Flexible Assembly Cell Optimization by Operational Analysis

2013 ◽  
Vol 309 ◽  
pp. 55-61 ◽  
Author(s):  
Angela Javorova ◽  
Martina Kusa ◽  
Miriam Matúšová
Keyword(s):  
Production Process ◽  
Situation Model ◽  
Competitive Environment ◽  
Model Parameters ◽  
Optimal Solutions ◽  
Flexible Assembly ◽  
Operational Analysis ◽  
Operation Analysis ◽  
Scientific Disciplines ◽  
Assembly Cell

Operation analysis one of the system scientific disciplines closely related to system engineering. This discipline is part of praxeology. Praxeology deals with the research effectiveness of the procedure methods for all areas of human activity. The aim of this analysis is creating solved situation model and their optimization. Optimization is model extremes finding. There are model parameters values that output achieved minimum or maximum. Competitive environment is the reason for finding optimal solutions in the production process.

Flexible Assembly Cell: An Implementation Experiment Using the Estelle FDT

1990 ◽  
pp. 221-232 ◽  
Author(s):  
V. B. Mazzola ◽  
J. P. Courtiat ◽  
M. Diaz ◽  
A. M. Druilhe ◽  
J. F. Lenotre ◽  
...  
Keyword(s):  
Flexible Assembly ◽  
Assembly Cell

scholarly journals Neutrosophic Number Optimization Models and Their Application in the Practical Production Process

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Angyan Tu ◽  
Jun Ye ◽  
Bing Wang
Keyword(s):  
Production Process ◽  
Optimal Solution ◽  
Optimization Models ◽  
Optimal Solutions ◽  
Practical Applications ◽  
Linear And Nonlinear Programming ◽  
Constrained Conditions ◽  
Minimum Objective Function ◽  
Maximum Minimum ◽  
Neutrosophic Number

In order to simplify the complex calculation and solve the difficult solution problems of neutrosophic number optimization models (NNOMs) in the practical production process, this paper presents two methods to solve NNOMs, where Matlab built-in function “fmincon()” and neutrosophic number operations (NNOs) are used in indeterminate environments. Next, the two methods are applied to linear and nonlinear programming problems with neutrosophic number information to obtain the optimal solution of the maximum/minimum objective function under the constrained conditions of practical productions by neutrosophic number optimization programming (NNOP) examples. Finally, under indeterminate environments, the fit optimal solutions of the examples can also be achieved by using some specified indeterminate scales to fulfill some specified actual requirements. The NNOP methods can obtain the feasible and flexible optimal solutions and indicate the advantage of simple calculations in practical applications.

Uncertainty in Operational Analysis of Two-Lane Highways

2002 ◽  
Vol 1802 (1) ◽  
pp. 105-114 ◽  
Author(s):  
R. Tapio Luttinen
Keyword(s):  
Input Data ◽  
Travel Speed ◽  
Level Of Service ◽  
Model Parameters ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Operational Analysis ◽  
Percent Time ◽  
Different Types ◽  
Percent Time Spent Following

The Highway Capacity Manual (HCM) 2000 provides methods to estimate performance measures and the level of service for different types of traffic facilities. Because neither the input data nor the model parameters are totally accurate, there is an element of uncertainty in the results. An analytical method was used to estimate the uncertainty in the service measures of two-lane highways. The input data and the model parameters were considered as random variables. The propagation of error through the arithmetic operations in the HCM 2000 methodology was estimated. Finally, the uncertainty in the average travel speed and percent time spent following was analyzed, and four approaches were considered to deal with uncertainty in the level of service.

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