Process modeling for simulation: observations and open issues

The use of design process models is of great importance for developing better products. Indeed, it is one of the factors that may differentiate the best companies from the rest. However, their adoption in companies is declining. Usefulness and usability issues may be responsible for process models not to meet the needs of its users. The goal of this research is to provide deeper understanding of the users' needs of design process models. Three main perspectives are provided: (1) why organizations use process models, (2) who are the users of process models, and (3) how the context of use of process models is. The research methodology adopted was the Design Research Methodology (DRM). Three stages were performed: (i) Research Clarification, (ii) Descriptive Study I, and (iii) Prescriptive Study. In the first stage, an initial literature review was carried out to collect evidences of why researching process models and their users' needs is relevant for the design theory. During the second stage (Descriptive Study I), literature was reviewed to identify the purposes of use of design process models and its potential users; a focusgroup section with 24 subject matter experts was carried out to evaluate these purposes and identify process model users; and, lastly, a case study was perfomed to investigate the context of use of design process models in one organization and to portray the profile of the core users. Finally, the third stage (Prescriptive Study) aimed to uncover directions for organizations develop user-centered design process models. Four main results were achieved through this research. The first result is a deep understanding of three types of application of the design process models: (a) develop the design activity, (b) manage the design project, and (c) improve the design process. The purposes for these aplications were investigated and their level of importance were revealed. In addition, it was mapped the core users of process models for the three applications. The second result is the definition of the context of use of the models.Three dimensions of the context were depicted: the product, the design process, and the organizational structure. The third result is the set of users profiles. Empathy Maps were elaborated to represent the profiles of product engineers, project managers, and technical leaders. The last result consists in recommendations regarding the content provided to users and the process models system design. Finally, industrial practitioners will benefit from this research once it was provided evidences that the activity development application type is not properly considered in organization and that important users' needs are not getting proper attention in the current models. Therefore, they will be able to make use of the recommendations outlined here.

Proactive prevention and fighting fire at industrial facilities, often located in urbanized clusters, should include the use of modern methods for modeling danger zones that appear during the spread of the harmful combustion products of various chemicals. Simulation modeling is a method that allows predicting the parameters of a danger zone, taking into account a number of technological, landscape, and natural-climatic factors that have a certain variability. The purpose of this research is to develop a mathematical simulation model of the formation process of a danger zone during an emergency at an industrial facility, including an explosion of a container with chemicals and fire, with the spread of an aerosol and smoke cloud near residential areas. The subject of this study was the development of a simulation model of a danger zone of combustion gases and its graphical interpretation as a starting point for timely decision making on evacuation by an official. The mathematical model of the process of danger zone formation during an explosion and fire at an industrial facility presented in this article is based on the creation of a GSL library from data on the mass of explosion and combustion products, verification using the Wald test, and the use of algorithms for calculating the starting and ending points of the danger zone for various factor values’ variables, constructing ellipses of the boundaries of the distribution of pollution spots. The developed model makes it possible to calculate the linear dimensions and area of the danger zone under optimistic and pessimistic scenarios, constructing a graphical diagram of the zones of toxic doses from the source of explosion and combustion. The results obtained from the modeling can serve as the basis for making quick decisions about evacuating residents from nearby areas.

Background and Purpose: Business process simulation (BPS) model is based on real-life data form sources like databases, observations and interviews. It acts as “as-is” business scenario can used for reengineering. The main challenge is to gather relevant data and to develop simulation model. Research aims to elaborate BPS model and to systematically assess how close to reality it is. Design/Methodology/Approach: The research has been performed in Polish telecommunications company. Authors investigate technical process of expanding cellular network. After elaborating “as-is” model, authors use ADONIS simulation tool to run a series simulations and confront simulation results with actual historical events. After this, assessment whether computer simulation model can precisely map real-life business process - and consequently act as credible basis for process improvement - is made. Results: The simulation model has been constructed with data from the WfMS database, observations, staff knowledge and their experience. Fully equipped simulation model is found to allow reconstructing the historical execution of business activity with low margin for error. Some limitation were identified and discussed. Conclusion: BPS is not a popular approach for process reengineering and improvement yet. Data collection issues for BPS that require adopting process mining techniques and additional information sources are among the reasons for that. In our study, computer simulation outputs are compatible with historical events. Hence the model reflects the business reality and can be taken as a reference model while redesigning the process.

