Performance of merging lines with uneven buffer capacity allocation: the effects of unreliability under different inventory-related costs

This simulation study investigates whether machine efficiency, mean time to failure (MTTF) and mean time to repair (MTTR) significantly affect the performance of uneven buffer capacity allocation patterns for merging lines. Also studied is the trade-off between increasing throughput via bigger buffers and their associated inventory-related costs, since previous studies have shown that higher overall buffer capacity and higher average inventory content result in higher throughput. Results suggest that an ascending buffer allocation pattern (concentrating buffer capacity towards the end of the line) produces higher throughput in shorter, more unreliable lines; whereas the balanced pattern shows better performance in longer, more reliable lines. Increasing average buffer capacity per station and/or having higher average buffer content was found to be more cost-effective in lines with lower machine inefficiency, shorter MTTF and MTTR, and longer lines. Results differed between reliable and unreliable lines since reliable lines were particularly penalised by buffer capacity investiment/maintenance costs due to a relatively low increase in throughput resulting from the addition of extra buffer capacity

Serial production line performance under random variation:Dealing with the ‘Law of Variability’

Many Queueing Theory and Production Management studies have investigated specific effects of variability on the performance of serial lines since variability has a significant impact on performance. To date, there has been no single summary source of the most relevant research results concerned with variability, particularly as they relate to the need to better understand the ‘Law of Variability’. This paper fills this gap and provides readers the foundational knowledge needed to develop intuition and insights on the complexities of stochastic simple serial lines, and serves as a guide to better understand and manage the effects of variability and design factors related to improving serial production line performance, i.e. throughput, inter-departure time and flow time, under random variation

The impact of unequal processing time variability on reliable and unreliable merging line performance

Research on merging lines is expanding as their use grows significantly in the contexts of remanufacturing, reverse logistics and developing economies. This article is the first to study the behavior of unpaced, reliable, and unreliable merging assembly lines that are deliberately unbalanced with respect to their coefficients of variation (CV). Conducting a series of simulation runs with varying line lengths, buffer storage capacities and unbalanced CV patterns delivers intriguing results. For both reliable and unreliable lines, the best pattern for generating higher throughput is found to be a balanced configuration (equal CVs along both parallel lines), except for unreliable lines with a station buffer capacity of six. In that case, the highest throughput results from the descending configuration, i.e. concentrating the variable stations close to the beginning of both parallel lines and the steady stations towards the end of the line. Ordering from the least to most steady station also provides the best average buffer level. By exploring the experimental Pareto Frontier, this study shows the combined performance of unbalanced CV patterns for throughput and average buffer level. Study results suggest that caution should be exercised when assuming equivalent behavior from reliable and unreliable lines, or single serial lines and merging lines, since the relative throughput performance of some CV patterns changed between the different configurations

Studying the effects of skewness of inter-arrival and service times on the probability distribution of waiting times

Previous studies have shown that the mean queue length of a GI/G/1 system is significantly influenced by the skewness of inter-arrival times, but not by the skewness of service times. These results are limited because all the distributions considered in previous studies were positively skewed. To address this limitation, this paper investigates the effects of the skewness of inter-arrival and service times on the probability distribution of waiting times, when a negatively skewed distribution is used to model inter-arrival and service times. Subsequent to a series of experiments on a GI/G/1 queue using discrete-event simulation, results have shown that the lowest mean waiting time and the lowest variance of waiting times can be attained with a combination of positive inter-arrival skewness and negative service skewness. Results also show an interesting effect of the skewness of service times in the probability of no-delay in environments with a higher utilization factor

Studying the Effects of the Skewness of Inter-Arrival and Service Times on the Probability Distribution of Waiting Times

Previous studies have shown that the mean queue length of a GI/G/1 system is significantly influenced by the skewness of inter-arrival times, but not by the skewness of service times. These results are limited because all the distributions considered in previous studies were positively skewed. To address this limitation, this paper investigates the effects of the skewness of inter-arrival and service times on the probability distribution of waiting times, when a negatively skewed distribution is used to model inter-arrival and service times. Subsequent to a series of experiments on a GI/G/1 queue using discrete-event simulation, results have shown that the lowest mean waiting time and the lowest variance of waiting times can be attained with a combination of positive inter-arrival skewness and negative service skewness. Results also show an interesting effect of the skewness of service times in the probability of no-delay in environments with a higher utilization factor

Parameter Estimation Based on Double Ranked Set Samples with Applications to Weibull Distribution

In this paper, the likelihood function for parameter estimation based on double ranked set sampling (DRSS) schemes is introduced. The proposed likelihood function is used for the estimation of the Weibull distribution parameters. The maximum likelihood estimators (MLEs) are investigated and compared to the corresponding ones based on simple random sampling (SRS) and ranked set sampling (RSS) schemes. A Monte Carlo simulation is conducted and the absolute relative biases, mean square errors, and efficiencies are compared for the different schemes. It is found that, the MLEs based on DRSS is more efficient than MLE using SRS and RSS for estimating the two parameters of the Weibull distribution (WD)

