Simulation Of Production Process Research Articles

Utilization of Advanced Computational Methods to Predict Spring-back of Aluminium Alloys in Automotive Industry

The automotive industry is one of the most dynamically developing segments of the industrial production worldwide. The introduction of still increasingly stringent emission limits for newly developed cars forces car producers to still reduce the fuel consumption of cars. One option is to use hybrid drive units in combination with a redesign of the automobile body while maintaining the highest possible level of vehicle safety. For these reasons, the automotive industry has been increasingly demanding to apply and process low density (lightweight) alloys, including aluminium-based alloys. These materials are subject to high demands both in terms of mechanical properties and technological workability in the mass production process. The utilization of mathematical modelling (numerical simulations) of production processes is now one of the standards in all phases of design and production the car-body and allows the implementation of variable designs in a relatively short time scale and the detection of potential production problems as well. In this paper, the influence of the kinematic hardening model on the accuracy of spring-back prediction is shown in comparison with the commonly used isotropic hardening model. For deformation analysis, a simple workpiece having ?U-shape? of EN AW 6111 material was used. Such aluminium alloys is used for production car-body panels in the automotive industry. Achieved accuracy of numerical simulation results is evaluated by the comparison shape obtained by numerical simulations and shape of experimentally bended workpiece.

A Novel Design of Methyl Methacrylate Synthesis Process with Low CO2 Emission

Methyl methacrylate (MMA) is an important raw material for synthesising polymethyl methacrylate, plastic modifier, and surface coating. In this paper, an optimum “energy saving and low emission” process is proposed for MMA production. MMA is synthesised from ethylene and synthetic gas generated from coal chemical looping gasification (CLG), which can largely reduce CO2 emission. Firstly, the reaction mechanism of coal CLG is investigated using molecular dynamics simulation. Secondly, to verify the feasibility of the process, the steady-state simulation of MMA production process is carried out by Aspen Plus. Finally, based on the steady-state simulation results, one control scheme is verified with Aspen Dynamics to strictly control the purity of MMA.

Design and Optimization of the Process of Preparing Biofuel Ethanol from Lignocellulose

Fossil resources are increasingly exhausted and energy problems are facing severe challenges. The synthesis of ethanol from abundant lignocellulose is conducive to alleviating energy shortage, reducing environmental pollution, and achieving sustainable development. In this paper, compared with the traditional process, the whole process simulation of lignocellulose to biofuel ethanol is established, and a deep-eutectic solvents (DES) pretreatment process for Lignocellulose is proposed. Firstly, to verify the feasibility of the process, the steady-state simulation of the biofuel ethanol production process is carried out using Aspen Plus. Secondly, based on the steady-state simulation, the process is optimised to obtain the optimal operating parameters. Finally, DES is used as an entrainer to increase the concentration of ethanol, and its mechanism is investigated by molecular dynamics simulation (MD). The simulation results show that the DES has good effect in pretreatment and extractive distillation. The final yield of ethanol is 16.8 kg/h and the purity is 99 %. The results of molecular dynamics simulation show that the interaction between DES and water is much larger than that between DES and ethanol. The results are consistent with the process simulation results.

Utilization of computer simulation for optimization of furniture production system

Computer simulation methods are currently used to simulate production processes and optimize production systems. Computer simulation is one of the most effective tools for implementation of Industry 4.0 principles in industrial practice. This research focused on the optimization of production processes in furniture production using simulation, which is an innovative method of production optimization for furniture manufacturers. The aim of this research was to improve the production system of Slovak furniture manufacturing enterprise by creating a discrete event simulation model of production based on the analysis of its current state. Improvement indicators are specific parameters of the production system, which primarily include material flow, productivity, and workload utilization. First, with the use of Tecnomatix Plant Simulation software and the collected real production data, the original production system processes were simulated and analyzed. Second, the incorporation of more powerful devices was proposed to improve the production line. Third, the proposed improvements were simulated and analyzed. The result of this research was a statistical comparison of the parameters of the current production line and the proposed production improvements.