Fused deposition modeling (FDM) offers many advantages over conventional manufacturing methods, but it is limited by the number of materials available. Extending FDM technology to semicrystalline polymers has been challenging due to the crystallization that occurs during cooling which results in FDM part warpage. Previous work used process simulation models to study the effects of material parameters and FDM process variables on the part warpage seen using polypropylene (PP). In this work, the process simulation models were adapted to investigate warpage of FDM parts made with a high-performance semicrystalline polymer, polyphenylene sulfide (PPS). Material parameters in the PPS process simulation models were individually changed to the PP values to investigate which material parameters cause PP to exhibit higher warpage than PPS. Material parameters of interest included coefficient of thermal expansion (CTE), thermal conductivity, heat capacity, and Young’s modulus. Additional material parameters based on material property modification through the addition of fillers were investigated in order to establish the relationship between material parameters and warpage values. The simulation models suggested that the CTE has the largest impact on FDM part warpage. Decreasing the CTE in the simulation model resulted in a decrease in the FDM part warpage by the same factor.

The anisotropy of single crystal copper and crystal orientation have a significant effect on the micro-milling process. At present, there is no systematic and perfect theory to explain the influence of single crystal orientation on the micro-milling process. Therefore, it is urgent to conduct an in-depth study on the micro-milling process of single crystal copper. In this paper, based on the theory of crystal plasticity, considering the anisotropy of single crystal copper, the VUMAT material subroutine of single crystal copper is programmed by the Fortran language, and the crystal plastic constitution is introduced into the finite element simulation. The model of the micro-milling tool and work-piece is established and meshed. Considering the friction among the tool and the work-piece, material removal, etc., the three-dimensional finite element simulation model of single crystal copper micro-milling process is achieved by ABAQUS software. The validity of the simulation model of the micro-milling process of single crystal copper considering the single crystal plastic constitution is verified by experimental micro-milling forces. The research has explored a feasible way to predict the micro-milling force of single crystal copper, and has provided a reference for revealing the micro-milling mechanism of single crystal materials.

The article describes a simulation model of airliner evacuation process and an application developed to perform agent-based simulation for this model. The model contains the airliner map and model of agent's behaviour. The simulation is implemented as a web application with settings of simulation parameters. After performing the simulation, a report and visualization animation are generated.

