scholarly journals Simulation and Optimization of the VTC200C Machining Center Production Plan

TEM Journal ◽  
2020 ◽  
pp. 1295-1306
Author(s):  
Marian Králik ◽  
Vladimír Jerz
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Input Data ◽  
Simulation Software ◽  
Efficient Production ◽  
Production Plan ◽  
Output Data ◽  
Simulation And Optimization ◽  
Machining Center ◽  
Plant Simulation

The paper describes the use of the Plant Simulation software to create a simulation model of the manufacturing process in the VTC200C machining centre. A genetic algorithm was used to optimize the production process. It is an algorithm that learns itself and looks for the best solution based on input data. The optimization is done based on the assessment of the output data from the simulation model. Based on the results of the optimization, a more efficient production plan was designed in the selected company.

scholarly journals Production Planning Based on a Genetic Algorithm Controlled Simulation Model

2021 ◽  
pp. 233-243
Author(s):  
Alexey N. Sochnev
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Optimization Procedure ◽  
Simulation Models ◽  
Simulation Software ◽  
Simulation Approach ◽  
Fitness Functions ◽  
Optimization And Simulation ◽  
Plant Simulation ◽  
Positive Effect

The article proposes an approach to solving the task of operational calendar planning of production based on the application of the principles of the optimization and simulation approach. The production simulation model is implemented using the Tecnomatix Plant Simulation software. The optimization procedure is represented by a genetic algorithm. In the implementation of the genetic algorithm, a simulation model is used to evaluate fitness functions. An example of using the proposed approach for a typical production system is given and the positive effect of its application is confirmed. Features of use, positive and negative properties, as well as the possibility of replication to other types of simulation models are revealed

scholarly journals Dynamic Simulation of Petrochemical Wastewater Treatment Using Wastewater Plant Simulation Software

2018 ◽  
Vol 203 ◽  
pp. 03005
Author(s):  
Idzham Fauzi Mohd Ariff ◽  
Mardhiyah Bakir
Keyword(s):  
Simulation Model ◽  
Dynamic Simulation ◽  
Stable Condition ◽  
Oxygen Demand ◽  
Simulation Software ◽  
Petrochemical Plant ◽  
Dynamic Simulation Model ◽  
Plant Monitoring ◽  
Plant Simulation

A dynamic simulation model was developed, calibrated and validated for a petrochemical plant in Terengganu, Malaysia. Calibration and validation of the model was conducted based on plant monitoring data spanning 3 years resulting in a model accuracy (RMSD) for effluent chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N) and total suspended solids (TSS) of ±11.7 mg/L, ±0.52 mg/L and ± 3.27 mg/L respectively. The simulation model has since been used for troubleshooting during plant upsets, planning of plant turnarounds and developing upgrade options. A case study is presented where the simulation model was used to assist in troubleshooting and rectification of a plant upset where ingress of a surfactant compound resulted in high effluent TSS and COD. The model was successfully used in the incident troubleshooting activities and provided critical insights that assisted the plant operators to quickly respond and bring back the system to normal, stable condition.

scholarly journals Applying Simulation Modelling in Quantifying Optimization Results

2021 ◽  
Vol 15 (4) ◽  
pp. 518-523
Author(s):  
Ratko Stanković ◽  
Diana Božić
Keyword(s):  
Linear Programming ◽  
Simulation Model ◽  
Input Data ◽  
Optimization Problems ◽  
Programming Model ◽  
Optimal Solution ◽  
Simulation Modelling ◽  
Simulation Software ◽  
Programming Models ◽  
Freight Forwarding

Improvements achieved by applying linear programming models in solving optimization problems in logistics cannot always be expressed by physically measurable values (dimensions), but in non-dimensional values. Therefore, it may be difficult to present the actual benefits of the improvements to the stake holders of the system being optimized. In this article, a possibility of applying simulation modelling in quantifying results of optimizing cross dock terminal gates allocation is outlined. Optimal solution is obtained on the linear programming model by using MS Excel spreadsheet optimizer, while the results are quantified on the simulation model, by using Rockwell Automation simulation software. Input data are collected from a freight forwarding company in Zagreb, specialized in groupage transport (Less Than Truckload - LTL).

scholarly journals Nurse Scheduling Using Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Komgrit Leksakul ◽  
Sukrit Phetsawat
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Input Data ◽  
Level Of Service ◽  
Nurse Scheduling ◽  
Random Mutation ◽  
Scheduling Model ◽  
Hospital Staffing ◽  
Service Standards ◽  
The Mathematical Model