A thermo-mechanical material model for rubber curing and tire manufacturing simulation

In this contribution, the phase change of unvulcanized to vulcanized rubber is described by a thermo-mechanical material model within the finite element method (FEM) framework. Before the vulcanization process (curing), rubber exhibits an elasto-visco-plastic behaviour with significant irreversible deformations without a distinct yield surface. After exposing rubber to high temperature, the molecular chains build-up crosslinks among each other and its mechanical behaviour changes to stiffer viscoelastic material. The proposed model assumes, that both phases are present during the vulcanization process. The ratio changes from the uncured phase at the beginning to the cured phase according to the current state of cure. A constitutive curing formulation is introduced into the model, to capture the shape change during the vulcanization and to ensure, that the second law of thermodynamics is fulfilled. A multiplicative split of the deformation gradient is assumed to describe incompressible material. Thermal expansion due to the change of temperature is taken into account in the volumetric part, as well as shrinkage during the vulcanization process. In the isochoric part, the phase change from elasto-visco-plastic to viscoelastic material is described by micro-macro transition based on the micro-sphere model. The consistent formulation of the material model and its tangent are important for a successful implementation into a three-dimensional finite strain FEM framework. The capabilities of the model are shown by the simulation of an axisymmetric tire production process starting at the green tire inserted into the heating press up to a post-cure inflation step.

Modelling and Simulation of Methanol and Biodiesel Production Processes Using Innovative Technologies

Modelling and Simulation of Methanol and Biodiesel Production Processes Using Innovative Technologies

Simulation of Bottom Phytocenosis in the Crimean Coastal Zone

Purpose. The work is aimed at simulating production processes in the bottom phytocenosis typical of the rocky soils in the Crimean coastal zone. The macroalgae uptake of the main nutrients (phosphates, ammonium and nitrates) and release of oxygen and dissolved compounds are planned to be estimated. Methods and Results. The study was based on the balance model of the macroalgae growth and interaction with the environment. The model empirical parameters were determined from the published data of the laboratory experiments. The bottom phytocenosis in the model was represented by seven algae species: Cystoseira barbata, Ulva lactuca, Ceramium tenuicorne, Cladophora glomerata, Polysiphonia nigrescens, Phyllophora truncata, Enteromorpha prolifera. The main simulation results were: annual estimates of the released and absorbed substances, seasonal dynamics of the macroalgae biomass and evaluation of the bottom phytocenosis response to the changing environmental conditions. The rate of the production processes in the model was influenced both by the external (water temperature, insolation and concentration of nutrients in water) and internal (intracellular quotas of nitrogen and phosphorus, and species-specific parameters determining efficiency of nutrient assimilation by the algae tissues) factors. According to the simulation results, the ratio of nitrogen to phosphorus in the algae tissues was significantly higher than that in the seawater and varied from 30 to 60 for different species depending on water temperature, light exposure and concentration of nutrients. Conclusions. During the periods of intensive macroalgae growth (from April to September), the rate of nitrogen and phosphorus uptake can increase by a factor of 1.5 in comparison with the winter period. Maximum contribution to water purification from the surplus nutrients was made by the green algae: Ulva lactuca, Cladophora glomerata and Enteromorpha prolifera. At that Cladophora glomerata has shown the best adaptive abilities (minimal decrease in the growth rate) under a sharp drop of nutrients concentration in water.

Data processing of robotic parameters in intelligent robotic systems

The scientific problem of developing the processing of technological data generated by the intelligent robotic systems (IRS) in the mechatronic robotic process is considered. It is shown that mechatronic robotic data is generated simultaneously in the real IRS and in the cloud-based IRS. In the real IRS, data is captured by a system of sensors built into the IRS process chamber. In the cloud-based IRS, mechatronic robotic data is generated by simulating production processes in a modelling tools (in the cloud) using the IRS digital twins. It is shown that the quality of mathematical data processing acceptable for implementation in mechatronic robotic industry is achieved using mathematical methods of regression analysis. Regression analysis allows you to detect the disorder of difficult to control production processes, accompanied by the formation of time series of mechatronic robotic data having a stochastic nature. Structural schemes of the mathematical processing of mechatronic robotic data in industrial IRS is described.

