Jahar Lal Bhowmik

Experimental Investigations of Process Parameters Influence on Rheological Behavior and Dynamic Mechanical Properties of FDM Manufactured Parts

Fused deposition modeling (FDM) has gained popularity in industry because of its ability to manufacture complex parts. But when it comes to the manufacturing of functional products, the advantages of FDM are not so distinct due to the high number of intervening parameters and complex optimal settings setup. This paper investigates the influence of process parameters on the rheological and dynamic mechanical properties of FDM-manufactured parts. In this study, an attempt has been made to establish an empirical relationship between the FDM input parameters and the properties involved using IV-optimal response surface methodology and statistical analysis. Further, optimized process parameters were established to maximize the rheological and dynamic mechanical properties through the graphical optimization. The optimization results show that the parameters with the most significant effect on the rheological and dynamic mechanical properties are the layer thickness, the air gap, the road width, and the number of contours. The results also show that by taking into consideration the number of contours, the functionality of manufactured part is improved significantly.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Are Urinary Porphyrins a Valid Diagnostic Biomarker of Autism Spectrum Disorder

A fundamental challenge to the timely diagnosis of Autism Spectrum Disorder (ASD) is the reliance on the observation of a set of aberrant behavior. Consequently, the diagnostic process requires that the child reach an age where the behaviors would typically be exhibited. The identification of a reliable biological marker (biomarker) could be of considerable benefit to the diagnostic process. As a diagnostic biomarker, porphyrins present an attractive prospect as previous studies have reported consistent findings of children with ASD showing significant elevations in porphyrin levels in contrast to controls. Furthermore, there is some evidence that ASD severity may be associated with porphyrins, which would be a valuable characteristic of any ASD biomarker. Importantly, for practical use, porphyrins can be tested non‐invasively via a sample of urine. The present study sought to investigate whether porphyrin profiles can reliably be used to (a) differentiate ASD cases from healthy controls; and (b) predict ASD severity. The study compared the porphyrin levels of three groups of children aged 2–6 years: Group 1—children diagnosed with ASD (n = 70); Group 2—healthy, normally developing siblings of children diagnosed with ASD (n = 36); and Group 3—healthy, normally developing children with no known blood relative diagnosed with ASD (n = 54). The results of logistic regression analyses failed to find support for the hypotheses that porphyrin levels could be used as a valid tool to detect ASD cases or predict severity. Autism Res 2014, 7: 535–542.

Factors Associated with Disability in Rural Bangladesh: Bangladesh Population-Based Diabetes and Eye Study (BPDES)

Background To assess factors associated with disability in a rural district of Bangladesh. Methods Using a population-based systematic sampling technique, data were collected from 3104 adults aged ≥ 30 years from the Banshgram union of Narail district. Data collected included an interviewer administered questionnaire to report physical disabilities including impairment that prevents engagement with paid work, visual, hearing, and mobility as well as mental disabilities. Socio-demographic and anthropometric factors including educational attainment and body mass index, as well as clinical factors such as blood pressure, and fasting blood glucose were also collected. Binary and multinomial logistic regression techniques were used to explore the association of various socio-demographic and clinical factors with disability. Results The mean (SD), minimum and maximum ages of the participants were 51 (12), 30 and 89 years. Of total participants, 65% were female. The prevalence of disability varied from 29.1% for visual impairment (highest) to 16.5% for hearing, 14.7% for movement difficulties and 1.6% (lowest) for any other disability that prevented engagement with paid work. Overall, the prevalence of a single disability was 28.6% and that of two or more disabilities was 14.7%. Older age, gender (female), lower socio-economic status (SES), and hypertension were associated with a higher prevalence of most of the disability components. The prevalence of hearing problems (24.5% vs. 13.3%, p<0.001) and movement difficulties (24.9% vs. 13.0%, p<0.001) was significantly higher among lower-income participants than their higher-income counterparts after controlling for age. Prevalence of visual impairment (54.6% vs. 9.2%, p<0.001), hearing (32.2% vs. 6.7%, p<0.001) and movement difficulties (29.2% vs. 5.5%, p<0.001) were significantly higher in people of aged 60 years or older than those aged 30–34 years. After multivariate adjustment, the prevalence of single disability (prevalence risk ratio [PRR] 1.25, 95% CI: 1.09–1.42, p<0.001), and multiple disabilities (PRR 1.41, 95% CI 1.14–1.73, p<0.001) was higher among females than males. The prevalence of single disability and multiple disabilities was respectively 21% (PRR 1.21, 95% CI: 1.02–1.42, p<0.001) and 88% (PRR 1.88, 95% CI: 1.38–2.54, p<0.001) higher among participants with low educational attainment (primary level or less) than those with at least a secondary level of education. Conclusions In rural Bangladesh, the prevalence of disability is high. Public health programs should target those of low SES, older age, and female participants and aim to provide necessary supports in order to bridge disability-related inequities.

