Self-Evolution of an Assembly Workshop in Knowledgeable Manufacturing Environment

2014 ◽  
Vol 602-605 ◽  
pp. 623-628
Author(s):  
Tian Hua Jiang ◽  
Hong Sen Yan
Keyword(s):  
Manufacturing Systems ◽  
Decision Processes ◽  
The Self ◽  
Production Performance ◽  
Evolution Process ◽  
Rolling Horizon ◽  
Decision Point ◽  
General Mathematical Model ◽  
Simulation Results ◽  
Knowledgeable Manufacturing

In this study, the self-evolution problem of knowledgeable manufacturing systems is studied by taking an assembly workshop as an example. The rolling horizon procedure (RHP) is adopted to implement the self-evolution process of the workshop. The whole dynamic self-evolution process is decomposed into several static decision processes. At each decision point, a static decision sub-problem needs to be solved. A general mathematical model of these sub-problems is built, and a bi-level genetic algorithm (BiGA) is designed. Simulation results show that the model and algorithm are feasible and effective. By comparison, the system with self-evolution operations has a better production performance.

scholarly journals An Intelligent Evaluation Method to Analyze the Competitiveness of Airlines

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Zhao ◽  
Xumei Chen
Keyword(s):  
Neural Network ◽  
Prior Knowledge ◽  
Evaluation Method ◽  
Standard Sample ◽  
Reference Value ◽  
The Self ◽  
Index Data ◽  
Som Neural Network ◽  
Simulation Results ◽  
Self Organizing

An intelligent evaluation method is presented to analyze the competitiveness of airlines. From the perspective of safety, service, and normality, we establish the competitiveness indexes of traffic rights and the standard sample base. The self-organizing mapping (SOM) neural network is utilized to self-organize and self-learn the samples in the state of no supervision and prior knowledge. The training steps of high convergence speed and high clustering accuracy are determined based on the multistep setting. The typical airlines index data are utilized to verify the effect of the self-organizing mapping neural network on the airline competitiveness analysis. The simulation results show that the self-organizing mapping neural network can accurately and effectively classify and evaluate the competitiveness of airlines, and the results have important reference value for the allocation of traffic rights resources.

CHAOS SYNCHRONIZATION VIA UNIDIRECTIONAL COUPLING AND ITS APPLICATION TO SECURE COMMUNICATION

2009 ◽  
Vol 23 (32) ◽  
pp. 5949-5964 ◽  
Author(s):  
XINGYUAN WANG ◽  
MINGJUN WANG
Keyword(s):  
Secure Communication ◽  
Chaos Synchronization ◽  
Function Method ◽  
The Self ◽  
Largest Lyapunov Exponent ◽  
Global Synchronization ◽  
Unidirectional Coupling ◽  
Response System ◽  
Lyapunov Function Method ◽  
Simulation Results

This paper studies chaos synchronization via unidirectional coupling. The self-synchronization of Lorenz systems, modified coupled dynamos systems and hyperchaotic Chen systems is studied by three methods: the Lyapunov function method, the global synchronization method and the numerical calculation of the largest Lyapunov exponent method. In regard to application to communication, we show that via transmitting single signal the synchronization of the drive system and the response system can be achieved. An example of applying self-synchronization of hyperchaotic Chen systems to chaotic masking secure communication is presented in this paper. Simulation results show the effectiveness of the method.

Design and vibration analysis of a self-adaptive piston in a novel nanoimprint system

2017 ◽  
Vol 69 (4) ◽  
pp. 591-597
Author(s):  
Chaoran Liu ◽  
Yufeng Su ◽  
Jinzhao Yue ◽  
Junjie Wang ◽  
Weiwei Xia ◽  
...  
Keyword(s):  
Nanoimprint Lithography ◽  
Vibration Analysis ◽  
Design Methodology ◽  
The Self ◽  
Ball Screw ◽  
Piston Rings ◽  
Content Type ◽  
Simulation Results ◽  
The One ◽  
Self Adaptive

Purpose A self-adaptive piston is designed for the compressional gas cushion press nanoimprint lithography system. It avoids the lube pollution and high wear of traditional piston. Design/methodology/approach The self-adaptive piston device consists of symmetrical piston bodies, piston rings and other parts. The two piston bodies are linked by a ball-screw. The locking nut adjusts the distance between two piston bodies to avoid the piston rings from being stuck. The piston rings are placed between two piston bodies. Findings The simulation results based on COMSOL indicate that cylinder vibration caused by self-adaptive piston is 15.9 times smaller than the one caused by a traditional piston. Originality/value The self-adaptive piston is superior to the traditional piston in decreasing cylinder vibration.

