Lean Six Sigma in a Manufacturing Lead Time Improvement Project

The objective of this research is to demonstrate the use of Lean Six Sigma methodology in a manufacturing lead time improvement project. Moreover, the goal is to develop working solutions for the target company to improve its manufacturing lead time. The theoretical background is achieved through exploring the literature of Six Sigma, Lean and Lean Six Sigma. The development will be done in collaboration with the related stakeholders, by following the Lean Six Sigma improvement process DMAIC and by analyzing the process data from the target company. The focus of this research is in demonstrating how to use Lean Six Sigma improvement process DMAIC in practice, rather than in comparing Lean Six Sigma to other improvement methodologies. In order to validate the manufacturing system’s current state, improvement potential and solutions, statistical tools such as linear regression analysis were used. This ensured that all the decisions were as heavily based on actual data as possible. As a result of this research, a set of solutions were developed and implemented in the target company. These solutions included batch size reduction, bottleneck shift, first-in first-out queuing and shifting a data entry task from production planners to line workers. With the use of these solutions, the target company was able to reduce its manufacturing lead time by over one third.

Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone

Bioanalytical data from a bioequivalence study were used to develop limited-sampling strategy (LSS) models for estimating the area under the plasma concentration versus time curve (AUC) and the peak plasma concentration (Cmax) of 4-methylaminoantipyrine (MAA), an active metabolite of dipyrone. Twelve healthy adult male volunteers received single 600 mg oral doses of dipyrone in two formulations at a 7-day interval in a randomized, crossover protocol. Plasma concentrations of MAA (N = 336), measured by HPLC, were used to develop LSS models. Linear regression analysis and a "jack-knife" validation procedure revealed that the AUC0-¥ and the Cmax of MAA can be accurately predicted (R²>0.95, bias <1.5%, precision between 3.1 and 8.3%) by LSS models based on two sampling times. Validation tests indicate that the most informative 2-point LSS models developed for one formulation provide good estimates (R²>0.85) of the AUC0-¥ or Cmax for the other formulation. LSS models based on three sampling points (1.5, 4 and 24 h), but using different coefficients for AUC0-¥ and Cmax, predicted the individual values of both parameters for the enrolled volunteers (R²>0.88, bias = -0.65 and -0.37%, precision = 4.3 and 7.4%) as well as for plasma concentration data sets generated by simulation (R²>0.88, bias = -1.9 and 8.5%, precision = 5.2 and 8.7%). Bioequivalence assessment of the dipyrone formulations based on the 90% confidence interval of log-transformed AUC0-¥ and Cmax provided similar results when either the best-estimated or the LSS-derived metrics were used.

Noninvasive classification of liver disease in asymptomatic and oligosymptomatic male alcoholics

The predominant type of liver alteration in asymptomatic or oligosymptomatic chronic male alcoholics (N = 169) admitted to a psychiatric hospital for detoxification was classified by two independent methods: liver palpation and multiple quadratic discriminant analysis (QDA), the latter applied to two parameters reported by the patient (duration of alcoholism and daily amount ingested) and to the data obtained from eight biochemical blood determinations (total bilirubin, alkaline phosphatase, glycemia, potassium, aspartate aminotransferase, albumin, globulin, and sodium). All 11 soft and sensitive, and 13 firm and sensitive livers formed fully concordant groups as determined by QDA. Among the 22 soft and not sensitive livers, 95% were concordant by QDA grouping. Concordance rates were low (55%) in the 73 firm and not sensitive livers, and intermediate (76%) in the 50 not palpable livers. Prediction of the liver palpation characteristics by QDA was 95% correct for the firm and not sensitive livers and moderate for the other groups. On a preliminary basis, the variables considered to be most informative by QDA were the two anamnestic data and bilirubin levels, followed by alkaline phosphatase, glycemia and potassium, and then by aspartate aminotransferase and albumin. We conclude that, when biopsies would be too costly or potentially injurious to the patients to varying extents, clinical data could be considered valid to guide patient care, at least in the three groups (soft, not sensitive; soft, sensitive; firm, sensitive livers) in which the two noninvasive procedures were highly concordant in the present study.

