fusion of Metals Using a Laser Beam

Due to the tool-less fabrication of parts and the high degree of geometric design freedom, additive manufacturing is experiencing increasing relevance for various industrial applications. In particular, the powder bed fusion of metals using a laser beam (PBF-LB/M) process allows for the metal-based manufacturing of complex parts with high mechanical properties. However, residual stresses form during PBF-LB/M due to high thermal gradients and a non-uniform cooling. These lead to a distortion of the parts, which reduces the dimensional accuracy and increases the amount of post-processing necessary to meet the defined requirements. To predict the resulting residual stress state and distortion prior to the actual PBF-LB/M process, this paper presents the finite-element-based simulation tool AscentAM with its core module and several sub-modules. The tool is based on open-source programs and utilizes a sequentially coupled thermo-mechanical simulation, in which the significant influences of the manufacturing process are considered by their physical relations. The simulation entirely emulates the PBF-LB/M process chain including the heat treatment. In addition, algorithms for the part pre-deformation and the export of a machine-specific file format were implemented. The simulation results were verified, and an experimental validation was performed for two benchmark geometries with regard to their distortion. The application of the optimization sub-module significantly minimized the form deviation from the nominal geometry. A high level of accuracy was observed for the prediction of the distortion at different manufacturing states. The process simulation provides an important contribution to the first-time-right manufacturing of parts fabricated by the PBF-LB/M process.

Study on Rapid Simulation of the Pre-Cooling Process of a Large LNG Storage Tank with the Consideration of Digital Twin Requirements

The pre-cooling of a large LNG storage tank involves complex phenomena such as heat transfer, low-temperature flow, gas displacement, and vaporization. The whole pre-cooling process could take up to 50 h. For large-scale, full-capacity storage tanks, it is particularly important to accurately control the pre-cooling temperature. Digital twin technology can characterize and predict the full life cycle parameters from the beginning of pre-cooling development to the end and even the appearance of damage in real time. The construction of a digital twin platform requires a large number of data samples in order to predict the operating state of the device. Therefore, a simulation method with high computational efficiency for the pre-cooling process of LNG tanks is of great importance. In this paper, the mixture model and discrete phase model (DPM) are applied to simulate the pre-cooling process of a large LNG full-capacity tank. Following Euler–Lagrange, the DPM greatly simplifies the solution process. Compared with the experimental results, the maximum error of the DPM simulation results is less than 11%. Such a highly efficient simulation method for the large LNG full-capacity storage tank can make it possible to build the digital twin platform that needs hundreds of data model samples.

Injection Moulded Part Analysis by Alignment of Simulated and Referent Part Geometry

Warpage of the injection moulded parts is one of the most common defects after demoulding, which is intensively present in thin-walled moulded parts or parts with non-uniform wall thickness. The level of the warpage can be reduced by optimizing the mould tempering system in the phase of mould design, by optimizing the injection moulding parameters and recently by optimizing the shape of the mould cavity elements geometry – so-called inverse contouring. Computer simulation of injection moulding process can show the level of moulded part warpage after ejection from the mould, but it will not allow detailed measuring of critical moulded part measures deviations. Detailed analysis and prediction of the critical moulded part dimensions can be performed by aligning of the deformed moulded part design obtained with computer simulation, with moulded part reference CAD geometry. This paper shows the main steps and an example of the geometry aligning process for a specific thermoplastic part.

