The Production System Automatic Layout Based on Simulation

2013 ◽  
Vol 819 ◽  
pp. 393-397
Author(s):  
Chao Lv ◽  
Shuang Liu ◽  
Shi Ming Wang ◽  
Bei Cai
Keyword(s):  
Production System ◽  
Production Efficiency ◽  
Optimal Solution ◽  
Operation Time ◽  
Simulation Software ◽  
Main Function ◽  
Automatic Layout ◽  
And Function ◽  
Plant Simulation ◽  
System Layout

The U-Shaped layout and function of production system is studied, the purpose is showing how the layouts and their main function influence each other, thus to provide enlightenments and references to improve the design of the production system layout. The simple automatic arrangement system is presented based on Plant Simulation software and focused on an equipment layout problem. The automatic layout system is an automatic layout system of workshop layout according to data; adopt the method of simulation modeling combined with optimization of the workshop layout. According to the different optimization objectives, the user can get a different optimal solution. Through simulation, we can get the default layout of the carrying amount, size and arrangement, combined with the enterprise's actual situation. The appropriate adjustments and production efficiency of production workshop are improved, and the operation time of manual modeling is shortened.

Optimization of production system in Plant Simulation

SIMULATION ◽  
2021 ◽  
pp. 003754972110389
Author(s):  
Peter Malega ◽  
Vladimír Gazda ◽  
Vladimír Rudy
Keyword(s):  
Production System ◽  
Business Strategy ◽  
Large Scale ◽  
Production Efficiency ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Production Cycle ◽  
Model Parameters ◽  
Practical Applications ◽  
Plant Simulation

An optimization of the production process is defined as the search for solutions with improved production efficiency. Process optimization should be one of the main components of a business strategy that not only delivers benefits to customers but also helps increase the performance of production processes and benefits the entire business. The traditional approaches to job shop scheduling are based on the exact mathematically formalized model. If the number of model parameters is high and the environment is rather uncertain, the practical applications are quite restricted. That is why the theory proposes an approach based on a large-scale computer simulation. The main goal of this paper is to show that in a concrete company case, the simulation-based approach provides increased productivity. The presented study proposes the practical application of the Tecnomatix software used in the research to optimize the production system. The partial aims of the paper are as follows: (1) to create a simulation model of the production system with the help of the Plant Simulation module, (2) to model the current state of matters in the company, and (3) to propose a solution to the problem. Ultimately, we show that the simulation approach to the production line control provides rather effective solutions when compared to the intuitive one based on trial-and-error experience. The improvement includes a significant (1) shortening of the production cycle and (2) increase in productivity.

scholarly journals Research on the Reliability Allocation Method for a Production System Based on Availability

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yankun Wang ◽  
Binbin Xu ◽  
Tianqi Ma ◽  
Ziyue Wang
Keyword(s):  
Production System ◽  
Simulation Software ◽  
Scaling Factor ◽  
System Availability ◽  
Reliability Allocation ◽  
Equivalent Unit ◽  
Allocation Method ◽  
Complex Production System ◽  
Buffer States ◽  
Plant Simulation

This paper involves a production system, which is composed of units (workstations) and buffers. The buffer is used to store semifinished and finished products in the production process, to reduce the impacts of bad equipment in the production system on the entire system performance. Considering the characteristics of the large number of components and the state of the buffers in the production system, this paper considers the influences of buffer states on upstream and downstream units. When using the availability as the allocation index and combining it with Markov theory, the production unit (workstation) and upstream and downstream buffers are regarded as an equivalent unit (workstation) with multiple output states. We establish the relationship between the availability of each equivalent unit (workstation) and the production system availability and determine a scaling factor for the availability of the equivalent unit to account for the system availability. The expected availability goal of the production system is allocated to each equivalent unit (workstation) by the scaling factor; then, the availability of each equivalent unit (workstation) is assigned to each unit. Finally, the Plant Simulation software is used to simulate and analyze the production system to verify the correctness of the allocation method and realize the reliability allocation from a complex production system to a unit.