Experimental investigation for dynamic stiffness and dimensional accuracy of FDM manufactured part using IV-Optimal response surface design

Purpose Fused deposition modeling (FDM) has become an increasingly important process among the available additive manufacturing technologies in various industries. Although there are many advantages of FDM process, a downside of its industrial application is the attainable dimensional accuracy with tight tolerance without compromising the mechanical performance. This paper aims to study the effects of six FDM operating parameters on two conflicting responses, namely, dynamic stiffness and dimensional stability of FDM produced PC-ABS parts. This study also aims to determine the optimal process settings using graphical optimization that satisfy the dynamic mechanical properties without compromising the dimensional accuracy. Design/methodology/approach The regression models based upon IV-optimal response surface methodology are developed to study the variation of dimensional accuracy and dynamic mechanical properties with changes in process parameter settings. Statistical analysis was conducted to establish the relationships between process variables and dimensional accuracy and dynamic stiffness. Analysis of variance is used to define the level of significance of the FDM operating parameters. Scanning electron microscope and Leica MZ6 optical microscope are used to examine and characterize the morphology of the structures for some specimens. Findings Experimental results highlight the individual and interaction effects of processing conditions on the dynamic stiffness and part accuracy. The results showed that layer thickness (slice height), raster-to-raster air gap and number of outlines have the largest effect on the dynamic stiffness and dimensional accuracy. The results also showed an interesting phenomenon of the effect of number of contours and the influence of other process parameters. The optimal process conditions for highest mechanical performance and part accuracy are obtained. Originality/value The effect of FDM processing parameters on the properties under dynamic and cyclic loading conditions has not been studied in the previous published work. Furthermore, simultaneous optimization of dynamic mechanical properties without compromising the dimensional accuracy has also been investigated. On the basis of experimental findings, it is possible to provide practical suggestions to set the optimal FDM process parameters in relation to dynamic mechanical performance, as well as the dimensional accuracy.

Optimising technology to measure functional vision, mobility and service outcomes for people with low vision or blindness: protocol for a prospective cohort study in Australia and Malaysia

Introduction Orientation and mobility (O&M) specialists assess the functional vision and O&M skills of people with mobility problems, usually relating to low vision or blindness. There are numerous O&M assessment checklists but no measures that reduce qualitative assessment data to a single comparable score suitable for assessing any O&M client, of any age or ability, in any location. Functional measures are needed internationally to align O&M assessment practices, guide referrals, profile O&M clients, plan appropriate services and evaluate outcomes from O&M programmes (eg, long cane training), assistive technology (eg, hazard sensors) and medical interventions (eg, retinal implants). This study aims to validate two new measures of functional performance vision-related outcomes in orientation and mobility (VROOM) and orientation and mobility outcomes (OMO) in the context of ordinary O&M assessments in Australia, with cultural comparisons in Malaysia, also developing phone apps and online training to streamline professional assessment practices. Methods and analysis This multiphase observational study will employ embedded mixed methods with a qualitative/quantitative priority: corating functional vision and O&M during social inquiry. Australian O&M agencies (n=15) provide the sampling frame. O&M specialists will use quota sampling to generate cross-sectional assessment data (n=400) before investigating selected cohorts in outcome studies. Cultural relevance of the VROOM and OMO tools will be investigated in Malaysia, where the tools will inform the design of assistive devices and evaluate prototypes. Exploratory and confirmatory factor analysis, Rasch modelling, cluster analysis and analysis of variance will be undertaken along with descriptive analysis of measurement data. Qualitative findings will be used to interpret VROOM and OMO scores, filter statistically significant results, warrant their generalisability and identify additional relevant constructs that could also be measured. Ethics and dissemination Ethical approval has been granted by the Human Research Ethics Committee at Swinburne University (SHR Project 2016/316). Dissemination of results will be via agency reports, journal articles and conference presentations.