Numerical investigation gaseous ammonia basic jet and mixing characteristics in the constant volume vessel

Ammonia is considered a promising zero-carbon fuel under the dual-carbon targets. Systematically understanding ammonia's basic jet and mixing characteristics can promote its practical application in the engine field. Thus, a three-dimensional computational fluid dynamics (CFD) model of constant volume vessel (CVV) is established in this paper, and the forecasting abilities of the Large Eddy Simulation (LES) and Reynolds-Averaged Navier-Stokes (RANS) models for the gaseous ammonia jet process are compared based on the experimental data. Then, the ammonia jet development rule and mixing characteristics under different ambient temperatures, ambient pressures, and fuel temperatures are investigated. The variation laws of key data such as penetration distance, jet area, ammonia mass concentration distribution, equivalence ratio, and turbulent kinetic energy are obtained and analyzed. The results show that during the injection process, the airflow on the left and right sides of the jet rotates in opposite directions. A higher temperature and lower pressure within the CVV lead to a larger flammable range for ammonia jets. Moreover, the distribution of ammonia mass concentration on the radial plane shows a dynamic development law with time, meaning that it first increases to a maximum value, then gradually decreases, and finally remains stable. The farther the radial plane is from the nozzle outlet position, the lower the ammonia mass concentration. In addition, the ammonia jet's turbulent kinetic energy has a large core region and symmetrical distribution along the central axis. At the beginning of the injection, the core length is small, gradually increasing with time and finally stabilizing.

Benchmarking various nonadiabatic semiclassical mapping dynamics methods with tensor-train thermo-field dynamics.

Accurate quantum dynamics simulations of nonadiabatic processes are important for studies of electron transfer, energy transfer, and photochemical reactions in complex systems. In this comparative study, we benchmark various approximate nonadiabatic dynamics methods with mapping variables against numerically exact calculations based on the tensor-train (TT) representation of high-dimensional arrays, including TT-KSL for zero-temperature dynamics and TT-thermofield dynamics for finite-temperature dynamics. The approximate nonadiabatic dynamics methods investigated include mixed quantum-classical Ehrenfest mean-field and fewest-switches surface hopping, linearized semiclassical mapping dynamics, symmetrized quasiclassical dynamics, the spin-mapping method, and extended classical mapping models. Different model systems were evaluated, including the spin-boson model for nonadiabatic dynamics in the condensed phase, the linear vibronic coupling model for electronic transition through conical intersections, the photoisomerization model of retinal, and Tully's one-dimensional scattering models. Our calculations show that the optimal choice of approximate dynamical method is system-specific, and the accuracy is sensitively dependent on the zero-point-energy parameter and the initial sampling strategy for the mapping variables.

Coupled modeling and simulation of tank self-pressurization and thermal stratification

Numerical analysis of thermo-fluid dynamics for cryogenic propellant storage primarily consists of nodal and computational fluid dynamics (CFD) modeling approaches. While nodal approaches prioritize faster computation over fidelity, CFD approaches promise accuracy and fidelity at the expense of significant computational resources. This paper presents an efficient coupling methodology developed to facilitate the simulation of a long-term self-pressurization process of a cryogenic propellant tank as well as associated thermal stratification phenomenon under both normal and reduced gravity conditions. Key highlight of the methodology is the development of a coupling scheme based on a domain decomposition approach that separates the tank into two computational regions at the liquid-vapor interface. SINDA/FLUINT, the nodal code, is utilized to simulate the liquid region, while ANSYS Fluent, the CFD code, handles the vapor region. A data exchange algorithm was developed to compute required boundary conditions for each region using the local thermodynamic properties of assumed infinitely thin interface. The coupling between the nodal and CFD codes was demonstrated by simulating a self-pressurization process in a small size tank using hydrogen as the working fluid. A sensitivity study on the grid sizing and coupling time step was conducted to determine appropriate spatial and ensure a divergent-free explicit data exchange time step size. Using the coupling approach, two numerical case studies were performed to study tank self-pressurization by considering two initial hydrogen fill levels. The effectiveness and efficiency of the coupling methodology was assessed by comparing the temperature and pressure evolution results of the coupled simulation with those obtained solely from the CFD simulation. Results showed that the coupling scheme and data exchange algorithm were successfully implemented, and the coupled simulation agreed well with the CFD simulations. In addition, a stratification number was used to characterize the transient dynamic development of the thermal stratification. Lastly, the computational costs associated with both approaches were compared. Significant reductions in simulation time were achieved for both cases.