Predicting bankruptcy of Finnish limited liability companies from historical financial statements

This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.

Serum cytokine profile in the subclinical form of visceral leishmaniasis

The factors determining the development or not of visceral leishmaniasis (VL) have not been completely identified, but a Leishmania-specific cellular immune response seems to play a fundamental role in the final control of infection. Few studies are available regarding the production of cytokines in the subclinical form of VL, with only the production of IFN-g and TNF-a known. The aim of the present study was to identify immunological markers for the oligosymptomatic or subclinical form of VL. A prospective cohort study was conducted on 784 children aged 0 to 5 years from an endemic area in the State of Maranhão, Brazil, between January 1998 and December 2001. During 30 consecutive months of follow-up, 33 children developed the oligosymptomatic form of the disease and 12 the acute form. During the clinical manifestations, serum cytokine levels were determined in 27 oligosymptomatic children and in nine patients with the acute form using a quantitative sandwich enzyme immunoassay. In the subclinical form of VL, variable levels of IL-2 were detected in 52.3% of the children, IL-12 in 85.2%, IFN-g in 48.1%, IL-10 in 88.9%, and TNF-a in 100.0%, with the last two cytokines showing significantly lower levels than in the acute form. IL-4 was not detected in oligosymptomatic individuals. Multiple discriminant analysis used to determine the profile or combination of cytokines predominating in the subclinical form revealed both a Leishmania resistance (Th1) and susceptibility (Th2) profile. The detection of both Th1 and Th2 cytokine profiles explains the self-limited evolution accompanied by the discrete alterations observed for the subclinical form of VL.

Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

Atherosclerosis in aged mice over-expressing the reverse cholesterol transport genes

We determined whether over-expression of one of the three genes involved in reverse cholesterol transport, apolipoprotein (apo) AI, lecithin-cholesterol acyl transferase (LCAT) and cholesteryl ester transfer protein (CETP), or of their combinations influenced the development of diet-induced atherosclerosis. Eight genotypic groups of mice were studied (AI, LCAT, CETP, LCAT/AI, CETP/AI, LCAT/CETP, LCAT/AI/CETP, and non-transgenic) after four months on an atherogenic diet. The extent of atherosclerosis was assessed by morphometric analysis of lipid-stained areas in the aortic roots. The relative influence (R²) of genotype, sex, total cholesterol, and its main sub-fraction levels on atherosclerotic lesion size was determined by multiple linear regression analysis. Whereas apo AI (R² = 0.22, P < 0.001) and CETP (R² = 0.13, P < 0.01) expression reduced lesion size, the LCAT (R² = 0.16, P < 0.005) and LCAT/AI (R² = 0.13, P < 0.003) genotypes had the opposite effect. Logistic regression analysis revealed that the risk of developing atherosclerotic lesions greater than the 50th percentile was 4.3-fold lower for the apo AI transgenic mice than for non-transgenic mice, and was 3.0-fold lower for male than for female mice. These results show that apo AI overexpression decreased the risk of developing large atherosclerotic lesions but was not sufficient to reduce the atherogenic effect of LCAT when both transgenes were co-expressed. On the other hand, CETP expression was sufficient to eliminate the deleterious effect of LCAT and LCAT/AI overexpression. Therefore, increasing each step of the reverse cholesterol transport per se does not necessarily imply protection against atherosclerosis while CETP expression can change specific athero genic scenarios.

Validation of the Beck Depression Inventory for a Portuguese-speaking Chinese community in Brazil

The objective of the present study was to investigate the psychometric properties and cross-cultural validity of the Beck Depression Inventory (BDI) among ethnic Chinese living in the city of São Paulo, Brazil. The study was conducted on 208 community individuals. Reliability and discriminant analysis were used to test the psychometric properties and validity of the BDI. Principal component analysis was performed to assess the BDI's factor structure for the total sample and by gender. The mean BDI score was lower (6.74, SD = 5.98) than observed in Western counterparts and showed no gender difference, good internal consistency (Cronbach's alpha 0.82), and high discrimination of depressive symptoms (75-100%). Factor analysis extracted two factors for the total sample and each gender: cognitive-affective dimension and somatic dimension. We conclude that depressive symptoms can be reliably assessed by the BDI in the Brazilian Chinese population, with a validity comparable to that for international studies. Indeed, cultural and measurement biases might have influenced the response of Chinese subjects.

