Angela Isabel dos Santos Dullius

Relationship between sustainable operations practices and performance: a meta-analysis

Purpose The purpose of this paper is to examine the relationship between sustainable operations practices (SOP) and performance. Design/methodology/approach This study was conducted through a systematic literature review followed by a meta-analysis of correlations. Findings In the results, 14 of the relationships examined showed a positive relationship and 12 the presence of moderators. The study findings indicate that contingency affects the relationship between SOPs and performance. Research limitations/implications The research presented in this paper is mainly limited to databases that were searched. Among the quantitative articles selected from the databases, many did not have the data needed to conduct the meta-analysis, which may have limited the results of this study. Practical implications Using the results of this study, practitioners can become aware of to the occurrence of moderating factors in the relationships, which can range from interference from other practices and variables to characteristics of the organization itself or the market in which organizations operate. Originality/value This study uses a multidimensional approach for both SOP and performance. This approach allowed a more complete and comprehensive result, showing how these SOPs influence the different categories of performance, expanding the understanding of the relationship between practices and performance.

Effect of Blood Contamination on The Push-Out Bond Strength of Calcium Silicate Cements

This study investigated the effect of blood-contamination on the push-out bond strength of BiodentineTM (BD) and MTA Angelus® (MTA-A) to root dentin over time. Twenty-five teeth were sectioned horizontally to obtain 120 root slices. The lumens were filled with MTA-A or BD: 60 for each cement (30 uncontaminated and 30 blood contaminated). Push out bond strength to dentin was assessed at 24 h (n=10), 7 days (n=10) and 28 days (n=10). Failure modes were classified as: cohesive, adhesive or mixed failure. Two-way ANOVA was used to investigate the interaction between blood contamination vs. hydration period. Mann Whitney test compared different materials in each period, and it also compared the contaminated versus uncontaminated material for each period. Friedman, followed by Dunn`s test, compared periods of hydration for each material, regardless of blood contamination. Failure modes were reported descriptively. The interaction hydration period vs. blood contamination was highly significant for MTA-A (P=0.001) and it was not significant for BD (P=0.474). There were no differences between bond strength of uncontaminated and contaminated BD in any of the periods. Bond strength of uncontaminated MTA-A increased at each time of hydration; but it remained stable over time for blood-contaminated samples. BD had higher bond strength than MTA-A in all periods of hydration. Cohesive failure predominated. Only for MTA-A, the over time bond strength to dentin was affected by blood contamination.

Measure nicotine dependence by the fagerström test for nicotine dependence

Objective To assess the level of nicotine dependence of smokers in a university dental clinic in southern Brazil using the Fagerström Test for Nicotine Dependence and identify those who would like to quit smoking. Methods A cross-sectional study was carried out with 93 Dental School patients, who underwent a face-to-face interview with four researchers. Data was analysed using descriptive statistics and the Chi-Square test with a significance level of 5%. Results The mean age of the smokers was 47.90 and most had had up to eight years of schooling, and had a family income of less than 1,000 Brazilian Reais. The degree of nicotine dependence was classified, by the mean, 4.45 ± 2.53 points (±SD). There was a significant correlation between nicotine dependence and the number of cigarettes smoked per day. Conclusion The 1% sodium hypochlorite solution caused least damage to the denture structure, not leading to decrease of the superficial microhardness. Indexing terms: Smoking. Smoking cessation Tobacco.

INTERNATIONAL COLUMN: Association of demographic, economic and clinical variables in daily activities and symptoms presented by patients in cancer treatment

Objective To investigate the association between demographic, economic and clinical variables, cancer symptoms, and daily life interference in patients receiving cancer treatment in Brazil. Methods In this cross-sectional study, 268 patients were assessed. A questionnaire was used to collect data on demographic, economic and clinical variables, and the M.D. Anderson Symptom Inventory was used to assess cancer symptoms. Data were analyzed using bivariate and multivariate descriptive statistics. Findings The following variables were associated with higher symptom scores: female sex (prevalence ratio [PR]=1.28; 95% confidence interval [95% CI] 1.06-1.53), illiteracy or ≤ 9 years of formal education (PR=1.40; 95% CI 1.08-1.82), clinical equipment or situations that requiring nursing care (PR=1.23; 95% CI 1.03-1.46), and family history of cancer (PR=1.23; 95% CI 1.04-1.45). Daily life interference was associated with female sex (PR=1.40; 95% CI 1.12-1.75), secondary tumour (PR=1.42; 95% CI 1.16-1.74) and radiotherapy (PR=1.24; 95% CI 1.01-1.51). Conclusion Management of cancer patients requires multidisciplinary knowledge, taking into consideration all the subjective dimensions of the patients. Knowing the profile of patients most strongly affected by symptoms will help them face the limitations and consequences of the disease and its treatment.

An algorithm for quality control charts for autocorrelated data

Currently considerable attention has been given to the effect of data correlation on statistical process control (SPC). Use of traditional SPC methods when observations are correlated often leads to misleading conclusions as to whether or not the process is under control. The objetive of this paper is to develop an algorithm to adjust a model ARMA(p,q), for calculate the run length distribution (RLD), the average run length (ARL), and the standard deviation of the run length (SRL), for residual control charts X(ind) and MR used to monitor autocorrelated processes. The algorithm was used for analysis of real data. We conclude that for negative first-order autocorrelation, the residuals chart is performing better than the Shewhart chart for independent observations.

Kalman Filter an application in process control

In this paper, we present in a systematic way an approach to modelling of Kalman Filter in the Statistical Process Control, formulated in state space. The procedure based on the Kalman filter was superior to the classical procedures like Shewhart and CUSUM control charts.

Study of the layout of a steel manufacturing industry

A layout survey is required to improve the production flow of a steel company. A reliable layout provides improvements in productivity and savings because it states a better distribution for machinery, appliances and human resources. In this paper the layout of a steel company is analyzed. It is found that the production flow does not match with the physical positioning of the machinery that designs the production line of the company. Following this analysis, a reformulation of the layout is proposed to aim the reduction of processing appliance transportation time, leading an improvement in the capacity of production and a reduction in setups times. Pursuing the implementation of the new layout, a search was developed to compare the outputs before and after the redefinition of the layout. The result highlights improvements as shortening processing appliance transportation time, broadening production programming performance and lessening setup times in the lines.

Control charts for monitoring autocorrelated processes based on Neural Networks model

Statistical process control can have different objectives and can be done in different forms (Hawkins, et al, 2003). Currently, considerable attention has been given to the effect of data correlation on the statistical process control (SPC). The use of traditional SPC methods when observations are correlated often leads to misleading conclusions as to whether or not the process is under control. This paper presents the construction of residual based control charts, obtained from Neural Network model, to monitor the mean and dispersion in autocorrelated productive processes. One application with real data and a performance comparison of the residual control charts obtained from the Artificial Neural Network model with that of traditional control charts X(bar) and R presented. It is established that the former procedure is more efficient in detecting changes in the mean and dispersion of the process than the latter.