Process-Time Benchmarking: A Two-Tier Model for Banking Firms

Abstract This work presents a novel method of continuous improvement for faster, better and cheaper TEM sample preparation using Cut Look and Measure (CLM). The improvement of the process is executed by operational monitoring of daily beam conditions, end products, bulk thickness control, recipe usage and tool running time. This process produces a consequent decrease in rework rate and process time. In addition, it also increases throughput with better quality TEM samples.

Download Full-text

Data Visualization Indicator Disease (Malaria, Dengue Fever, and Measles) in The Year 2012-2015

International Journal of New Media Technology ◽

10.31937/ijnmt.v4i2.785 ◽

2017 ◽

Vol 4 (2) ◽

pp. 87-93

Author(s):

Immanuel Luigi Da Gusta ◽

Johan Setiawan

Keyword(s):

Data Mining ◽

Human Resources ◽

Data Visualization ◽

Health Sector ◽

Medical Personnel ◽

Database Systems ◽

Process Time ◽

Acceptance Test ◽

Visual Data Mining ◽

The Government

The aim of this paper are: to create a data visualization that can assist the Government in evaluating the return on the development of health facilities in the region and province area in term of human resources for medical personnel, to help community knowing the amount of distribution of hospitals with medical personnel in the regional area and to map disease indicator in Indonesia. The issue of tackling health is still a major problem that is not resolved by the Government of Indonesia. There are three big things that become problems in the health sector in Indonesia: infrastructure has not been evenly distributed and less adequate, the lack of human resources professional health workforce, there is still a high number of deaths in the outbreak of infectious diseases. Data for the research are taken from BPS, in total 10,600 records after the Extract, Transform and Loading process. Time needed to convert several publications from PDF, to convert to CSV and then to MS Excel 3 weeks. The method used is Eight-step Data Visualization and Data Mining methodology. Tableau is chosen as a tool to create the data visualization because it can combine each dasboard inside a story interactive, easier for the user to analyze the data. The result is a story with 3 dashboards that can fulfill the requirement from BPS staff and has been tested with a satisfied result in the UAT (User Acceptance Test). Index Terms—Dashboard, data visualization, disease, malaria, Tableau REFERENCES [1] S. Arianto, Understanding of learning and others, 2008. [2] Rainer; Turban, Introduction to Information Systems, Danvers: John Wiley & Sons, Inc, 2007. [3] V. Friedman, Data Visualization Infographics, Monday Inspirition, 2008. [4] D. A. Keim, "Information Visualization and Visual Data Mining," IEEE Transactions on Visualization and Computer Graphics 8.1, pp. 1-8, 2002. [5] Connolly and Begg, Database Systems, Boston: Pearson Education, Inc, 2010. [6] E. Hariyanti, "Pengembangan Metodologi Pembangunan Information Dashboard Untuk Monitoring kinerja Organisasi," Konferensi dan Temu Nasional Teknologi Informasi dan Komunikasi untuk Indonesia, p. 1, 2008. [7] S. Darudiato, "Perancangan Data Warehouse Penjualan Untuk Mendukung Kebutuhan Informasi Eksekutif Cemerlang Skin Care," Seminar Nasional Informatika 2010, pp. E-353, 2010.

Download Full-text

Design of Center Pillar with Composite Reinforcements Using Hybrid Molding Method

Materials ◽

10.3390/ma14082047 ◽

2021 ◽

Vol 14 (8) ◽

pp. 2047

Author(s):

Ji-Heon Kang ◽

Jae-Wook Lee ◽

Jae-Hong Kim ◽

Tae-Min Ahn ◽

Dae-Cheol Ko

Keyword(s):

Composite Materials ◽

Weight Reduction ◽

Fuel Efficiency ◽

Vehicle Body ◽

Process Time ◽

Fiber Reinforced ◽

Fiber Reinforced Plastic ◽

Molding Method ◽

Reinforced Plastic ◽

Composite Reinforcements

Recently, with the increase in awareness about a clean environment worldwide, fuel efficiency standards are being strengthened in accordance with exhaust gas regulations. In the automotive industry, various studies are ongoing on vehicle body weight reduction to improve fuel efficiency. This study aims to reduce vehicle weight by replacing the existing steel reinforcements in an automobile center pillar with a composite reinforcement. Composite materials are suitable for weight reduction because of their higher specific strength and stiffness compared to existing steel materials; however, one of the disadvantages is their high material cost. Therefore, a hybrid molding method that simultaneously performs compression and injection was proposed to reduce both process time and production cost. To replace existing steel reinforcements with composite materials, various reinforcement shapes were designed using a carbon fiber-reinforced plastic patch and glass fiber-reinforced plastic ribs. Structural analyses confirmed that, using these composite reinforcements, the same or a higher specific stiffness was achieved compared to the that of an existing center pillar using steel reinforcements. The composite reinforcements resulted in a 67.37% weight reduction compared to the steel reinforcements. In addition, a hybrid mold was designed and manufactured to implement the hybrid process.