scholarly journals Fault diagnosis of industrial robot reducer by an extreme learning machine with a level-based learning swarm optimizer

2021 ◽  
Vol 13 (5) ◽  
pp. 168781402110195
Author(s):  
Jianwen Guo ◽  
Xiaoyan Li ◽  
Zhenpeng Lao ◽  
Yandong Luo ◽  
Jiapeng Wu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Extreme Learning Machine ◽  
Large Scale ◽  
Production Efficiency ◽  
Industrial Robot ◽  
Optimal Solution ◽  
Industrial Robots ◽  
Generalization Performance ◽  
Gradient Descent Algorithm ◽  
Learning Machine

Fault diagnosis is of great significance to improve the production efficiency and accuracy of industrial robots. Compared with the traditional gradient descent algorithm, the extreme learning machine (ELM) has the advantage of fast computing speed, but the input weights and the hidden node biases that are obtained at random affects the accuracy and generalization performance of ELM. However, the level-based learning swarm optimizer algorithm (LLSO) can quickly and effectively find the global optimal solution of large-scale problems, and can be used to solve the optimal combination of large-scale input weights and hidden biases in ELM. This paper proposes an extreme learning machine with a level-based learning swarm optimizer (LLSO-ELM) for fault diagnosis of industrial robot RV reducer. The model is tested by combining the attitude data of reducer gear under different fault modes. Compared with ELM, the experimental results show that this method has good stability and generalization performance.

scholarly journals Solution of Bottlenecks in the Logistics Flow by Applying the Kanban Module in the Tecnomatix Plant Simulation Software

2021 ◽  
Vol 13 (14) ◽  
pp. 7989
Author(s):  
Miriam Pekarcikova ◽  
Peter Trebuna ◽  
Marek Kliment ◽  
Michal Dic
Keyword(s):  
Lean Manufacturing ◽  
Business Processes ◽  
Software Tool ◽  
Transportation Systems ◽  
Simulation Software ◽  
Simulation Methods ◽  
Software Environment ◽  
Production Logistics ◽  
Pull System ◽  
Plant Simulation

The presented article deals with the issue of solving bottlenecks in the logistics flow of a manufacturing company. The Tx Plant Simulation software tool is used to detect bottlenecks and deficiencies in the company’s production, logistics and transportation systems. Together with the use of simulation methods and lean manufacturing tools, losses in business processes are eliminated and consequently flow throughput is improved. In the TX Plant Simulation software environment, using Bottleneck analyzer, bottlenecks were defined on the created simulation model and a method of optimizing logistics flows was designed and tested by introducing the Kanban pull system. This resulted in an improvement and throughput of the entire logistics flow, a reduction in inter-operational stocks and an increase in the efficiency of the production system as a whole.

Well Placement Technique and Production Optimization for Mature Field - A Case Study of L-X Field

2020 ◽  
Vol 46 ◽  
pp. 168-179
Author(s):  
Patrick Nwafor ◽  
Kelani Bello
Keyword(s):  
Oil And Gas ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Oil And Gas Industry ◽  
Optimization Method ◽  
Simulation Software ◽  
Production Optimization ◽  
Direct Optimization ◽  
Well Placement ◽  
Local Optimal Solution

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.

Simulation Optimization of Backrest Mechanism of Separable Bed Chair System

2021 ◽  
Vol 15 ◽  
pp. 1114-1123
Author(s):  
Meng Ning ◽  
Zhi Wu ◽  
Lianjie Chen ◽  
Fan Zhang ◽  
Huitao Chen
Keyword(s):  
Sudden Change ◽  
Optimal Solution ◽  
Simulation Software ◽  
Final Solution ◽  
Integration System ◽  
Modeling And Analysis ◽  
Movement Characteristics ◽  
Fixed Structure ◽  
The Relationship ◽  
Research And Design