Output from two process simulation models (EPIC and GLEAMS) was combined with a farm level linear programming model to assess the economic and environmental implications of selected eastern Corn Belt farming systems. The farm level economic results suggest that an alfalfa ( Medicago sativa L.)‐based cropping system is generally less profitable than a corn‐soybean ( Zea mays L.‐Glycine max L. [Merr.]) rotation produced under farm program prices or recent average market price conditions. Net returns are projected to decline by approximately 38% if alfalfa is included in an eastern Corn Belt cropping system. The adoption of a corn‐alfalfa cropping system could reduce annual soil erosion and the quantity of nitrates in surface water runoff relative to a conventional corn‐soybean rotation. The corn‐alfalfa system, however, leads to an increase in atrazine and alachlor runoff in surface water and an increase in nitrate percolation. A more environmentally desirable outcome may be attained by continuing farm programs that reduce acreage planted to corn. Yet to maintain farm income and encourage voluntary farmer participation, taxpayer costs may be unacceptably high. Thus, there are significant trade‐offs among environmental goals, federal budget reduction efforts, and income and employment in farming and agribusiness.Research QuestionProponents of alternative agriculture suggest that certain sustainable cropping systems can reduce soil erosion and water pollution without adversely affecting farmers ’ incomes. This research evaluated the farm level environmental and economic impacts of cropping systems in the eastern Corn Belt, which include alfalfa in rotation with other conventional row crops.Literature SummaryMost economic studies of alternative crop production systems have focused on the costs of adoption but have generally ignored the environmental impacts. Studies that have considered environmental impacts have typically focused on a single factor, for example soil loss or sedimentation.Study DescriptionTwo 500 acre farms were modelled: one on a Drummer silty clay loam, a high productivity soil commonly found in northwestern Indiana and eastern Illinois; and the second on a Clermont silt loam, a low productivity soil found in southern Indiana and Ohio.Three cases were analyzed: (i) a government program case with a 10% corn set‐aside, (ii) a market price scenario based on observed market prices for the crops, and (iii) a policy option requiring one‐fourth of the farm to produce alfalfa. Input use amounts can be found in Table .A farm‐level linear programming model was used for the economic analysis. The objective function of the model maximized gross revenue minus variable costs subject to constraints which included land, labor, and machinery resource requirements and availability during critical crop production periods.Two process simulation models were used to analyze the environmental impacts of the different cropping systems. The first of these was the Erosion Productivity Impact Calculator (EPIC). The second was Groundwater Loading Effects of Agricultural Management Systems (GLEAMS).Applied QuestionWas alfalfa profitable and did it enter the optimal cropping pattern?At an average yield of 5 tons/acre on the high productivity soil and 3.50 tons on the low productivity soil, alfalfa was a profitable crop, but not as profitable as corn and soybeans. Therefore, it did not enter the optimal solution as generated by the linear programming model. Sensitivity analysis showed that it would enter the solution on the highly productive soil at a price of $86.50/ton or at a yield of 7.33 tons/acre. Likewise, on the lower quality soil it would enter at a price of $84.50/ton or a yield of 4.50 tons/acre.What happened to returns when alfalfa had to be planted?When 1/4 of the farm was planted to alfalfa, whole farm net returns were reduced 50% and 64% on the high and low productivity soils, respectively, relative to the government program cases, which produced the highest net returns.How did the cases compare environmentally?On both soil types, the results from this study suggest that the adoption of a corn‐alfalfa Cropping system could reduce annual soil erosion and decrease the quantity of nitrates in surface water runoff relative to a conventional corn‐soybean rotation (Fig. ). The corn‐alfalfa system, however, can lead to an increase in atrazine and alachlor runoff in surface water as well as an increase in nitrates lost in percolate (Fig. and ). Input use amounts for crops used in simulation models. Input: N P Atrazine Alachlor Metolachlor Bentazon Dimethoate Carbofuran Trade name: Atrazine Lasso Dual Basagran Cygon Furadan Crop Formulation: 4 L 4 EC 8 EC 4 EC 4 EC 4 F ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐lb‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ High productivity soil Corn 153 23 1.2 2.0 Soybeans 30 2.5 1.0 Alfalfa 70 0.4 0.75 Set‐aside 50 Low productivity soil Corn 90 8 0.9 2.0 Soybeans 24 2.0 0.33 Alfalfa 70 0.4 0.75 Set‐aside 50 Fertilizer use rate is actual pounds applied. Herbicide and insecticide use rate is pounds per acre of active ingredient. imageimage

Depending on the complexity of organizational processes, the development of process simulation models might be a very demanding activity in which simulation professionals describe business processes using a specific simulation language. Besides being a difficult and error prone activity, process simulation modelling is also a major reason why simulation projects have a tendency to take too much time to be accomplished. In an effort to contribute to improve the situation, in this paper we present an approach in which previously developed process simulation components are used in the context of simulation projects. Using this approach, new process simulation models are developed in a component-based fashion by simply selecting pieces of simulation functionality from a repository of process simulation components, which were previously developed and properly tested. As an example, by taking advantage of the componentization mechanisms available in a specific simulation tool, we have developed a small set of process simulation components which were stored in a repository and then used in the development of a new business process simulation model.