Download Full-text

Decolorization of Reactive Black B from wastewater by electro-coagulation: optimization using multivariate RSM and ANN

Chemical Product and Process Modeling ◽

10.1515/cppm-2020-0043 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Kajal Gautam ◽

Rishi K. Verma ◽

Suantak Kamsonlian ◽

Sushil Kumar

Keyword(s):

Current Density ◽

Operating Cost ◽

Quadratic Model ◽

Coefficient Of Determination ◽

Process Time ◽

Mathematical Tool ◽

Electrode Gap ◽

Artificial Neural Network Ann ◽

Electro Coagulation ◽

Optimized Conditions

AbstractThe present study is aimed to model and optimize the electrocoagulation (EC) process with five important parameters for the decolorization of Reactive Black B (RBB) from simulated wastewater. A multivariate approach, response surface methodology (RSM) together with central composite design (CCD) is used to optimize process parameters such as pH (5–9), electrode gap (0.5–2.5 cm), current density (2.08–10.41 mA/cm2), process time (10–30 min), and initial dye concentration (100–500 mg/l). The predicted percentage decolorization of dye is obtained as 97.21% at optimized conditions: pH (6.8), gapping (1.3 cm), current density (8.32 mA/cm2), time (23 min), and initial dye concentration (200 mg/L), which is very close to experimental percent decolorization (98.41%). The statistical analysis of variance (ANOVA) is performed to evaluate the quadratic model (RSM), and shows good fit of experimental data with coefficient of determination R2 >0.93. An Artificial Neural Network (ANN) is also used to predict the percentage decolorization and gives overall 94.96% which shows performance accuracy between the predicted and actual value of decolorization. The additional considerations of operating cost and current efficiency are also taken care to show the efficacy of EC process with mathematical tool. The sludge characteristics are determined by FE-SEM/EDX.

Download Full-text

Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication

Mathematics ◽

10.3390/math9091029 ◽

2021 ◽

Vol 9 (9) ◽

pp. 1029

Author(s):

Ying-Mei Tu

Keyword(s):

Arrival Time ◽

Time Estimation ◽

Advanced Technology ◽

Shop Floor ◽

Process Time ◽

Short Term ◽

Work In Process ◽

Scheduling Model ◽

Cluster Tools ◽

Cluster Tool

Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

Download Full-text

Optimization of the Bioactivation of Isoflavones in Soymilk by Lactic Acid Bacteria

Processes ◽

10.3390/pr9060963 ◽

2021 ◽

Vol 9 (6) ◽

pp. 963

Author(s):

Jon Kepa Izaguirre ◽

Leire Barañano ◽

Sonia Castañón ◽

Itziar Alkorta ◽

Luis M. Quirós ◽

...

Keyword(s):

Lactic Acid ◽

Lactic Acid Bacteria ◽

Lactobacillus Plantarum ◽

Inoculum Size ◽

Process Time ◽

Medical Applications ◽

Bacterial Strains ◽

Food Industries ◽

Glucosidase Activity ◽

Interesting Candidate

Soybeans and soy-based products contain isoflavones which can be used for nutraceutical and medical applications. In soybeans and in unfermented soy foods, isoflavones are normally present as glycosides. Isoflavone glycosides can be enzymatically converted to isoflavone aglycones, thus releasing the sugar molecule. The effective absorption of isoflavones in humans requires the bioconversion of isoflavone glycosides to isoflavone aglycones through the activity of the enzyme β-glucosidase. The objective was to assess the capacity of 42 bacterial strains (belonging to Lactobacillus, Streptococcus and Enterococcus) to produce β-glucosidase activity. The strain that showed the highest β-glucosidase activity (Lactobacillus plantarum 128/2) was then used for the optimization of the bioconversion of genistin and daidzin present in commercial soymilk to their aglycone forms genistein and daidzein. The contribution of process parameters (temperature, inoculum size, time) to the efficiency of such bioactivation was tested. Lactobacillus plantarum 128/2 was able to completely bioactivate soymilk isoflavones under the following conditions: 25 °C temperature, 2% inoculum size and 48 h process time. These results confirm the suitability of lactic acid bacteria for the bioactivation of isoflavones present in soymilk and provide an interesting candidate (L. plantarum 182/2) for food industries to perform this transformation.