Gender-related pathways for behavior problems in the offspring of alcoholic fathers

The objective of the present study was to examine gender differences in the influence of paternal alcoholism on children's social-emotional development and to determine whether paternal alcoholism is associated with a greater number of externalizing symptoms in the male offspring. From the Mannheim Study of Risk Children, an ongoing longitudinal study of a high-risk population, the developmental data of 219 children [193 (95 boys and 98 girls) of non-alcoholic fathers, non-COAs, and 26 (14 boys, 12 girls) of alcoholic fathers, COAs] were analyzed from birth to the age of 11 years. Paternal alcoholism was defined according to the ICD-10 categories of alcohol dependence and harmful use. Socio-demographic data, cognitive development, number and severity of behavior problems, and gender-related differences in the rates of externalizing and internalizing symptoms were assessed using standardized instruments (IQ tests, Child Behavior Checklist questionnaire and diagnostic interviews). The general linear model analysis revealed a significant overall effect of paternal alcoholism on the number of child psychiatric problems (F = 21.872, d.f. = 1.217, P < 0.001). Beginning at age 2, significantly higher numbers of externalizing symptoms were observed among COAs. In female COAs, a pattern similar to that of the male COAs emerged, with the predominance of delinquent and aggressive behavior. Unlike male COAs, females showed an increase of internalizing symptoms up to age 11 years. Of these, somatic complaints revealed the strongest discriminating effect in 11-year-old females. Children of alcoholic fathers are at high risk for psychopathology. Gender-related differences seem to exist and may contribute to different phenotypes during development from early childhood to adolescence.

Rats with high left ventricular end-diastolic pressure can be identified by Doppler echocardiography one week after myocardial infarction

The severity of left ventricular (LV) dysfunction in rats with myocardial infarction (MI) varies widely. Because homogeneity in baseline parameters is essential for experimental investigations, a study was conducted to establish whether Doppler echocardiography (DE) could accurately identify animals with high LV end-diastolic pressure as a marker of LV dysfunction soon after MI. Direct measurements of LV end-diastolic pressure were made and DE was performed simultaneously 1 week after surgically induced MI (N = 16) or sham-operation (N = 17) in female Wistar rats (200 to 250 g). The ratio of peak early (E) to late (A) diastolic LV filling velocities and the ratio of E velocity to peak early (Em) diastolic myocardial velocity were the best predictors of high LV end-diastolic pressure (>12 mmHg) soon after MI. Cut-off values of 1.77 for the E/A ratio (P = 0.001) identified rats with elevated LV end-diastolic pressure with 90% sensitivity and 80% specificity. Cut-off values of 20.4 for the E/Em ratio (P = 0.0001) identified rats with elevated LV end-diastolic pressure with 81.8% sensitivity and 80% specificity. Moreover, E/A and E/Em ratios were the only echocardiographic parameters independently associated with LV end-diastolic pressure in multiple linear regression analysis. Therefore, DE identifies rats with high LV end-diastolic pressure soon after MI. These findings have implications for using serial DE in animal selection and in the assessment of their response to experimental therapies.

HFE gene mutations and iron status of Brazilian blood donors

Mutations of the HFE and TFR2 genes have been associated with iron overload. HFE and TFR2 mutations were assessed in blood donors, and the relationship with iron status was evaluated. Subjects (N = 542) were recruited at the Hemocentro da Santa Casa de São Paulo, São Paulo, Brazil. Iron status was not influenced by HFE mutations in women and was independent of blood donation frequency. In contrast, men carrying the HFE 282CY genotype had lower total iron-binding capacity (TIBC) than HFE 282CC genotype carriers. Men who donated blood for the first time and were carriers of the HFE 282CY genotype had higher transferrin saturation values and lower TIBC concentrations than those with the homozygous wild genotype for the HFE C282Y mutation. Moreover, in this group of blood donors, carriers of HFE 63DD plus 63HD genotypes had higher serum ferritin values than those with the homozygous wild genotype for HFE H63D mutation. Multiple linear regression analysis showed that HFE 282CY leads to a 17.21% increase (P = 0.018) and a 83.65% decrease (P = 0.007) in transferrin saturation and TIBC, respectively. In addition, serum ferritin is influenced by age (3.91%, P = 0.001) and the HFE 63HD plus DD genotype (55.84%, P = 0.021). In conclusion, the HFE 282Y and 65C alleles were rare, while the HFE 63D allele was frequent in Brazilian blood donors. The HFE C282Y and H63D mutations were associated with alterations in iron status in blood donors in a gender-dependent manner.

