SMART ADDITIVE MANUFACTURING: IN-PROCESS SENSING AND DATA ANALYTICS FOR ONLINE DEFECT DETECTION IN METAL ADDITIVE MANUFACTURING PROCESSES

The goal of this dissertation is to detect the incipient flaws in metal parts made using additive manufacturing processes (3D printing). The key idea is to embed sensors inside a 3D printing machine and conclude whether there are defects in the part as it is being built by analyzing the sensor data using artificial intelligence (machine learning). This is an important area of research, because, despite their revolutionary potential, additive manufacturing processes are yet to find wider acceptance in safety-critical industries, such as aerospace and biomedical, given their propensity to form defects. The presence of defects, such as porosity, can afflict as much as 20% of additive manufactured parts. This poor process consistency necessitates an approach wherein flaws are not only detected but also promptly corrected inside the machine. This dissertation takes the critical step in addressing the first of the above, i.e., detection of flaws using in-process sensor signatures. Accordingly, the objective of this work is to develop and apply a new class of machine learning algorithms motivated from the domain of spectral graph theory to analyze the in-process sensor data, and subsequently, detect the formation of part defects. Defects in additive manufacturing originate due to four main reasons, namely, material, process parameters, part design, and machine kinematics. In this work, the efficacy of the graph theoretic approach is determined to detect defects that occur in all the above four contexts. As an example, in Chapter 4, flaws such as lack-of-fusion porosity due to poor choice of process parameters in additive manufacturing are identified with statistical accuracy exceeding 80%. As a comparison, the accuracy of existing conventional statistical methods is less than 65%. Advisor: Prahalada Ra

SMART ADDITIVE MANUFACTURING: IN-PROCESS SENSING AND DATA ANALYTICS FOR ONLINE DEFECT DETECTION IN METAL ADDITIVE MANUFACTURING PROCESSES

The goal of this dissertation is to detect the incipient flaws in metal parts made using additive manufacturing processes (3D printing). The key idea is to embed sensors inside a 3D printing machine and conclude whether there are defects in the part as it is being built by analyzing the sensor data using artificial intelligence (machine learning). This is an important area of research, because, despite their revolutionary potential, additive manufacturing processes are yet to find wider acceptance in safety-critical industries, such as aerospace and biomedical, given their propensity to form defects. The presence of defects, such as porosity, can afflict as much as 20% of additive manufactured parts. This poor process consistency necessitates an approach wherein flaws are not only detected but also promptly corrected inside the machine. This dissertation takes the critical step in addressing the first of the above, i.e., detection of flaws using in-process sensor signatures. Accordingly, the objective of this work is to develop and apply a new class of machine learning algorithms motivated from the domain of spectral graph theory to analyze the in-process sensor data, and subsequently, detect the formation of part defects. Defects in additive manufacturing originate due to four main reasons, namely, material, process parameters, part design, and machine kinematics. In this work, the efficacy of the graph theoretic approach is determined to detect defects that occur in all the above four contexts. As an example, in Chapter 4, flaws such as lack-of-fusion porosity due to poor choice of process parameters in additive manufacturing are identified with statistical accuracy exceeding 80%. As a comparison, the accuracy of existing conventional statistical methods is less than 65%. Advisor: Prahalada Ra

Pneumatic Rupture of Rectosigmoid; a Case Report

Pneumatic rectosigmoid rapture is usually occurred following the inappropriate fun by direct entering a high volume of the air through the pneumatic device to the anus. Such an event was reported for the first time in 1904 by Stone. Diagnosis and treatment of such injuries are often delayed because of some social limitations and preventing the patient form explaining the event. Colon sigmoid rupture and pneumoperitoneum is one of the most dangerous and life treating complications of entering a high volume of the air to the rectum in a short time. There are only a few reports regarding the similar cases. Here, a case of pneumatic rectosigmoid rapture was reported in a 53 year-old male following an inappropriate fun

A New Hybrid Robust Fault Detection of Switching Systems by Combination of Observer and Bond Graph Method

In this paper, the problem of robust Fault Detection (FD) for continuous time switched system is tackled using a hybrid approach by combination of a switching observer and Bond Graph (BG) method. The main criteria of an FD system including the fault sensitivity and disturbance attenuation level in the presence of parametric uncertainties are considered in the proposed FD system. In the first stage, an optimal switching observer based on state space representation of the BG model is designed in which simultaneous fault sensitivity and disturbance attenuation level are satisfied using H=H1 index. In the second stage, the Global Analytical Redundancy Relations (GARRs) of the switching system are derived based on the output estimation error of the observer, which is called Error-based Global Analytical Redundancy Relations (EGARRs). The parametric uncertainties are included in the EGARRs, which define the adaptive thresholds on the residuals. A constant term due to the effect of disturbance is also considered in the thresholds. In fact, a two-stage FD system is proposed wherein some criteria may be considered in each stage. The efficiency of the proposed method is shown for a two-tank system