Energy system optimization model for tissue papermaking process

Model validation is an important step for testing the correctness and accuracy of a simulation model of petrochemical process. However there are few systematic approaches which can carry out complete and exhaustive validation due to the complexity of petrochemical process. A signed directed graph based simulation model validation framework for chemical process was proposed. There are three levels in the framework including single variable validation, multiple variables validation and abnormal condition validation. There are three sublevels in every level including qualitative validation, semi-quantitative validation and quantitative validation. Signed directed graph is used to generate test cases. The simulation model can be validated in different levels by the cases. The quality of the simulation model can be guaranteed if all the levels can be satisfied. The framework was used for validating a model of a binary evaporation process. It was proved that the quality of the model can be guaranteed by using the framework.

Simulation modeling provides powerful decision support capabilities for production planning in manufacturing systems, yet widespread adoption remains limited by significant barriers in model development and maintenance. Traditional simulation approaches require substantial expertise, time investment, and financial resources, creating accessibility challenges particularly for small and medium enterprises. Current research on automatic simulation generation overlooks the significant potential that generative AI can offer in bridging the gap between natural language expression and executable model creation. This paper presents a novel methodology integrating large language models (LLMs) with automatic simulation model generation (ASMG) to enable direct generation of executable simulation models from natural language conversations. Unlike existing ASMG approaches that require formal specifications or simulation knowledge, our framework reduces programming requirements by allowing users to create functional models through conversational interaction. Our approach leverages natural language processing capabilities to transform user requests into executable simulation models without requiring specialized programming knowledge, enhancing human–machine interaction in production planning environments. The framework implements a four-step process: user intent expression through natural language interfaces, knowledge extraction using structured templates, simulation model construction via object-oriented data-driven components, and simulation execution with comprehensive result analysis for resource utilization, bottleneck identification, and production scheduling optimization. Performance testing demonstrates successful model generation across 18 supported action types with response times ranging from 8 s for simple operations to 5 min for complete manufacturing system creation. By enabling direct conversion of natural language requests into functional simulation models, this LLM-enhanced ASMG approach represents a step toward expanding access to simulation technology for non-expert users while maintaining the analytical power needed for complex manufacturing decision support and production control.

Particle breakage in milling operations is often modeled using population balance models (PBMs). A discrete element method (DEM) model can be coupled with a PBM in order to explicitly identify the effect of material properties on breakage rate. However, the DEM-PBM framework is computationally expensive to evaluate due to high-fidelity DEM simulations. This limits its application in continuous process modeling for dynamic simulation, optimization, or control purposes. The current work proposes the use of surrogate modeling (SM) techniques to map mechanistic data obtained from DEM simulations as a function of processing conditions. To demonstrate the benefit of the SM-PBM approach in developing integrated process models for continuous pharmaceutical manufacturing, a comill-tablet press model integration utilizing the proposed framework is presented. The SM-PBM approach is in excellent agreement with the DEM-PBM approach to predict particle size distributions (PSDs) and dynamic holdup, with a maximum sum of square errors of 0.0012 for PSD in volume fraction and 0.93 for holdup in grams. In addition, the time taken to run a DEM simulation is in the order of days whereas the proposed hybrid model takes few seconds. The SM-PBM approach also enables comill-tablet press model integration to predict tablet properties such as weight and hardness. The proposed hybrid framework compares well with a DEM-PBM framework and addresses limitations on computational expense, thus enabling its use in continuous process modeling.

This paper presents the issue of general methodology for modeling and simulation of seaport and inland terminals in intermodal freight transportation systems. The report documents a phase of the on-going more comprehensive effort aimed at developing a generalized modeling capability to provide strategic and tactical decision support for transportation logistics and intermodal terminals. By providing the object-oriented process of simula tion modeling with the coherent and uniform methodo logical basis, it was possible to construct a practical tool "TRANSNODE," The Simulator of Intermodal Transportation Terminals which allows one to model and simulate any transportation terminal, or a group of interconnected terminals, large or small, multipurpose or specialized, at optional scale. Knowledge-base and artificial intelligence concepts were incorporated in the simulator. Different from traditional simulation modeling, which combines data, knowledge and control program ming, the data-driven simulation modeling approach of the TRANSNODE system treats data and control logic as distinct parts. The resulting model is a generic simulator which can be used in many different application scenarios without requiring user simulation knowledge to modify the program. The only thing the user must do is supply the input data in the specified format through data files. Different terminal configura tions can be simulated merely by changing the input data. The developed technology is expected to be used by the industry for supporting their strategic and tactical decisions, by engineering firms in evaluating the design of their client facilities, their policies, and by the universities and research institutes in supporting and furthering their research.