This study applied engineering techniques to develop a nurse scheduling model that, while maintaining the highest level of service, simultaneously minimized hospital-staffing costs and equitably distributed overtime pay. In the mathematical model, the objective function was the sum of the overtime payment to all nurses and the standard deviation of the total overtime payment that each nurse received. Input data distributions were analyzed in order to formulate a simulation model to determine the optimal demand for nurses that met the hospital’s service standards. To obtain the optimal nurse schedule with the number of nurses acquired from the simulation model, we proposed a genetic algorithm (GA) with two-point crossover and random mutation. After running the algorithm, we compared the expenses and number of nurses between the existing and our proposed nurse schedules. For January 2013, the nurse schedule obtained by GA could save 12% in staffing expenses per month and 13% in number of nurses when compare with the existing schedule, while more equitably distributing overtime pay between all nurses.

Simulation and optimization of an experimental membrane wastewater treatment plant using computational intelligence methods

2011 ◽  
Vol 63 (10) ◽  
pp. 2255-2260 ◽  
Author(s):  
T. Ludwig ◽  
P. Kern ◽  
M. Bongards ◽  
C. Wolf
Keyword(s):  
Wastewater Treatment ◽  
Simulation Model ◽  
Computational Intelligence ◽  
Municipal Wastewater ◽  
Optimization Problems ◽  
Treatment Plant ◽  
Simulation Software ◽  
Simulation And Optimization ◽  
Highly Nonlinear ◽  
Computational Intelligence Methods

The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.

scholarly journals Fine Description of Multi-Process Operation Behavior in Steelmaking-Continuous Casting Process by a Simulation Model with Crane Non-Collision Constraint

Metals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 1078 ◽  
Author(s):  
Yang ◽  
Zhang ◽  
Guan ◽  
Hong ◽  
Gao ◽  
...  
Keyword(s):  
Continuous Casting ◽  
Simulation Model ◽  
Production Scheduling ◽  
Casting Process ◽  
Simulation Software ◽  
Continuous Casting Process ◽  
Proposed Model ◽  
Dynamic Simulation Model ◽  
Process Operation ◽  
Plant Simulation

The fine description of multi-process operation behavior in steelmaking-continuous casting process is an important foundation for the improvement of production scheduling in steel plants. With sufficient consideration on non-collision movements among cranes, a dynamic simulation model is established by Plant Simulation software to describe the operation behavior of multi-process in the steelmaking-continuous casting process of lacking refining span. The design and implement of simulation are illustrated based on a typical workshop layout of “one converter-one refining furnace-one caster”. The method to avoid the collisions between adjacent cranes is represented in detail. To validate the availability of this model, an actual steel plant without refining span is studied, and simulation experiments are conducted by introducing actual production plans as simulation instances. The simulated findings agree well with the actual results of interest, including the total completed times of simulation instances, the turnover number of ladles, and the transfer times of heats among different processes. Hence, the proposed model can reliably simulate the multi-process operation behavior in steelmaking-continuous casting process.

The Industry Assembly Line Layout’s Modeling and Simulation in Industry Manufacturing Based on Genetic Algorithm

2013 ◽  
Vol 675 ◽  
pp. 3-7
Author(s):  
Fang Guo ◽  
Zhi Hong Huang
Keyword(s):  
Genetic Algorithm ◽  
Modeling And Simulation ◽  
Equilibrium Problem ◽  
Assembly Line ◽  
Simulation Software ◽  
Heuristic Procedure ◽  
Plant Simulation ◽  
Line Design

The equilibrium problem is one important aspect of industry assembly line design. This paper puts forward the method to solve the industry assembly line’s equilibrium problem based on the genetic algorithm’s heuristic procedure and on this basis it also optimizes the industry assembly line’s layout and synthetically considers the material carrying cost, plant area’s use ratio and other factors in industry manufacturing. Then it optimizes by eM-Plant simulation software and combining with genetic algorithm to efficiently acquire visual and satisfying layout effects. At last, it uses examples of industry assembly line to verify this method’s feasibility.

scholarly journals Calculation of an SPTA set using the Dialog computer simulation system (Part 1. General provisions for the calculation of an SPTA set)

Dependability ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 32-38
Author(s):  
B. A. Dolgopolov ◽  
Yu. G. Zayko ◽  
V. A. Mikhailov ◽  
A. V. Trakhtomirov
Keyword(s):  
Simulation Model ◽  
Input Data ◽  
Simulation Models ◽  
Spare Parts ◽  
Simulation Software ◽  
Statistical Testing ◽  
Modes Of Operation ◽  
Target Values ◽  
Characteristic Features ◽  
Redundant Systems