A survey of the relationship between EQ and organizational entrepreneurship of the employees of Bank Maskan in Kerman province (Iran)

In recent decades, organizational entrepreneurship is taken into attention by researchers. The concept of organizational entrepreneurship is of great importance for the organizations in a new era, as well as the factors affecting the entrepreneurial orientation are. EQ as a variable related to the management of our own feelings and establishing the effective communication with others took our attention. One of the psychological variables in relation with organizational entrepreneurship is EQ. EQ is an array of non-cognitive capabilities, competencies, and skills that influence one’s ability to succeed in coping with environmental demands and pressures. Based on the importance of organizational entrepreneurship and the effect of personality characteristics including EQ on organizational entrepreneurship, the present study attempted to evaluate the relation between EQ and organizational entrepreneurship in Bank Maskan of Kerman province. The present study is applied in terms of aim and it is descriptive-correlation in terms of method. The study population was the employees of Bank Maskan in Kerman province as 357 people. The sample size was selected randomly based on Cochran’s formula, 185 employees of Bank Maskan in Kerman province. For data collection of EQ data, Shrink test was applied and to evaluate the organizational entrepreneurship, Dr. Moqimi questionnaire was used and their reliability by Cronbach’s alpha were 0.89, 0.87, respectively. For data analysis, one-sample t-test and Pearson correlation analysis were applied and the results showed a positive and strong relation between EQ and organizational entrepreneurshi

Quality of life in chemical warfare survivors with ophthalmologic injuries: the first results form Iran Chemical Warfare Victims Health Assessment Study

<p>Abstract</p> <p>Background</p> <p>Iraq used chemical weapons extensively against the Iranians during the Iran-Iraq war (1980–1988). The aim of this study was to assess the health related quality of life (HRQOL) in people who had ophthalmologic complications due to the sulfur mustard gas exposure during the war.</p> <p>Methods</p> <p>The Veterans and Martyrs Affair Foundation (VMAF) database indicated that there were 196 patients with severe ophthalmologic complications due to chemical weapons exposure. Of these, those who gave consent (n = 147) entered into the study. Quality of life was measured using the 36-item Short Form Health Survey (SF-36) and scores were compared to those of the general public. In addition logistic regression analysis was performed to indicate variables that contribute to physical and mental health related quality of life.</p> <p>Results</p> <p>The mean age of the patients was 44.8 (SD = 8.7) ranging from 21 to 75 years. About one-third of the cases (n= 50) reported exposure to chemical weapons more than once. The mean exposure duration to sulfur mustard gas was 21.6 years (SD = 1.2). The lowest scores on the SF-36 subscales were found to be: the role physical and the general health. Quality of life in chemical warfare victims who had ophthalmologic problems was significantly lower than the general public (P < 0.001). The results obtained from logistic regression analysis indicated that those who did not participate in sport activities suffer from a poorer physical health (OR = 2.93, 95% CI = 1.36 to 6.30, P = 0.006). The analysis also showed that poor mental health was associated with longer time since exposure (OR = 1.58, 95% CI = 1.04 to 2.39, P = 0.03) and lower education (OR = 3.03, 95% CI = 1.21 to 7.56, P = 0.01).</p> <p>Conclusion</p> <p>The study findings suggest that chemical warfare victims with ophthalmologic complications suffer from poor health related quality of life. It seems that the need for provision of health and support for this population is urgent. In addition, further research is necessary to measure health related quality of life in victims with different types of disabilities in order to support and enhance quality of life among this population.</p

A survey of the relationship between EQ and organizational entrepreneurship of the employees of Bank Maskan in Kerman province (Iran)

In recent decades, organizational entrepreneurship is taken into attention by researchers. The concept of organizational entrepreneurship is of great importance for the organizations in a new era, as well as the factors affecting the entrepreneurial orientation are. EQ as a variable related to the management of our own feelings and establishing the effective communication with others took our attention. One of the psychological variables in relation with organizational entrepreneurship is EQ. EQ is an array of non-cognitive capabilities, competencies, and skills that influence one’s ability to succeed in coping with environmental demands and pressures. Based on the importance of organizational entrepreneurship and the effect of personality characteristics including EQ on organizational entrepreneurship, the present study attempted to evaluate the relation between EQ and organizational entrepreneurship in Bank Maskan of Kerman province. The present study is applied in terms of aim and it is descriptive-correlation in terms of method. The study population was the employees of Bank Maskan in Kerman province as 357 people. The sample size was selected randomly based on Cochran’s formula, 185 employees of Bank Maskan in Kerman province. For data collection of EQ data, Shrink test was applied and to evaluate the organizational entrepreneurship, Dr. Moqimi questionnaire was used and their reliability by Cronbach’s alpha were 0.89, 0.87, respectively. For data analysis, one-sample t-test and Pearson correlation analysis were applied and the results showed a positive and strong relation between EQ and organizational entrepreneurshi