Virtual Sensor Development for Multioutput Nonlinear Processes Based on Bilinear Neighborhood Preserving Regression Model With Localized Construction

The traditional data-driven virtual sensors mainly define the outer shape of the data, but they cannot provide any insight into the micro perspective of manifold proximity indicating the local relationships among the data samples. In this article, a regression model with localized construction named bilinear neighborhood preserving regression (BNPR) model is proposed by synchronously exploring the local manifold geometry among both the process variables and primary variables and developing the regression relationship for the estimates of the primary variables. The model is constructed under multi-output to discover the inherent relationships among the primary variables instead of building independent models for each primary variable. The effectiveness of the proposed algorithm is demonstrated by case studies carried out on a simulated penicillin production process and a real-life semiconductor process.

Leveraging Category Theory in Model Based Enterprise

A mathematical framework based on category theory is proposed to formally describe and explore procedures of modeling engineering products and processes that comprise operation of a model-oriented enterprise. The framework is intended to provide interoperability across a variety of engineering modeling languages and tools, supplying them with a common abstract foundation capable to represent, generate, and verify diverse design and production knowledge. The framework is leveraged via algebraic representation of product configurations as diagrams in categories with models as objects and descriptions of actions involved into products assembly as morphisms. Relevance of the framework is justified by appealing to systems engineering standards such as IEC 81346. Category theoretical methods for solving direct assembly problems that consist in constructing a product model from a given configuration are presented. Specifically, solutions are obtained via the universal construction called a colimit of a diagram. Much attention is then paid to stating and solving inverse assembly problems that consist in recovery and subsequent optimization of the configuration from the product model and assembly actions. Inverse problem solving is in demand for generative design, viz. an emerging fully automatic product development and manufacturing technology. Example solutions to direct and inverse problems are described in categories that represent two major areas of model-based enterprise operation: solid body geometric modeling of mechanical products and discrete-event simulation of production processes.

Simulation of Bioreactors for PHB Production from Natural Gas

Recently, many economic studies of poly(3-hydroxybutyrate) PHB production on an industrial scale, and the impact of replacing petrochemical polymers by PHB were carried out, clearly indicating that the most crucial factors to reduce the cost of producing biopolymers are allotted to the application of microbial production strains capable of high productivity in inexpensive carbon sources, high cell density cultivation methods, cheap yet effective methods for the extraction of PHB and other polyhydroxyalkanoates (PHAs), and gene transfer from bacteria to plants. We present current strategies to reduce the production price of biological PHA. Because an important part of the PHA production cost is related to the cost of carbon source, the article focuses on the use of natural gas as an inexpensive and readily available C1-carbon source. Since the first and foremost point in PHA production is biomass growth, we discuss different types of bioreactors to be potentially used for efficient biomass production from natural gas, which facilitates the subsequent selection of the ideal bioreactor for PHA production from this substrate. Nowadays, process simulation software can be used as a powerful tool for analysis, optimization, design, and scale up of bioprocesses. Controlling the process design by in silico simulations instead of performing an excessive number of lab-scale experiments to optimize various factors to save in time, material and equipment. Simulation of PHA production processes to find the optimal conditions can play a decisive role in increasing the production efficiency. Computational fluid dynamics and mathematical modeling helps us to achieve a better understanding of the role of different nutrients, flow parameters of gaseous substrates, efficient feeding strategies, etc. This finding leads to higher productivity by prediction of parameters e.g. nutrient supply and biomass concentration time profile and their respective yields.