Download Full-text

Substrate adhesion evolves non-monotonically with processing time in millimeter-scale aligned carbon nanotube arrays

Nanoscale ◽

10.1039/d0nr05469k ◽

2021 ◽

Vol 13 (1) ◽

pp. 261-271

Author(s):

Ashley L. Kaiser ◽

Dale L. Lidston ◽

Sophie C. Peterson ◽

Luiz H. Acauan ◽

Stephen A. Steiner ◽

...

Keyword(s):

Carbon Nanotube ◽

Adhesion Strength ◽

Processing Time ◽

Effective Modulus ◽

Work Of Adhesion ◽

Process Time ◽

Nanotube Arrays ◽

Substrate Adhesion ◽

Carbon Nanotube Arrays

Aligned carbon nanotube (CNT) array adhesion strength evolves with CNT process time, decreasing and then increasing during growth and annealing, as captured by models relating CNT diameter, array effective modulus, and CNT–substrate work of adhesion.

Download Full-text

Improving the W Coating Uniformity by a COMSOL Model-Based CVD Parameter Study for Denser Wf/W Composites

Metals ◽

10.3390/met11071089 ◽

2021 ◽

Vol 11 (7) ◽

pp. 1089

Author(s):

Leonard Raumann ◽

Jan Willem Coenen ◽

Johann Riesch ◽

Yiran Mao ◽

Daniel Schwalenberg ◽

...

Keyword(s):

Relative Density ◽

Gas Flow ◽

Chemical Vapor ◽

Process Time ◽

Parameter Study ◽

Reactor Model ◽

Production Route ◽

Coating Uniformity ◽

Hydrogen Retention ◽

Return Lead

Tungsten (W) has the unique combination of excellent thermal properties, low sputter yield, low hydrogen retention, and acceptable activation. Therefore, W is presently the main candidate for the first wall and armor material for future fusion devices. However, its intrinsic brittleness and its embrittlement during operation bears the risk of a sudden and catastrophic component failure. As a countermeasure, tungsten fiber-reinforced tungsten (Wf/W) composites exhibiting extrinsic toughening are being developed. A possible Wf/W production route is chemical vapor deposition (CVD) by reducing WF6 with H2 on heated W fabrics. The challenge here is that the growing CVD-W can seal gaseous domains leading to strength reducing pores. In previous work, CVD models for Wf/W synthesis were developed with COMSOL Multiphysics and validated experimentally. In the present article, these models were applied to conduct a parameter study to optimize the coating uniformity, the relative density, the WF6 demand, and the process time. A low temperature and a low total pressure increase the process time, but in return lead to very uniform W layers at the micro and macro scales and thus to an optimized relative density of the Wf/W composite. High H2 and low WF6 gas flow rates lead to a slightly shorter process time and an improved coating uniformity as long as WF6 is not depleted, which can be avoided by applying the presented reactor model.

Download Full-text

Quadrature Integration Techniques for Random Hyperbolic PDE Problems

Mathematics ◽

10.3390/math9020160 ◽

2021 ◽

Vol 9 (2) ◽

pp. 160

Author(s):

Rafael Company ◽

Vera N. Egorova ◽

Lucas Jódar

Keyword(s):

Numerical Methods ◽

Laplace Transform ◽

Quadrature Rule ◽

Inverse Laplace Transform ◽

Process Time ◽

Efficient Computation ◽

Hyperbolic Pde ◽

Numerical Convergence ◽

Laplace Transform Technique ◽

Integration Techniques

In this paper, we consider random hyperbolic partial differential equation (PDE) problems following the mean square approach and Laplace transform technique. Randomness requires not only the computation of the approximating stochastic processes, but also its statistical moments. Hence, appropriate numerical methods should allow for the efficient computation of the expectation and variance. Here, we analyse different numerical methods around the inverse Laplace transform and its evaluation by using several integration techniques, including midpoint quadrature rule, Gauss–Laguerre quadrature and its extensions, and the Talbot algorithm. Simulations, numerical convergence, and computational process time with experiments are shown.

Download Full-text