The paper describes the design concept of the DIALOG simulation software suite (SSS) intended for calculating the dependability indicators of electronic systems (ES) of random configuration, as well as solving problems associated with assuring the functional dependability of such systems. The DIALOG SSS employs a specially designed DIALOG-SINTEZ technology that enables automatic synthesis of event simulation models in the form of programs in the selected programming language. In DIALOG SSS, the input data include: system composition in the form of a combination of conventional blocks; criteria of failure event occurrence and repairs; random value parameters (failures of system components in various modes of operation, SPTA requests, etc.); stages of system operation and types of repairs; list of calculated indicators. For the purpose of ensuring the required indicators, the simulation models undergo statistical testing under modified indicators of random values in each new test. Based on the accumulated results of all the performed tests the required indicators are calculated. The DIALOG SSS consists of four components: DIALOG-NRS is intended for the calculation of dependability indicators of non-repairable redundant systems; DIALOG-RRS is intended for the calculation of dependability indicators of repairable redundant systems, as well as the number of and cost of warranty repairs; DIALOG-ZIP-NS is intended for SPTA sets calculation for simple non-redundant systems; DIALOG-ZIP-RS is intended for SPTA sets calculation for any redundant systems. SPTA set calculation is normally done using standard procedures described in regulatory documents. In solving the direct problem of optimal SPTA set calculation, the input data includes the required value of one of the two SPTA sufficiency indicators (SI) and type of costs that are to be optimized (minimized) in order to achieve the target values of SI. In solving the inverse problem of optimal SPTA set calculation, it is required to ensure the specified costs of the initial SPTA supply. As the SPTA supply SI, the mean spare parts (SP) supply delay time out of SPTA Δtd.SPTA and SPTA availability coefficient Ca.SPTA are used. SPTA optimization using the DIALOG-ZIP SSS allows improving user options through the following additional characteristics: SPTA SP failure logging; optimization of SP count and accounting for the their characteristic features for the purpose of SP emergency delivery (ED); capability to use products with any type of redundancy; when using SPTA-G group set, capability to include differently-structured products into ESs. The paper sets forth the structure diagram of the DIALOG SSS programs interaction, that implies three modes of operation of the simulation model: SI calculation for specific SPTA contents; calculation of preliminary SPTA supply before the beginning of optimization; calculation of optimal SPTA set. The authors examine the matters related to the selection of the required number and duration of simulation model testing.

scholarly journals The Use of a Genetic Algorithm for Sorting Warehouse Optimisation

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1197
Author(s):  
Patrik Grznár ◽  
Martin Krajčovič ◽  
Arkadiusz Gola ◽  
Ľuboslav Dulina ◽  
Beáta Furmannová ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Business Processes ◽  
Optimal Number ◽  
Simulation Software ◽  
Heuristic Methods ◽  
Major Purpose ◽  
Processing Times ◽  
Speed Up ◽  
Plant Simulation

In the last decade, simulation software as a tool for managing and controlling business processes has received a lot of attention. Many of the new software features allow businesses to achieve better quality results using optimisation, such as genetic algorithms. This article describes the use of modelling and simulation in shipment and sorting processes that are optimised by a genetic algorithm’s involvement. The designed algorithm and simulation model focuses on optimising the duration of shipment processing times and numbers of workers. The commercially available software Tecnomatix Plant Simulation, paired with a genetic algorithm, was used for optimisation, decreasing time durations, and thus selecting the most suitable solution for defined inputs. This method has produced better results in comparison to the classical heuristic methods and, furthermore, is not as time consuming. This article, at its core, describes the algorithm used to determine the optimal number of workers in sorting warehouses with the results of its application. The final part of this article contains an evaluation of this proposal compared to the original methods, and highlights what benefits result from such changes. The major purpose of this research is to determine the number of workers needed to speed up the departure of shipments and optimise the workload of workers.

Alternatives for Railroad Traffic Simulation Analysis

2005 ◽  
Vol 1916 (1) ◽  
pp. 34-41 ◽  
Author(s):  
Thomas White
Keyword(s):  
Input Data ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Accurate Assessment ◽  
Output Data ◽  
Output Analysis ◽  
Traffic Conditions ◽  
Analysis Methodology ◽  
Appropriate Care ◽  
Simulation Input

In North America, the process for determining appropriate railroad infrastructure for new service or an increased volume of existing service usually includes the use of simulation software. Decisions are generally based on statistical analysis of the simulation output. The simulation and analysis that are commonly conducted, however, may not provide an accurate assessment of the adequacy of the infrastructure. Furthermore, the output data comparisons commonly used to describe the effect of infrastructure on traffic may not be easily associated with traffic conditions. These shortcomings can be mitigated with appropriate care in developing the simulation input data and changing the output analysis methodology.

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