This research has been performed in the Ethylene Oxide production process. It is a flammable and colorless gas at temperatures above 11 °C. It is an important commodity chemical for the production of solvents, antifreeze, textiles, detergents, adhesives, polyurethane foam, and pharmaceuticals. Small amounts of Ethylene Oxide [EO] are used in manufacturing fumigants and sterilants for spices and cosmetics, as well as hospital sterilization for surgical equipment. Modern Ethylene oxide [EO] productions employ either air or oxygen (O2)to oxidize ethylene (C2H4) with a silver catalyst on an alumina oxide carrier[Ag/Al2O3]catalyst packed in a fixed-bed reactor (plug-flow reactor)but the oxygen-base reaction process is more desirable here we used oxygen. Mainly two reactions occur, partial oxidation of ethylene to ethylene oxide and total oxidation of ethylene to carbon dioxide and water. The design models of the process in this research based on a three-part system. They are: the reaction system, absorption system and Ethylene Oxide [EO] purification system. The largest cost in production of ethylene oxide is ethylene therefore, it’s important to optimize the selectivity towards ethylene oxide and thus reduce the consumption of Ethylene. The aim of this work is to create a simulation model of the Ethylene Oxide production process from Ethylene using Aspen Hysys V9. Also to knowing the optimum operational conditions (temperature –pressure –flow rate) for the oxidation reactions of Ethylene. The simulation was running three times with various operational conditions to make a good result. The conclusion was that during operational time the activation energy increased for both reactions which have to be compensated with increasing reactor temperature. At the same time the selectivity for producing Ethylene Oxide decreases, i.e. more carbon dioxide and water are formed. The simulation models yield Ethylene Oxide with purity of 99.2%.

The aim of the research is to develop a modeling methodology for solving problems associated with the creation of simulation models and means of information and technological support for the tasks of allocating water resources on drainage systems for double regulation of the water regime of soils. The methodological and informational basis of the work was formed by the experience of creating and operating existing means of information technology support for the design and operation of double regulation drainage systems, the provisions of normative and technical documents on the automation of systems, as well as the design features of drainage and humidification and drainage systems. irrigation systems. As a result of studies of the problem of distribution of water resources on a specific system, the main stages were determined: the allocation of its blocks for which a system of water resources regulation is being developed, the allocation of subsystems in the structure, classification of tasks in subsystems, construction of an information model of the system, construction of a complex of models. To solve the problem associated with the development of simulation models and means of information technology support for the tasks of water resources distribution on dual control systems, it is proposed to use the method of contour modeling of water resources management regimes. The essence of the methodology consists in identifying characteristic contours in the structure of the water distribution network, for which you can use standard modeling algorithms and tools (quickly adjusted to the parameters of these contours) and sequentially calculating the parameters of the distribution of water resources for each of them. In this connection, the main control loops have been determined: the control loop «Water consumer № 1, 2 ... n», «Group of water consumers № 1, 2 ... n», «Section of the system № 1, 2 ... n» and «System». The proposed technique allows you to select typical control loops and then, in the selected standard loop, select characteristic control loops, along which simulation modeling of the processes of regulating the distribution of water resources over all control loops is carried out. The carried out simulation modeling of regulation processes throughout the «system» can be used by the maintenance service of the double regulation drainage system as variations in solutions when controlling the operation of regulatory structures, pumping stations and other structures of the system used to control water distribution.