Reproducibility of heart rate variability parameters measured in healthy subjects at rest and after a postural change maneuver

Heart rate variability (HRV) provides important information about cardiac autonomic modulation. Since it is a noninvasive and inexpensive method, HRV has been used to evaluate several parameters of cardiovascular health. However, the internal reproducibility of this method has been challenged in some studies. Our aim was to determine the intra-individual reproducibility of HRV parameters in short-term recordings obtained in supine and orthostatic positions. Electrocardiographic (ECG) recordings were obtained from 30 healthy subjects (20-49 years, 14 men) using a digital apparatus (sampling ratio = 250 Hz). ECG was recorded for 10 min in the supine position and for 10 min in the orthostatic position. The procedure was repeated 2-3 h later. Time and frequency domain analyses were performed. Frequency domain included low (LF, 0.04-0.15 Hz) and high frequency (HF, 0.15-0.4 Hz) bands. Power spectral analysis was performed by the autoregressive method and model order was set at 16. Intra-subject agreement was assessed by linear regression analysis, test of difference in variances and limits of agreement. Most HRV measures (pNN50, RMSSD, LF, HF, and LF/HF ratio) were reproducible independent of body position. Better correlation indexes (r > 0.6) were obtained in the orthostatic position. Bland-Altman plots revealed that most values were inside the agreement limits, indicating concordance between measures. Only SDNN and NNv in the supine position were not reproducible. Our results showed reproducibility of HRV parameters when recorded in the same individual with a short time between two exams. The increased sympathetic activity occurring in the orthostatic position probably facilitates reproducibility of the HRV indexes.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Serum metabolic profiling of human gastric cancer based on gas chromatography/mass spectrometry

Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.

Morphometric evaluation of nitric oxide synthase isoforms and their cytokine regulators predict pulmonary dysfunction and survival in systemic sclerosis

Because histopathological changes in the lungs of patients with systemic sclerosis (SSc) are consistent with alveolar and vessel cell damage, we presume that this interaction can be characterized by analyzing the expression of proteins regulating nitric oxide (NO) and plasminogen activator inhibitor-1 (PAI-1) synthesis. To validate the importance of alveolar-vascular interactions and to explore the quantitative relationship between these factors and other clinical data, we studied these markers in 23 cases of SSc nonspecific interstitial pneumonia (SSc-NSIP). We used immunohistochemistry and morphometry to evaluate the amount of cells in alveolar septa and vessels staining for NO synthase (NOS) and PAI-1, and the outcomes of our study were cellular and fibrotic NSIP, pulmonary function tests, and survival time until death. General linear model analysis demonstrated that staining for septal inducible NOS (iNOS) related significantly to staining of septal cells for interleukin (IL)-4 and to septal IL-13. In univariate analysis, higher levels of septal and vascular cells staining for iNOS were associated with a smaller percentage of septal and vascular cells expressing fibroblast growth factor and myofibroblast proliferation, respectively. Multivariate Cox model analysis demonstrated that, after controlling for SSc-NSIP histological patterns, just three variables were significantly associated with survival time: septal iNOS (P=0.04), septal IL-13 (P=0.03), and septal basic fibroblast growth factor (bFGF; P=0.02). Augmented NOS, IL-13, and bFGF in SSc-NSIP histological patterns suggest a possible functional role for iNOS in SSc. In addition, the extent of iNOS, PAI-1, and IL-4 staining in alveolar septa and vessels provides a possible independent diagnostic measure for the degree of pulmonary dysfunction and fibrosis with an impact on the survival of patients with SSc.