The optimal carbon and hydrogen balance for methanol production from coke oven gas and Linz-Donawitz gas: Process development and techno-economic analysis

This study addresses the simulation and techno-economic analysis of novel methanol production processes by the combined feeding of hydrogen-rich coke oven gas (COG) and carbon-rich Linz-Donawitz gas (LDG). The optimal operating scheme and conditions to ensure the most favorable carbon and hydrogen balance of the proposed processes, maximized methanol production and polygeneration of methanol, power, and heat, were determined through a rigorous process simulation with a sequential quadratic programming optimization. A techno-economic analysis revealed that two combined-feeding processes show an improved technical and economic performance compared to the conventional methanol production process involving separated feeding of COG and LDG. The primary energy efficiency and minimum methanol selling price of the proposed processes were 51% and 60%, and 265 and 370 USD/ton, respectively, which were greatly improved compared to the base process. In addition, the CO2 emissions of the two processes (0.41 and 1.03 kg of CO2 per kW) imply that adjusting the optimal carbon and hydrogen balance is an important strategy to produce economically viable and environmentally clean methanol from residue gases of the steel industry.

Consideration of digitalization for the purpose of resource efficiency in a learning factory

Product diversity is increasing as a result of changing consumer behavior and diversification in global markets. For manufacturing companies, this development means an increase in the complexity of the required production systems and all company processes involved. Digitalization can make a decisive contribution to mastering this complexity and also offers a number of approaches to conserve resources and avoid waste at all levels of the organization. Simulations in the product development can help to optimize the material usage. The simulation of logistics and production processes helps to avoid waste in the material flow. The increasing use of low-cost sensors enables comprehensive data to be obtained on material movements and energy consumption. These data can be evaluated via big data analyses in order to develop approaches for the control and regulation of material flows and energy consumption. The visualization of data in energy management systems brings transparency, which shows new approaches for optimization. In order to improve one’s own competitiveness through digitalization a strategic approach is required. Several models and tools are available for the development of a company-wide strategy for digitalization. The Lower Saxony Learning Factory for Resource Efficiency (“NiFaR“) has analyzed models and tools to use them for suitable applications in the production environment of the Factory. By using sensor technology and artificial intelligence and by visualizing the results, NiFaR enables its visitors to experience and comprehend the potential of digitalization for the purpose of resource efficiency. It also offers training on this topic for consultants and employees of companies, ranging from the presentation of different digitalization approaches to practical implementation examples.

Evaluation and Enhancement of Transfer line in Production Process by Simulation

Plant Simulation software enables the simulation and optimization of production systems and processes. Using Plant Simulation, you can optimize material flow, resource utilization and logistics for all levels of plant planning from global production facilities, through local plants, to specific lines. In times of increasing cost and time pressures in production, along with ongoing globalization, logistics has become a key factor in the success of a company. The need to deliver JIT (just-in-time)/JIS (just-in-sequence), introduce Kanban, plan and build new production lines and manage global production networks (to name a few) requires objective decision criteria to help management evaluate and compare alternative approaches. Plant Simulation helps create digital models of logistic systems (e.g., production) to explore the systems’ characteristics and to optimize their performance. The digital model enables users to run experiments and what-if scenarios without disturbing an existing production system or – when used in the planning process – long before the real system is installed. Extensive analysis tools, statistics and charts let users evaluate different manufacturing scenarios and make fast, reliable decisions in the early stages of production planning. Plant Simulation helps users to Detect and eliminate problems that otherwise would require cost-and time consuming correction measures during production ramp up Minimize the investment cost of production lines without jeopardizing required output, Optimize the performance of existing production systems by taking measures that have been verified in a simulation environment prior to implementation.

Virtual sensors of nonlinear industrial processes based on neighborhood preserving regression model

The micro perspective of manifold proximity would indicate local relationships with their unique spatial geometric distribution characteristics among the data samples, which are usually neglected by traditional data-driven virtual sensors. This would not guarantee a good prediction performance. In this paper, a regression model with localized construction named neighborhood preserving regression (NPR) model is proposed. It extends the unsupervised neighborhood preserving embedding (NPE) to the supervised form. The projection vector is learned from input process variables and the output quality variable, synchronously exploring the manifold structure of the input process variables for the dimension reduction and developing the regression relationship between the projected input process variables and the output quality variable. The model is developed as a novelly designed optimization whose analytical solution would be compactly and directly calculated without any iterative procedures. The effectiveness of the proposed algorithm is demonstrated by case studies carried out on a simulated penicillin production process.