Numerical simulation of high-frequency induction welding in longitudinal welded tubes

In the present paper the high-frequency induction welding process is studied numerically. The mathematical model comprises a harmonic vector potential formulation of the Maxwell equations and a quasi-static, convection dominated heat equation coupled through the Joule heat term and nonlinear constitutive relations. Its main novelties are a new analytic approach which permits to compute a spatially varying feed velocity depending on the angle of the Vee-opening and additional spring-back effects. Moreover, a numerical stabilization approach for the finite element discretization allows to consider realistic weld-line speeds and thus a fairly comprehensive three-dimensional simulation of the tube welding process.

Three-Dimensional Modeling of Polygonal Ridges in Salt Playas.

In this work, we investigate the formation of the curious polygonal salt ridges that tessellate salt playas worldwide using suitable three-dimensional modeling and simulation of the dynamical processes that are responsible for their formation. We employ the principles of fracture mechanics under cyclic wetting and drying, fluid and mass transport in fracture channels, and processes of crystallization and self-organization to finally replicate the almost Voronoidal pattern of salt ridge mosaics observed in playas. The model is generic and applicable to playas having different salt compositions, as the effect of the salt diffusion coefficient and critical salinity for crystallization are factored in. The final pattern of polygonal salt ridges obtained by simulation visually resembles the geometry of the salt ridges reported in the literature. A single equation describing the time of first crystallization of salt in terms of evaporation suction pressure P, diffusion coefficient D of salt, and relative salinity Δc with respect to critical salinity at saturation, has been proposed. The saturation of crystal growth rate is shown to be a dynamic equilibrium between advection and diffusion processes. We show that the stable polygonal geometry of the salt playas is an effort toward the total minimization of system energy.

Metrics for software process simulation modeling

Metrics for software process simulation modeling

Microstructure Prediction from Smooth Particle Hydrodynamics Process Simulations of Additive Friction Stir Deposition

Microstructure Prediction from Smooth Particle Hydrodynamics Process Simulations of Additive Friction Stir Deposition

Simulation of Gas Sweetening Process using Extended NRTL and Stages Efficiency as Modeling Approach

Gas sweetening is a process to remove CO2 and H2S from natural gas. The current established technology is by using Amine contactor where the solvent used is in form of Amine solution. To simulate the effect of different solvent, electrolyte-NRTL is used to model the equilibrium, and mass transfer-kinetic is used to model the rate-based processes. This modeling approach is rather complex and available only in commercial and proprietary process simulation software. Therefore we propose an alternative modeling approach where we use extended NRTL and stage efficiency to model the acid gas absorption processes. We find that this approach is quite good to describe CO2 absorption, yet unsuccessful to calculate the H2S absorption. Inadequate vapor liquid equilibrium parameter regression for H2S, specifically at low partial pressure might cause the problem. However the stage efficiency approach shows good result where it is comparable to rate-based model and corresponds to current understanding of physico-chemical phenomenon of acid gas absorption.

High-quality utilization of raw coke oven gas for hydrogen production based on CO2 adsorption-enhanced reforming

To realize the high-quality utilization of raw coke oven gas (RCOG), the adsorption-enhanced steam reforming process was purposed for hydrogen production, coupled with the sensible heat recovery and the conversion of the high-energy components (such as tar). For this process, the hydrogen production performance and energy utilization efficiency were focused via reforming experiment and process simulation. Using the prepared bifunctional catalyst (Ni/Ce–CaO–Ca12Al14O33), the enhanced reforming experiment was conducted based on orthogonal design and Taguchi method. Compared to S/C ratio (the mole ratio of steam to carbon in the simulated RCOG) and WHSV (weight hourly space velocity), reforming temperature shows a higher sensitivity to hydrogen production. At 800 °C, the produced H2 amount can achieve 3.86 times of that in the initial RCOG and the H2 concentration in the produced gas can reach 88.38 %, when the S/C ratio was 15 and the WHSV was 0.0847 h−1. Based on the established process model, the energy consumption of RCOG enhanced reforming system was discussed. Compared to traditional hydrogen production technologies, this novel process exhibits a lower energy consumption, just about 62.5 MJ/kg H2, and also shows a higher energy conversion efficiency.

