Wimonmas Bamrungsetthapong¹, Pramote Charongrattanasakul^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2471-2495, 2024, DOI:10.32604/cmes.2023.031433

Abstract This study presents the design of a modified attributed control chart based on a double sampling (DS) np chart applied in combination with generalized multiple dependent state (GMDS) sampling to monitor the mean life of the product based on the time truncated life test employing the Weibull distribution. The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing. Three control limit levels are used: the warning control limit, inner control limit, and outer control limit. Together, they enhance the capability for variation detection. A genetic algorithm can be used… More >

Hassan Okasha^1,2, Mazen Nassar^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2219-2241, 2023, DOI:10.32604/cmes.2023.028783

Abstract In this paper, we introduce a new four-parameter version of the traditional Weibull distribution. It is able to provide seven shapes of hazard rate, including constant, decreasing, increasing, unimodal, bathtub, unimodal then bathtub, and bathtub then unimodal shapes. Some basic characteristics of the proposed model are studied, including moments, entropies, mean deviations and order statistics, and its parameters are estimated using the maximum likelihood approach. Based on the asymptotic properties of the estimators, the approximate confidence intervals are also taken into consideration in addition to the point estimators. We examine the effectiveness of the maximum likelihood estimators of the model’s… More >

Musaed Alrashidi^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 491-513, 2023, DOI:10.32604/csse.2023.038628

Abstract Statistical distributions are used to model wind speed, and the two-parameters Weibull distribution has proven its effectiveness at characterizing wind speed. Accurate estimation of Weibull parameters, the scale (c) and shape (k), is crucial in describing the actual wind speed data and evaluating the wind energy potential. Therefore, this study compares the most common conventional numerical (CN) estimation methods and the recent intelligent optimization algorithms (IOA) to show how precise estimation of c and k affects the wind energy resource assessments. In addition, this study conducts technical and economic feasibility studies for five sites in the northern part of Saudi… More >

Pramote Charongrattanasakul¹, Wimonmas Bamrungsetthapong^2,*, Poom Kumam³

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1631-1651, 2023, DOI:10.32604/csse.2023.036179

Abstract A novel adaptive multiple dependent state sampling plan (AMDSSP) was designed to inspect products from a continuous manufacturing process under the accelerated life test (ALT) using both double sampling plan (DSP) and multiple dependent state sampling plan (MDSSP) concepts. Under accelerated conditions, the lifetime of a product follows the Weibull distribution with a known shape parameter, while the scale parameter can be determined using the acceleration factor (AF). The Arrhenius model is used to estimate AF when the damaging process is temperature-sensitive. An economic design of the proposed sampling plan was also considered for the ALT. A genetic algorithm with… More >

Musaed Alrashidi^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1073-1088, 2023, DOI:10.32604/cmc.2023.036170

Abstract Harvesting the power coming from the wind provides a green and environmentally friendly approach to producing electricity. To facilitate the ongoing advancement in wind energy applications, deep knowledge about wind regime behavior is essential. Wind speed is typically characterized by a statistical distribution, and the two-parameters Weibull distribution has shown its ability to represent wind speeds worldwide. Estimation of Weibull parameters, namely scale and shape parameters, is vital to describe the observed wind speeds data accurately. Yet, it is still a challenging task. Several numerical estimation approaches have been used by researchers to obtain c and k. However, utilizing such… More >

Refah Alotaibi¹, Hassan Okasha^2,3, Mazen Nassar^2,4, Ahmed Elshahhat^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2065-2089, 2023, DOI:10.32604/cmes.2023.023408

Abstract This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique. We refer to the new model as modified alpha power transformed Weibull distribution. The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions, which are quite familiar in environmental investigations. Its hazard rate function can be decreasing, increasing, bathtub and upside-down then bathtub shaped. Diverse structural properties of the proposed model are acquired including quantile function, moments, entropies, order statistics, residual life and reversed failure… More >

Refah Alotaibi¹, Hassan Okasha^2,3, Hoda Rezk⁴, Mazen Nassar^2,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1255-1274, 2023, DOI:10.32604/cmes.2022.022623

Abstract The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility. This addition is beneficial in a variety of fields, including reliability, economics, engineering, biomedical science, biological research, environmental studies, and finance. For modeling real data, several expanded classes of distributions have been established. The modified alpha power transformed approach is used to implement the new model. The data matches the new inverse Weibull distribution better than the inverse Weibull distribution and several other competing models. It appears to be a distribution designed to… More >

Pramote Charongrattanasakul¹, Wimonmas Bamrungsetthapong^2,*, Poom Kumam³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4611-4626, 2022, DOI:10.32604/cmc.2022.030856

Abstract The design of a new adaptive version of the multiple dependent state (AMDS) sampling plan is presented based on the time truncated life test under the Weibull distribution. We achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans. A warning sign for acceptance number was proposed to increase the probability of current lot acceptance. The optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk. A simulation study was presented to support the proposed sampling plan. A comparison between the proposed… More >

Murad A. A. Almekhlafi¹, Fahd N. Al-Wesabi^2,3, Majdy M. Eltahir⁴, Anwer Mustafa Hilal⁵, Amin M. El-Kustaban⁶, Abdelwahed Motwakel⁵, Ishfaq Yaseen⁵, Manar Ahmed Hamza^5,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3113-3129, 2022, DOI:10.32604/cmc.2022.024355

Abstract Energy is an essential element for any civilized country's social and economic development, but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the ecosystem. The Republic of Yemen has very good potential to use renewable energy. Unfortunately, we find few studies on renewable wind energy in Yemen. Given the lack of a similar analysis for the coastal city, this research newly investigates wind energy's potential near the Almukalla area by analyzing wind characteristics. Thus, evaluation, model identification, determination of available energy density, computing the capacity factors for several wind turbines and… More >

Walid Aydi^1,3,*, Fuad S. Alduais^2,4

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4033-4050, 2022, DOI:10.32604/cmc.2022.023119

Abstract The Weibull distribution is regarded as among the finest in the family of failure distributions. One of the most commonly used parameters of the Weibull distribution (WD) is the ordinary least squares (OLS) technique, which is useful in reliability and lifetime modeling. In this study, we propose an approach based on the ordinary least squares and the multilayer perceptron (MLP) neural network called the OLSMLP that is based on the resilience of the OLS method. The MLP solves the problem of heteroscedasticity that distorts the estimation of the parameters of the WD due to the presence of outliers, and eases… More >