Optimizing performance of oil filling processes using fuzzy goal programming

Al–Refaie, Abbas; Ghazaleh, Yaser Abu; Li, Ming-Hsien

doi:10.1177/0954408917698847

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…The chart has a central line is in the mean values (CL) as well as the upper and lower levels of control (sometimes called the "natural part of the process"), which represents the threshold "unlikely" of the resulting process and they are drawn in three standard errors from the central line (UCL and LCL, respectively). At initial factor, settings have been explained by the ̅charts for averages disposable glasses' weight, height, crater diameter, and volume [11]. , ̅ , ̅…”

Section: A Control Chartsmentioning

confidence: 99%

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Optimizing and evaluating performance quality control of the production process of disposable essentials using approach vague goal programming

Gholizadeh

Tajdin

2019

Journal of Industrial and Production Engineering

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses' weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses' average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

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Section: A Control Chartsmentioning

confidence: 99%

“…achieving membership goals for goals is to maximize or minimize uncertainty in a search process. In this study, the objectives of fusion-based distance-based programming are defined as a "false and true membership function" supported by "vague collections" [11].…”

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confidence: 99%

Optimizing and evaluating performance quality control of the production process of disposable essentials using approach vague goal programming

Gholizadeh

Tajdin

2019

Journal of Industrial and Production Engineering

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“…Hence, improving the performance of plastic manufacturing processes has received considerable attention in research. 4,5 For example, Diraddo and Garciarejon 6 studied the parameters of an injection blow molding process to optimize the thickness distribution, degree of crystallinity, and permeability of plastic parts by using numerical modeling. Huang and Liao 7 investigated the diameter and thickness swells of the parison in the continuous extrusion blow molding of high-density polyethylene as a function of the processing parameters including the die temperature and flow rate.…”

Section: Introductionmentioning

confidence: 99%

Using mixed goal programming to optimize performance of extrusion process for multiple responses of irrigation pipes

Al–Refaie

Musallam

2018

Proceedings of the Institution of Mechanical Engineers, Part E:

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The performance of the polyethylene extrusion process used in the plastic industry was optimized using mixed goal programming. Four responses, the roll weight, production cycle time, distance between emitters, and thickness, are crucial. After a combination of initial factor settings was determined, individual and moving range control charts were established for each response. Two-phase optimization was implemented using L18 and L9 arrays for conducting experiments. A two-phase fuzzy goal programming model was formulated and employed to determine the combination of optimal factor settings, which was used to perform experiments. The results showed a significant reduction in the average production time from 13.0 to 11.316 min. Moreover, the average respective relative percentages of variability reduction for the roll weight, production cycle time, distance between emitters, and thickness were 48.547%, 49.048%, 47.174%, and 63.704%, respectively, and the corresponding estimated process capability indices for the combination of initial (optimal) factor settings were 0.202 (1.440), 0.330 (0.914), and 0.460 (1.456). Such improvement results in significant reduction in quality costs.

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A fuzzy goal programming-regression approach to optimize process performance of multiple responses under uncertainty

Al–Refaie

Domi

Abdullah

2018

International Journal of Management Science and Engineering Man

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Optimizing performance of oil filling processes using fuzzy goal programming

Cited by 3 publications

References 27 publications

Optimizing and evaluating performance quality control of the production process of disposable essentials using approach vague goal programming

Optimizing and evaluating performance quality control of the production process of disposable essentials using approach vague goal programming

Using mixed goal programming to optimize performance of extrusion process for multiple responses of irrigation pipes

A fuzzy goal programming-regression approach to optimize process performance of multiple responses under uncertainty

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