Deriving Tests of the Semi-Linear Regression Model Using the Density Function of a Maximal Invariant

In the context of a general regression model in which some regression coefficients are of interest and others are purely nuisance parameters, we define the density function of a maximal invariant statistic with the aim of testing for the inclusion of regressors (either linear or non-linear) in linear or semi-linear models. This allows the construction of the locally best invariant test, which in two important cases is equivalent to the one-sided t test for a regression coefficient in an artificial linear regression model.We consider a specific semi-linear model to apply the constructed test.

Influence of processing parameters on creep and recovery behavior of FDM manufactured part using definitive screening design and ANN

Purpose The purpose of this paper is to investigate the effect of process parameters of fused deposition modelling (FDM) 3D printing process on viscoelastic responses (creep compliance and recoverable compliance) of FDM built parts using a novel experimental design technique. Design/methodology/approach As part of the process characterization, a recently developed class of three-level design methodology – definitive screening design (DSD) – was used in this study to fit a second-order polynomial regression model. Artificial neural network (ANN) was also used to determine the optimal process parameters to improve creep compliance and recoverable compliance. The relationship between layer thickness, air gap, raster angle, build orientation, road width, number of contours and creep performance of FDM fabricated part was thereafter established empirically. Scanning electron microscope (SEM) is used to examine and characterize the morphology of the structures for some samples. Findings This study found that the creep resistance of FDM-manufactured part is significantly influenced by layer thickness, air gap, raster angle and number of contours and it can be improved by optimizing the settings of the selected parameters. The relationship between FDM process parameters and creep properties was determined, with the best creep performance observed by using 0.127 mm of layer thickness, zero air gap, zero raster angle, build orientation of 17.188°, road width of 0.4572 mm and 10 contours. Finally, the result is verified by confirmation experiments. The results prove that a DSD is a very effective design in characterizing the influence of process parameters on creep properties of FDM-built part at the lowest cost. Originality/value The originality of this paper lies in characterizing and optimizing the effect of process parameters on creep performance of FDM manufactured part that has not been studied in all previous studies. The paper highlights, for the first time, how the application of DSD can overcome most of the limitations encountered in the conventional techniques. This study can be used as a guide to the different additive manufacturing users of various industries and the results provide a good technical database on how FDM process parameters influence the creep performance of manufactured parts.

Experimental investigation of the influence of fabrication conditions on dynamic viscoelastic properties of PC-ABS processed parts by FDM process

This paper presents optimization studies on manufacturing parameters for fused deposition modelling (FDM). Layer thickness, air gap, raster angle, build orientation, road width and number of contours are the process variables considered for optimization. Dynamic modulus and glass transition temperature were considered as response parameters. Experiments were designed using fractional factorial design. The effect of each process parameter was investigated using developed regression models and through analysis of variance (ANOVA) technique. The surface characteristics are studied using scanning electron microscope (SEM). Further, performance of optimum conditions was determined and validated by confirmation experiment.

Towards holistic dual diagnosis care: physical health screening in a Victorian community-based alcohol and drug treatment service

The poorer health outcomes experienced by people with mental illness have led to new directions in policy for routine physical health screening of service users. By contrast, little attention has been paid to the physical health needs of consumers of alcohol and other drug (AOD) services, despite a similar disparity in physical health outcomes compared with the general population. The majority of people with problematic AOD use have comorbid mental illness, known as a dual diagnosis, likely to exacerbate their vulnerability to poor physical health. With the potential for physical health screening to improve health outcomes for AOD clients, a need exists for systematic identification and management of common health conditions. Within the current health service system, those with a dual diagnosis are more likely to have their physical health surveyed and responded to if they present for treatment in the mental health system. In this study, a physical health screening tool was administered to clients attending a community-based AOD service. The tool was administered by a counsellor during the initial phase of treatment, and referrals to health professionals were made as appropriate. Findings are discussed in terms of prevalence, types of problems identified and subsequent rates of referral. The results corroborate the known link between mental and physical ill health, and contribute to developing evidence that AOD clients present with equally concerning physical ill health to that of mental health clients and should equally be screened for such when presenting for AOD treatment.