Visual Analytics as an Enabler for Manufacturing Process Decision-making

AbstractThe goal of an optimal manufacturing process is to maximize product performance while minimizing cost, time, and waste. A critical component of this optimization is the appropriate selection of process parameters. While central physical concepts often serve as a starting point, specific parameter selection is frequently done manually, based on operator skill, experience, and intuition. As a result, process optimization is often iterative, non-repeatable, and lacking in traceability. Further, there is no fundamental insight gained into the relationship between process parameter selection and critical process outputs. This paper explores the use of visual analytics as an enabler for manufacturing process decision making. An emerging science, visual analytics couples analytical reasoning with the substantial capability of the human brain to rapidly internalize and understand data that is presented visually. Through the use of interactive interfaces, visual analytics provides a mechanism through which the operator, engineer, and decision-maker can cooperate in real-time with both simulation, experimental, and operational data, facilitating trade studies, what-if analysis, and providing crucial insight into correlations and relationships that drive process optimization. As an exemplar, the concept of visual analytics is applied to the simulation of a notional high pressure die casting process, with the goal of gaining insight into those parameters that contribute to high scrap rates, particularly air entrapment

Wear Characterization of Laser Cladded Ti-Nb-Ta Alloy for Biomedical Applications

Additive manufacturing (AM) has started to unfold diverse fields of applications by providing unique solutions to manufacturing. Laser cladding is one of the prominent AM technologies that can be used to fulfill the needs of custom implants. In this study, the wear resistance of the laser cladded titanium alloy, Ti-17Nb-6Ta, has been evaluated under varied loads in Ringer’s solution. Microstructural evaluation of the alloy was performed by SEM and EDX, followed by phase analysis through XRD. The wear testing and analysis have been carried out with a tribometer under varied loads of 10, 15, and 20 N while keeping other parameters constant. Abrasion was observed to be the predominant mechanism majorly responsible for the wearing of the alloy at the interface. The average wear rate and coefficient of friction values were 0.016 mm3/Nm and 0.22, respectively. The observed values indicated that the developed alloy exhibited excellent wear resistance, which is deemed an essential property for developing biomedical materials for human body implants such as artificial hip and knee joints

A Mathematical Model for Force Prediction in Single Point Incremental Sheet Forming with Validation by Experiments and Simulation

Incremental sheet forming (ISF) is an emerging technology that has shown great potential in forming customized three-dimensional (3D) parts without the use of product-specific dies. The forming force is reduced in ISF due to the localized nature of deformation and successive forming. Forming force plays an important role in modeling the process accurately, so it needs to be evaluated accurately. Some attempts have been made earlier to calculate the forming force; however, they are mostly limited to empirical formulae for evaluating the average forming force and its different components. The current work presents a mathematical model for force prediction during ISF in a 3D polar coordinate system. The model can be used to predict forces for axis-symmetric cones of different wall angles and also for incremental hole flanging. Axial force component, resultant force in the r-θ plane, and total force have been calculated using the developed mathematical model appearing at different forming depths. The cone with the same geometrical parameters and experimental conditions was modeled and simulated on ABAQUS, and finally, experiments were carried out using a six-axis industrial robot. The mathematical model can be used to calculate forces for any wall angle, but for comparison purposes, a 45° wall angle cone has been used for analytical, numerical, and experimental validation. The total force calculated from the mathematical model had a very high level of accuracy with the force measured experimentally, and the maximum error was 4.25%. The result obtained from the FEA model also had a good level of accuracy for calculating total force, and the maximum error was 4.89%

Locoregional recurrence after cystectomy in muscle invasive bladder cancer:Implications for adjuvant radiotherapy

Purpose We report the patterns of locoregional recurrence (LRR) in muscle invasive bladder cancer (MIBC), and propose a risk stratification to predict LRR for optimizing the indication for adjuvant radiotherapy.Materials and Methods The study included patients of urothelial MIBC who underwent radical cystectomy with standard perioperative chemotherapy between 2013 and 2019. Recurrences were classified into local and/or cystectomy bed, regional, systemic, or mixed. For risk stratification modelling, T stage (T2, T3, T4), N stage (N0, N1/2, N3) and lymphovascular invasion (LVI positive or negative) were given differential weightage for each patient. The cohort was divided into low risk (LR), intermediate risk (IR) and high risk (HR) groups based on the cumulative score.Results Of the 317 patients screened, 188 were eligible for the study. Seventy patients (37.2%) received neoadjuvant chemotherapy (NACT) while 128 patients (68.1%) had T3/4 disease and 66 patients (35.1%) had N+ disease. Of the 55 patients (29%) who had a recurrence, 31 (16%) patients had a component of LRR (4% cystectomy bed, 11.5% regional 0.5% locoregional). The median time to LRR was 8.2 (IQR 3.3–18.8) months. The LR, IR and HR groups for LRR based on T, N and LVI had a cumulative incidence of 7.1%, 21.6%, and 35% LRR, respectively. The HR group was defined as T3, N3, LVI positive; T4 N1/2, LVI positive; and T4, N3, any LVI. The odds ratio for LRR was 3.37 (95% CI 1.16–9.73, P = 0.02) and 5.27 (95% CI 1.87–14.84, P = 0.002) for IR and HR respectively, with LR as reference.Conclusion LRR is a significant problem post radical cystectomy with a cumulative incidence of 35% in the HR group. The proposed risk stratification model in our study can guide in tailoring adjuvant radiotherapy in MIBC

Locoregional recurrence after cystectomy in muscle invasive bladder cancer:Implications for adjuvant radiotherapy

Purpose We report the patterns of locoregional recurrence (LRR) in muscle invasive bladder cancer (MIBC), and propose a risk stratification to predict LRR for optimizing the indication for adjuvant radiotherapy.Materials and Methods The study included patients of urothelial MIBC who underwent radical cystectomy with standard perioperative chemotherapy between 2013 and 2019. Recurrences were classified into local and/or cystectomy bed, regional, systemic, or mixed. For risk stratification modelling, T stage (T2, T3, T4), N stage (N0, N1/2, N3) and lymphovascular invasion (LVI positive or negative) were given differential weightage for each patient. The cohort was divided into low risk (LR), intermediate risk (IR) and high risk (HR) groups based on the cumulative score.Results Of the 317 patients screened, 188 were eligible for the study. Seventy patients (37.2%) received neoadjuvant chemotherapy (NACT) while 128 patients (68.1%) had T3/4 disease and 66 patients (35.1%) had N+ disease. Of the 55 patients (29%) who had a recurrence, 31 (16%) patients had a component of LRR (4% cystectomy bed, 11.5% regional 0.5% locoregional). The median time to LRR was 8.2 (IQR 3.3–18.8) months. The LR, IR and HR groups for LRR based on T, N and LVI had a cumulative incidence of 7.1%, 21.6%, and 35% LRR, respectively. The HR group was defined as T3, N3, LVI positive; T4 N1/2, LVI positive; and T4, N3, any LVI. The odds ratio for LRR was 3.37 (95% CI 1.16–9.73, P = 0.02) and 5.27 (95% CI 1.87–14.84, P = 0.002) for IR and HR respectively, with LR as reference.Conclusion LRR is a significant problem post radical cystectomy with a cumulative incidence of 35% in the HR group. The proposed risk stratification model in our study can guide in tailoring adjuvant radiotherapy in MIBC