The theoretical and experimental research on the thermodynamic process in transcritical carbon dioxide piston compressor

2018 ◽  
Vol 233 (2) ◽  
pp. 267-279
Author(s):  
Yulong Song ◽  
Qinfei Sun ◽  
Shuo Yang ◽  
Qijing Xing ◽  
Ling Cheng ◽  
...  
Keyword(s):  
Pressure Ratio ◽  
Piston Compressor ◽  
Volumetric Efficiency ◽  
Thermodynamic Process ◽  
Height Ratio ◽  
General Mathematical Model ◽  
Simulation Results ◽  
Transcritical Carbon Dioxide ◽  
Relative Measurements ◽  
Isentropic Efficiency

The general mathematical model of the transcritical CO2 compressor was presented to assess the compressor efficiencies including isentropic efficiency and volumetric efficiency based on the thermodynamic theories and compressor structures. Furthermore, the prototype of the transcritical CO2 system was established and relative measurements were carried out to evaluate the precision of the simulation. Results showed that the volumetric efficiency of the compressor kept decreasing while the isentropic efficiency increased first and then kept almost constant and even declined with the increase in the pressure ratio. Besides, the indicated efficiency and volumetric efficiency declined slightly with the decrease in the suction density corresponding to the increase in suction superheating. As for the effects of compressor structures on the performances, the indicated efficiency increased sharply and then decreased gradually, while the volumetric efficiency kept declining with the increase in the cylinder diameter-to-height ratio, respectively.

Numerical Simulation of Thermal Solvent Replacing Steam under Steam Assisted Gravity Drainage SAGD Process

2010 ◽  
Author(s):  
Weiqiang Li ◽  
Daulat D. Mamora
Keyword(s):  
High Temperature ◽  
Oil Recovery ◽  
Oil Sands ◽  
Steam Injection ◽  
Thermal Recovery ◽  
Production Performance ◽  
Gravity Drainage ◽  
Steam Assisted Gravity Drainage ◽  
Recovery Technique ◽  
Simulation Results

Abstract Steam Assisted Gravity Drainage (SAGD) is one successful thermal recovery technique applied in the Athabasca oil sands in Canada to produce the very viscous bitumen. Water for SAGD is limited in supply and expensive to treat and to generate steam. Consequently, we conducted a study into injecting high-temperature solvent instead of steam to recover Athabasca oil. In this study, hexane (C6) coinjection at condensing condition is simulated using CMG STARS to analyze the drainage mechanism inside the vapor-solvent chamber. The production performance is compared with an equivalent steam injection case based on the same Athabasca reservoir condition. Simulation results show that C6 is vaporized and transported into the vapor-solvent chamber. At the condensing condition, high temperature C6 reduces the viscosity of the bitumen more efficiently than steam and can displace out all the original oil. The oil production rate with C6 injection is about 1.5 to 2 times that of steam injection with oil recovery factor of about 100% oil initially-in-place. Most of the injected C6 can be recycled from the reservoir and from the produced oil, thus significantly reduce the solvent cost. Results of our study indicate that high-temperature solvent injection appears feasible although further technical and economic evaluation of the process is required.

scholarly journals Integration of Production Planning and Scheduling Based on RTN Representation under Uncertainties

Algorithms ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 120
Author(s):  
Tao Zhang ◽  
Yue Wang ◽  
Xin Jin ◽  
Shan Lu
Keyword(s):  
Production Planning ◽  
Integrated Model ◽  
Rolling Horizon ◽  
Optimization Strategy ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Proposed Model ◽  
Simulation Results ◽  
Period Decrease ◽  
Rolling Horizon Optimization

Production planning and scheduling are important bases for production decisions. Concerning the traditional modeling of production planning and scheduling based on Resource-Task Network (RTN) representation, uncertain factors such as utilities are rarely considered as constraints. For the production planning and scheduling problem based on RTN representation in an uncertain environment, this paper formulates the multi-period bi-level integrated model of planning and scheduling, and introduces the uncertainties of demand and utility in planning and scheduling layers respectively. Rolling horizon optimization strategy is utilized to solve the bi-level integrated model iteratively. The simulation results show that the proposed model and algorithm are feasible and effective, can calculate the consumption of utility in every period, decrease the effects of uncertain factors on optimization results, more accurately describe the uncertain factors, and reflect the actual production process.