Flowsheet simulation of solids processes: Current status and future trends

Complex manufacturing processes are nowadays applied for production of various solid products. It is very common that for production of particles with desired properties several transformation steps like drying, milling, classification, granulation, etc. should be involved. This leads to the process structures consisting of different apparatuses or transformation substeps connected with material and energy balances. Consequently, development of new processes or optimization of already existing, as well as an optimal control, is a very challenging task, which can be partially solved using numerical modelling.For the simulation of modern production processes, the flowsheet calculations can be effectively used. Starting from the 80 s a lot of work focused on the flowsheet simulation of liquid-vapor systems has been done and as result various well-established systems exist today. With respect to the solid processes the intensive research has been started much later. In this contribution we present our view about a current role of flowsheet simulation for modeling of particulate materials and specify the open fields which can be covered in future research.

Simulation of production processes with Plant Simulation

This article presents the modelling of interconnected companies’ logistic processes with Tecnomatix Plant Simulation by Siemens. It has two main parts. The first contains the details of recognition including simulation. The second part presents the modelling with Tecnomatix Plant Simulation. My publication is supported by the EFOP3.6.1-16-2016-00022 project. The project is co-financed by the European Union and the European Social Fund.

Simulation of production processes with Plant Simulation

This article presents the modelling of interconnected companies’ logistic processes with Tecnomatix Plant Simulation by Siemens. It has two main parts. The first contains the details of recognition including simulation. The second part presents the modelling with Tecnomatix Plant Simulation. My publication is supported by the EFOP3.6.1-16-2016-00022 project. The project is co-financed by the European Union and the European Social Fund.

The basic areas of research and actual developments of the rolling department of the Institute of Ferrous Metallurgy, Ukraine’ National Academy of sciences

In 1948 in the Institute of Ferrous Metallurgy, a department was created, the basic task of which was the perfection of equipment and technologies of rolling production. Basic research and development activity in the area of sheet and long products production, aimed at elaboration of scientific and technological fundamentals, creation of new and perfection of existing processes of continuous rolling, optimization of rolling processes and management the rolled products quality considered. The most important research and technical development of the department noted, including innovation technologies of rolled products production, expert computer systems for engineer calculations and optimization of the processes parameters, as well as systems of automatic process control. Among the basic areas of research and development achievements, the elaboration of computer simulation of hot-rolled and cold-rolled strip production processes, rebar, wire rod and profiles of high accuracy for machine-building highlighted, as well as predicting of rolled products quality indices, perfection of their production technology. The comprehensive systems elaborated and implemented at the ferrous metallurgy plants aimed at vibro-diagnostic and automatic control of speed of high-speed cold-rolling mills, automatic control of cold-rolled strip flatness, automatic alignment of plate heads, designing of rational configuration of strip mills rolls cooling collectors and prediction of working rolls temperature at their operation. In the area of long products production theoretical fundamental of the continuous long products rolling processes at using non-driven working stands and non-driven dividing facilities elaborated. Fundamental studies of regularity of temperature, deformation and energy-power parameters variation of high-speed continuous rolling process of wire rod at application of reducing-sizing blocks elaborated. The basic approaches to bands and precise profiles of small gauges by rolling-drawing method production efficiency elaborated theoretically and experimentally. A method of determination of rational structure schemes and production parameters of hot-rolled product production from continuously casted billets in the casting-rolling complexes elaborated.

Optimization of production processes when building a value flow map

The article aims to optimize value flows using the VSM map to increase the efficiency of an enterprise. The article shows that the VSM method is a key method of lean manufacturing. It has already gained popularity. Application of the method is relevant for industrial, transport, educational and many activities. Simulation of production processes reflected as flows for two different industrial activities. This approach allowed for the use of valuation methods to optimize production processes. The approach to assessing the effectiveness of the flow has been changed, and new assessment methods have been proposed.