Process simulation of laser shock-based disassembly of adhesively bonded composite/metallic structural parts: a numerical upscaling

ABSTRACT In previous works, both experimental and numerical investigations have shown the potential of the laser shock technique for disassembling adhesively bonded composite/metal coupons. This study extends this concept to upscale the method, focusing on the full disassembly of a foreign object damage (FOD) panel designed to replicate an aircraft engine fan blade. Utilizing LS-Dyna explicit FE software, the numerical simulation incorporates various material models: a progressive damage model for the 3D CFRP substrate, Johnson–Cook plasticity model combined with Grüneisen equation of state for the titanium layer, and a cohesive zone model with a bilinear traction separation law for the adhesive layer. Investigating the FOD panel’s inclined geometry, a preliminary analysis examines the impact of inclination angles on shock wave propagation and back face velocity, revealing minimal alterations. Initial simulations are conducted to determine double pulse delay times and evaluate spot location effects. Automation of the multi-step process simulation is achieved through a Python script. After approximately 30 shots, complete disassembly of the FOD strip is achieved, with observed damage primarily limited to matrix cracking in the composite substrate. Numerical findings support the efficacy of the double-shot laser shock method for disassembling adhesively bonded metallic/CFRP components, contingent upon appropriate experimental arrangements.

Process simulation of laser shock-based disassembly of adhesively bonded composite/metallic structural parts: a numerical upscaling

ABSTRACT In previous works, both experimental and numerical investigations have shown the potential of the laser shock technique for disassembling adhesively bonded composite/metal coupons. This study extends this concept to upscale the method, focusing on the full disassembly of a foreign object damage (FOD) panel designed to replicate an aircraft engine fan blade. Utilizing LS-Dyna explicit FE software, the numerical simulation incorporates various material models: a progressive damage model for the 3D CFRP substrate, Johnson–Cook plasticity model combined with Grüneisen equation of state for the titanium layer, and a cohesive zone model with a bilinear traction separation law for the adhesive layer. Investigating the FOD panel’s inclined geometry, a preliminary analysis examines the impact of inclination angles on shock wave propagation and back face velocity, revealing minimal alterations. Initial simulations are conducted to determine double pulse delay times and evaluate spot location effects. Automation of the multi-step process simulation is achieved through a Python script. After approximately 30 shots, complete disassembly of the FOD strip is achieved, with observed damage primarily limited to matrix cracking in the composite substrate. Numerical findings support the efficacy of the double-shot laser shock method for disassembling adhesively bonded metallic/CFRP components, contingent upon appropriate experimental arrangements.

Machine learning for high-precision simulation of dissolved organic matter in sewer: Overcoming data restrictions with generative adversarial networks

Understanding the transformation process of dissolved organic matter (DOM) in the sewer is imperative for comprehending material circulation and energy flow within the sewer. The machine learning (ML) model provides a feasible way to comprehend and simulate the DOM transformation process in the sewer. In contrast, the model accuracy is limited by data restriction. In this study, a novel framework by integrating generative adversarial network algorithm-machine learning models (GAN-ML) was established to overcome the drawbacks caused by the data restriction in the simulation of the DOM transformation process, and humification index (HIX) was selected as the output variable to evaluate the model performance. Results indicate that the GAN algorithm's virtual dataset could generally enhance the simulation performance of regression models, deep learning models, and ensemble models for the DOM transformation process. The highest prediction accuracy on HIX (R2 of 0.5389 and RMSE of 0.0273) was achieved by the adaptive boosting model which belongs to ensemble models trained by the virtual dataset of 1000 samples. Interpretability analysis revealed that dissolved oxygen (DO) and pH emerge as critical factors warranting attention for the future development of management strategies to regulate the DOM transformation process in sewers. The integrated framework proposed a potential approach for the comprehensive understanding and high-precision simulation of the DOM transformation process, paving the way for advancing sewer management strategy under data restriction.