A rolling horizon approach for production planning and condition-based maintenance under uncertain demand

2019 ◽  
Vol 233 (6) ◽  
pp. 1014-1028
Author(s):  
Lin Wang ◽  
Zhiqiang Lu ◽  
Yifei Ren
Keyword(s):  
Service Level ◽  
Condition Based Maintenance ◽  
Uncertain Demand ◽  
Programming Approach ◽  
Production Plan ◽  
Rolling Horizon ◽  
Decision Point ◽  
Total Cost ◽  
New Information ◽  
Maintenance Plan

In reality, the forecast of uncertainties often becomes more accurate with the approaching of the forecasted period. This article proposes a rolling horizon approach to dynamically determine the production plan and the maintenance plan for a degradation system under uncertain environment. In each rolling horizon, demand forecasts are updated with new information from customers, and the degradation level of system is confirmed by inspection. By taking advantage of the updated uncertainties, at each decision point, the maintenance plan is determined by an advance-postpone balancing approach and the production plan is optimized by a heuristic algorithm in a two-stage stochastic model. Numerical results validate that the rolling horizon approach has great superiority over traditional stochastic programming approach in terms of real total cost and service level.

ACTIVE TRACKING CONTROL OF THE HYPERCHAOTIC LORENZ SYSTEM

2008 ◽  
Vol 22 (19) ◽  
pp. 1859-1865 ◽  
Author(s):  
XINGYUAN WANG ◽  
DAHAI NIU ◽  
MINGJUN WANG
Keyword(s):  
Numerical Simulation ◽  
Tracking Control ◽  
Chaotic Systems ◽  
Lorenz System ◽  
The Self ◽  
Hyperchaotic System ◽  
Reference Signals ◽  
Tracking Controller ◽  
Hyperchaotic Lorenz System ◽  
Simulation Results

A nonlinear active tracking controller for the four-dimensional hyperchaotic Lorenz system is designed in the paper. The controller enables this hyperchaotic system to track all kinds of reference signals, such as the sinusoidal signal. The self-synchronization of the hyperchaotic Lorenz system and the different-structure synchronization with other chaotic systems can also be realized. Numerical simulation results show the effectiveness of the controller.

Formation of embedded Co nanostructures in Cu(001) surface under electromigration

2020 ◽  
pp. 2150090
Author(s):  
S. V. Kolesnikov ◽  
A. L. Klavsyuk ◽  
A. M. Saletsky
Keyword(s):  
Monte Carlo ◽  
Current Density ◽  
Kinetic Monte Carlo ◽  
The Self ◽  
Atomic Scale ◽  
Self Organization ◽  
Simulation Results ◽  
Self Learning

Formation of embedded Co nanostructures in Cu(001) surface under electromigration is investigated on the atomic scale by performing self-learning kinetic Monte Carlo (kMC) simulations. The analysis of simulation results reveals the following important result. The electromigration of vacancies does not influence on the self-organization of Co nanostructures in the first layer of Cu(001) surface at all values of current density, which can be achieved in experiments.

scholarly journals Development of Operator Theory in the Capacity Adjustment of Job Shop Manufacturing Systems

2019 ◽  
Vol 9 (11) ◽  
pp. 2249 ◽  
Author(s):  
Ping Liu ◽  
Qiang Zhang ◽  
Jürgen Pannek
Keyword(s):  
Manufacturing Systems ◽  
Job Shop ◽  
Control Method ◽  
Adjustment Process ◽  
Control Approach ◽  
Work In Process ◽  
Industrial Manufacture ◽  
Demand Fluctuations ◽  
Simulation Results ◽  
High Flexibility

With the development of industrial manufacture in the context of Industry 4.0, various advanced technologies have been designed, such as reconfigurable machine tools (RMT). However, the potential of the latter still needs to be developed. In this paper, the integration of RMTs was investigated in the capacity adjustment of job shop manufacturing systems, which offer high flexibility to produce a variety of products with small lot sizes. In order to assist manufacturers in dealing with demand fluctuations and ensure the work-in-process (WIP) of each workstation is on a predefined level, an operator-based robust right coprime factorization (RRCF) approach is proposed to improve the capacity adjustment process. Moreover, numerical simulation results of a four-workstation three-product job shop system are presented, where the classical proportional–integral–derivative (PID) control method is considered as a benchmark to evaluate the effectiveness of RRCF in the simulation. The simulation results present the practical stability and robustness of these two control systems for various reconfiguration and transportation delays and disturbances. This indicates that the proposed capacity control approach by integrating RMTs with RRCF is effective in dealing with bottlenecks and volatile customer demands.

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