Research and design an intelligent bed and chair integration system for assisting inconvenient mobility and aging population. The system consists of a removable detached wheelchair and a c-shaped bed with a fixed structure. The user can switch freely between the mobile wheelchair and the bed to meet the user's requirements of free movement and repositioning.Through the simulation software to analyze the movement characteristics of the bed backboard, the angle of the take-off and landing of the backboard and the sudden change of the take-off and abrupt angular velocity will cause the user to have dizziness and discomfort. In the case of determining the speed of the driving push rod, the relationship between mechanism parameters and installation parameters is the key to affect the lifting rate of the rear plate. Modeling and analysis of each mechanism is performed to determine the relationship between the mechanism parameters and the take-off and landing speed of the backplane. After optimizing the mechanism, the simulation is compared again to obtain the optimal solution. Finally, the optimal solution parameter is the final solution to improve the overall comfort of the nursing bed.

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.

PRACTICAL PRODUCTION LAYOUT DESIGN FOR MULTI-PRODUCT AND SMALL-LOT-SIZE PRODUCTION: A CASE STUDY

2016 ◽  
Vol 78 (7) ◽  
Author(s):  
Cheng Ying, Nyeoh ◽  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin
Keyword(s):  
Manufacturing Systems ◽  
Production Efficiency ◽  
Job Shop ◽  
Flow Line ◽  
Facility Layout ◽  
Layout Design ◽  
Simulation Software ◽  
Utilization Rate ◽  
Lot Size ◽  
Related Data

Facility layout design has an important function in manufacturing systems because it affects manufacturing costs, work in progress, lead times, and production output. This study presents facility layout designs for multi-product and small-lot-sized production lines. This research focuses on the development and analysis of layout alternatives on the basis of performance measures and aims to improve production efficiency. Thus, the tools and techniques available for the layout designed were investigated. Related data were collected, and alternative layouts were developed using the WITNESS simulation software. Finally, the alternative layouts were ana1yzed and evaluated using the analytic hierarchy process to identify the best possible layout. Two important parameters observed in the alternative layouts: the ability to produce a desired output and the flexibility of each layout coherent with the fluctuation of product demands in the industry. Results from analysis shows that suggested Model 3 with the combination of flow line and job shop configurations is the most suitable layout. This model has the highest machine utilization rate and the highest labour utilization rate yet requires only 21 operators, the lowest number of workers. For future work, this type of layout should be tested with different variation in lot sizes.

scholarly journals Structure and function relationships of proteins based on polar profile: a review.

2016 ◽  
Vol 63 (2) ◽  
Author(s):  
Carlos Polanco ◽  
Thomas Buhse ◽  
Vladimir N Uversky
Keyword(s):  
Mathematical Structure ◽  
Quantitative Structure Activity Relationship ◽  
Multidrug Resistant ◽  
Training Data ◽  
Main Function ◽  
Pharmaceutical Drugs ◽  
Linear Sequence ◽  
Wide Range ◽  
High Level ◽  
And Function

Proteins in the post-genome era impose diverse research challenges, the main are the understanding of their structure-function mechanism, and the growing need for new pharmaceutical drugs, particularly antibiotics that help clinicians treat the ever- increasing number of Multidrug-Resistant Organisms (MDROs). Although, there is a wide range of mathematical-computational algorithms to satisfy the demand, among them the Quantitative Structure-Activity Relationship algorithms that have shown better performance using a characteristic training data of the property searched; their performance has stagnated regardless of the number of metrics they evaluate and their complexity. This article reviews the characteristics of these metrics, and the need to reconsider the mathematical structure that expresses them, directing their design to a more comprehensive algebraic structure. It also shows how the main function of a protein can be determined by measuring the polarity of its linear sequence, with a high level of accuracy, and how such exhaustive metric stands as a "fingerprint" that can be applied to scan the protein regions to obtain new pharmaceutical drugs, and thus to establish how the singularities led to the specialization of the protein groups known today.

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).

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