Optimal performance of plastic pipes’ extrusion process using Min-Max model in fuzzy goal programming

2015 ◽  
Vol 231 (4) ◽  
pp. 888-898 ◽  
Author(s):  
Abbas Al-Refaie
Keyword(s):  
Goal Programming ◽  
Control Charts ◽  
Process Capability ◽  
Extrusion Process ◽  
Fuzzy Goal Programming ◽  
Statistical Control ◽  
Capability Index ◽  
Plastic Pipes ◽  
Fuzzy Goal ◽  
Process Factors

The main objective of this research is to optimize performance of plastic pipes’ extrusion process with two main quality responses, including pipe’s diameter and thickness, using Min-Max model in fuzzy goal programming. First, the variables control charts are constructed at initial factor settings of extrusion process, where the results reveal that the extrusion process is in statistical control. However, the actual capability index values for diameter and thickness are estimated 0.7094 and 0.7968, respectively. The process capability for a complete product, MCpk, is calculated as 0.752. These values indicate that the extrusion process is incapable. To improve process performance, the L18 array is utilized for experimental design with three 3-level process factors. Then, the Min-Max model is used to determine the combination of optimal factor settings. The estimated capability index values for diameter and thickness at the combination of optimal factor settings are estimated and found to be 1.504 and 1.879, respectively. The integrated process capability index, MCpk, is calculated as 1.681. Confirmation experiments should that the Min-Max model results in enhancing process capability for both responses. In conclusions, the Min-Max Model may provide valuable assistance to practitioners in optimizing performance while considering both product and process preferences.

Optimizing performance of oil filling processes using fuzzy goal programming

2017 ◽  
Vol 232 (3) ◽  
pp. 380-390 ◽  
Author(s):  
Abbas Al-Refaie ◽  
Yaser Abu Ghazaleh ◽  
Ming-Hsien Li
Keyword(s):  
Production Rate ◽  
Goal Programming ◽  
Control Charts ◽  
Programming Model ◽  
Fuzzy Goal Programming ◽  
Statistical Control ◽  
Quality Costs ◽  
Goal Programming Model ◽  
Fuzzy Goal ◽  
Filling Line

This research aims at improving the performance of the filling line machine using fuzzy goal programming. Two main quality responses including the number of defective products and the production rate of the filling machine are of main interest. Initially, the control charts for number of nonconforming and production rate, np and I-MR, respectively, are established and indicate that the process is in statistical control. However, the process is found incapable. The fuzzy goal programming model is adopted to identify the combination of optimal factor settings utilizing the Taguchi’s L16 array. The optimal factor settings are 5.6 s, 5.6 s, 6.4 s, 6.0 s, 75°, 75°, 1.9 cm, 2.5 cm, 1.0 s, 0.9 s, 5.8 s, and 0.11 s for timing nozzle # 1, timing nozzle # 2, timing nozzle # 3, timing nozzle # 4, weighing valve # 1, weighing valve # 2, crimping head # 1 height, crimping head # 2 height, crimping time # 1, crimping time # 2, crimping delay, and conveyer, respectively. Confirmation experiments are conducted at optimal factor settings. Results showed reduction in the number of defective cans and significant enhancement of the oil filling process capability. In conclusions, the fuzzy goal programming model is found to be an efficient technique in supporting the process engineers of oil filling line for obtaining significant yearly savings in quality costs and considerable productivity gains.

Disaster Risk Planning With Fuzzy Goal Programming

Risk Analysis ◽  
2021 ◽  
Author(s):  
Terry R. Rakes ◽  
Jason K. Deane ◽  
Loren P. Rees ◽  
David M. Goldberg
Keyword(s):  
Goal Programming ◽  
Disaster Risk ◽  
Fuzzy Goal Programming ◽  
Fuzzy Goal ◽  
Risk Planning

On Solving Multiobjective Transportation Problems with Fuzzy Random Supply and Demand Using Fuzzy Goal Programming

2017 ◽  
Vol 8 (3) ◽  
pp. 54-81 ◽  
Author(s):  
Animesh Biswas ◽  
Nilkanta Modak
Keyword(s):  
Goal Programming ◽  
Fuzzy Numbers ◽  
Optimal Allocation ◽  
Programming Model ◽  
Fuzzy Goal Programming ◽  
Chance Constrained Programming ◽  
Transportation Problems ◽  
Goal Programming Model ◽  
Fuzzy Goal ◽  
Fuzzy Random

In this article a fuzzy goal programming model is developed to solve multiobjective unbalanced transportation problems with fuzzy random parameters. In model formulation process the cost coefficients of the objectives are considered as fuzzy numbers and the supplies and demands are considered as fuzzy random variables with known fuzzy probability distribution from the view point of probabilistic as well as possibilistic uncertainties involved with the model. A fuzzy programming model is first constructed by applying chance constrained programming methodology in fuzzy environment. Then, the model is decomposed on the basis of the tolerance ranges of the fuzzy numbers associated with it. The individual optimal solution of each decomposed objectives is found in isolation to construct the membership goals of the objectives. Finally, priority based fuzzy goal programming technique is used to achieve the highest degree of each of the defined membership goals to the extent possible by minimizing the under deviational variables and thereby obtaining optimal allocation of products by using distance function in a cost minimizing decision making environment. An illustrative example is solved and compared with existing technique to explore the potentiality of the proposed methodology.

scholarly journals Shewhart's control charts and process capability ratio applied to a sewage treatment station

2014 ◽  
Vol 34 (4) ◽  
pp. 770-779 ◽  
Author(s):  
Fábio Orssatto ◽  
Marcio A. Vilas Boas ◽  
Ricardo Nagamine ◽  
Miguel A. Uribe-Opazo
Keyword(s):  
Control Charts ◽  
Suspended Solids ◽  
Sewage Treatment ◽  
Oxygen Demand ◽  
Process Capability ◽  
Total Suspended Solids ◽  
Statistical Control ◽  
Environmental Legislation ◽  
Shewhart Control Charts ◽  
Shewhart Control

The current study used statistical methods of quality control to evaluate the performance of a sewage treatment station. The concerned station is located in Cascavel city, Paraná State. The evaluated parameters were hydrogenionic potential, settleable solids, total suspended solids, chemical oxygen demand and biochemical oxygen demand in five days. Statistical analysis was performed through Shewhart control charts and process capability ratio. According to Shewhart charts, only the BOD(5.20) variable was under statistical control. Through capability ratios, we observed that except for pH the sewage treatment station is not capable to produce effluents under characteristics that fulfill specifications or standard launching required by environmental legislation.

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