Diethyl 3,4-dimethylthieno[2,3-it b]thiophene-2,5-dicarboxylate

In the title compound, C14H16O4S2, the thieno[2,3-b]thiophene ring systems are planar [maximum deviation = 0.008 (2) Å]. The molecular conformation is stabilized by intramolecular C-HO hydrogen bonds, while the crystal packing is stabilized by C-HO, C-H and - stacking [centroid-centroid distance = 3.6605 (14) Å] interactions, which lead to supramolecular layers in the ab plane

Effects of administration of 10 nm or 50 nm gold nanoparticles (AuNPs) on blood profile, liver and kidney functions in male albino rats

This work aimed to investigate the effect of acute and chronic administration of gold nanoparticles (GNPs) on liver and kidney functions, blood glucose concentration, lipid profile, and haematological parameters in male albino rats. Two experiments were conducted. In acute study: Fifty-four adult mature male rats were randomly assigned into three equal groups (18 per group). Group 1 (control group): in which rats were received intramuscular (i.m) injection of 1 ml normal saline 0.9%. Group 2 (50 nm GNPs group): rats were i.m. injected with a single dose of 75 µg 50 nm GNPs/kg body weight (bwt). In Group 3 (10 nm GNPs group): rats were i.m. injected with a single dose of 75 µg 10 nm GNPs/kg bwt. In chronic study: Eighteen adult male rats were randomly divided into three equal groups (6 per group). Group І (control): rats were intramuscular (i.m) repeatedly injected with 1 ml normal saline 0.9% once/week 5 for weeks. Group 2 (50 nm GNPs): rats were i.m. injected with once/week with a dose of 75 µg 50 nm GNPs/kg bwt) for 5 weeks. In Group 3 (10 nm GNPs): male rats were i.m. injected with once/week with a dose of 75 µg 50 nm GNPs/kg bwt for 5 weeks, followed by 3 weeks washout period for all groups. Blood was collected at 3, 7, and 60 days in acute experiment, while, they were collected only before and after 2 months in chronic experiment. Acute and chronic administration of GNPs (10 or 50 nm size) in male albino rats induced no significant alterations for liver and kidney functions, lipid profile parameters and different haematological parameters at days 3 and 60 of the study. However, on day-7 post-treatment, GNPs-treated rats showed significantly (P <0.05) higher serum ALT, AST, ALP, urea, creatinine, glucose, and different lipid profile and decreased HDL level. Chronic administration of 10 nm or 50 nm GNPs significantly (P <0.05) decreased serum glucose levels. In conclusion acute or chronic administration of 10 nm or 50 nm GNPs could alter the liver, kidney functions and blood profile on day 7 post-treatment, however, these values returned to the normal levels on day 60 post- injection. Also, the chronic administration of GNPs induced a hypoglycemic effect in male albino rats

Portal Venous Pressure as a Predictor of Mortality in Child’s A Cirrhotic Patients Undergoing Elective Surgery: A Prospective Study

BACKGROUND: Recently, portal venous pressure (PVP) exhibited high sensitivity and specificity in anticipating death in cirrhotic cases submitted to emergency operations. AIM: The current prospective work aimed to evaluate the utility of PVP in predicting 1st month post-operative death in Child’s A cirrhotic cases who underwent elective operations. METHODS: One-hundred and twenty cirrhotic cases that were planned to undergo elective surgery were enrolled in the current prospective work. The intraoperative (I.O) PVP and central venous pressure (CVP) were measured. The statistical analysis was performed using the SPSS version 22.0. The receiver operative curve was plotted to measure the predictive value of PVP. Multivariate analysis was done using logistic regression method for the significant variables impacting mortality on univariate analysis. RESULTS: Twenty-nine patients died in the current work. Patients who survived had statistically considerably lower PVP than patients who died (8.2 ± 1.5 vs. 12.5 ± 1.6 mmHg, respectively, p < 0.001). Similarly, patients who died had significantly higher I.O CVP (p < 0.001), body mass index (p < 0.001), and were more likely to have model for end-stage liver disease score between 9 and 16 (p = 0.003). At a cutoff value ≥10.5 mmHg, the PVP had a sensitivity of 82.8% and specificity of 93.4% for the prediction of mortality. The logistic regression analysis showed that only PVP (odds ratio [OR] =3.1, 95% confidence interval [CI] 1.25–7.5) and CVP (OR = 2.8, 95% CI 1.2–6.5) were the only independent predictors of mortality. CONCLUSION: PVP is a significant predictor of death in Child’s A cirrhotic cases submitted to elective operations