Effect of flip-chip ball grid array structure on capillary underfill flow

During the capillary underfill (CUF) process in flip-chip packaging, issues like incomplete filling, voids, wire sweeping, and overflow can impact product reliability and the relatively long filling time required. Therefore, finding ways to improve filling efficiency is a critical challenge. Conducting experiments to address these issues can be costly. As a result, the industry often relies on simulation software to simulate the actual manufacturing process, predict potential problems, compare results with experimental data, and analyze ways to improve the process. This approach helps enhance the package yield and further improves production efficiency.This study investigates the capillary underfill (CUF) process through simulation. Firstly, the viscosity and reaction kinetics of the underfill material are measured to establish the necessary data for the simulation. Then, Moldex3D, a mold flow simulation software, is used to create the model, generate the mesh, and perform the process simulation analysis. The effects of material properties and process parameters on the capillary underfill process are considered. The simulation results are compared with experimental data to validate the feasibility of the simulation. Subsequently, different flip-chip package structures and CUF process parameters are analyzed through simulation to explore the impact of these parameters on the flow pattern and filling efficiency of the adhesive material during the filling process.According to the simulation results, the filling speed is faster when the bump pitch and gap height are larger. However, the required filling time still has a considerable relationship with the volume of the filling region. Dispensing from the side with lower bump density can shorten the filling time when the bump distribution is uneven.

Thermoviscoelastic modelling of highly reactive thermoset resins for liquid moulding applications

This paper presents a methodology for developing thermo-mechanical properties model for highly reactive resins and its use for Resin Transfer Moulding process (RTM) modelling and prediction of residual stresses. Cure Hardening Instantaneously Linear Elastic (CHILE), and Thermoviscoelastic (TVE) models, were implemented to analyze the mechanical behaviour of the resin. Simulation of the RTM process was developed and applied to a representative curved plate geometry. An integral approach was considered where the degree of cure gradient, generated during the filling stage due to the reactivity of the resin, was implemented as initial condition of the stress-deformation process simulation. The validation process included fabricating experimental parts with the representative geometry. The degree of cure variation of highly reactive thermosets during injection caused a significant effect on the final shape of the parts. These effects were captured by the simulations, where the TVE model showed a more accurate prediction of the part distortion.

Mechanical characterization of Xenopus laevis oocytes using atomic force microscopy

Mechanical properties are essential for the biological activities of cells, and they have been shown to be affected by diseases. Therefore, accurate mechanical characterization is important for studying the cell lifecycle, cell-cell interactions, and disease diagnosis. While the cytoskeleton and actin cortex are typically the primary structural stiffness contributors in most live cells, oocytes possess an additional extracellular layer known as the vitelline membrane (VM), or envelope, which can significantly impact their overall mechanical properties. In this study, we utilized nanoindentation via an atomic force microscope to measure the Young's modulus of Xenopus laevis oocytes at different force setpoints and explored the influence of the VM by conducting measurements on oocytes with the membrane removed. The findings revealed that the removal of VM led to a significant decrease in the apparent Young's modulus of the oocytes, highlighting the pivotal role of the VM as the main structural component responsible for the oocyte's shape and stiffness. Furthermore, the mechanical behavior of VM was investigated through finite element (FE) simulations of the nanoindentation process. FE simulations with the VM Young's modulus in the range 20–60 MPa resulted in force-displacement curves that closely resemble experimental in terms of shape and maximum force for a given indentation depth.