Product Development Process Modeling Using Advanced Simulation

This paper presents a product development process modeling and analysis technique using advanced simulation.The model computes the probability distribution of lead time in a resource-constrained project network where iterations take place among sequential, parallel and overlapped tasks. The model uses the design structure matrix representation to capture the information flows between tasks. In each simulation run, the expected durations of tasks are initially sampled using the Latin Hypercube Sampling method and decrease over time as the model simulates the progress of dynamic stochastic processes. It is assumed that the rework of a task occurs for the following reasons: (1) new information is obtained from overlapped tasks after starting to work with preliminary inputs, (2) inputs change when other tasks are reworked, and (3) outputs fail to meet established criteria. The model can be used for better project planning and control by identifying leverage points for process improvements and evaluating alternative planning and execution strategies. An industrial example is used to illustrate the utility of the model.Center for Innovation in Product Developmen

An integrated method for managing complex engineering projects using the design structure matrix and advanced simulation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (p. 101-104).This thesis proposes an integrated project management framework for complex engineering projects such as the development of an automobile. The integrated method streamlines project planning and control using three modules: structuring, modeling, and scheduling. In the structuring module, the design structure matrix (DSM) method is used to structure the information flows among tasks and capture the iteration loops. By classifying various types of information dependencies, a critical dependency path is identified and redundant constraints are removed for the modeling and scheduling analyses. In the modeling module, a generalized process model predicts complex behaviors of iterative processes using advanced simulation techniques such as the Latin Hypercube Sampling and parallel discrete event simulation. The model computes the probability distribution of lead time and identifies critical paths in a resource-constrained, iterative project. Using the results of analyses from the structuring and modeling modules, a network-based schedule in the form of a PERT or Gantt chart is developed in the scheduling module. The schedule is used as the basis for monitoring and control of the project. The primary goal of this work is to develop an integrated method that guides project management efforts by improving the effectiveness and predictability of complex processes. The method can also be used for identifying leverage points for process improvements and evaluating alternative planning and execution strategies. Better project management will ultimately result in a better quality product with timely delivery to customers. Two case studies are performed to illustrate the utility of the method.by Soo-Haeng Cho.S.M

Effects of Huang Bai (Phellodendri Cortex) and Three Other Herbs on GnRH and GH Levels in GT1–7 and GH3 Cells

The present study was to evaluate the effects of Huang Bai, Zhi Mu, Mai Ya, and Xia Ku Cao on hormone using the GT1–7 and GH3 cells. The GT1–7 and GH3 cell lines were incubated with DW; DMSO; and 30, 100, or 300 μg/mL of one of the four extract solutions in serum-free media for 24 hours. The MTT assay was performed to determine the cytotoxicity of the four herbs. The GT1–7 and GH3 cells were incubated in DW, estradiol (GT1–7 only), or noncytotoxic herb solutions in serum-free medium for 24 hours. A quantitative RT-PCR and western blot were performed to measure the GnRH expression in GT1–7 cells and GH expression in GH3 cells. Huang Bai, Zhi Mu, Xia Ku Cao, and Mai Ya inhibited the GnRH mRNA expression in GT1–7 cells, whereas Huang Bai enhanced GH mRNA expression in GH3 cells. Additionally, Xia Ku Cao inhibited GnRH protein expression in GT1–7 cells and Huang Bai promoted GH protein expression in GH3 cells. The findings suggest that Huang Bai can delay puberty by inhibiting GnRH synthesis in the hypothalamus while also accelerating growth by promoting GH synthesis and secretion in the pituitary

Clinical features and long-term prognosis of acute fibrinous and organizing pneumonia histologically confirmed by surgical lung biopsy

Abstract Background Acute fibrinous and organizing pneumonia (AFOP) is a rare interstitial pneumonia characterized by intra-alveolar fibrin deposition and organizing pneumonia. The clinical manifestations and long-term prognosis of AFOP are unclear. Our objective was to investigate the clinical features and prognosis of AFOP. Methods We identified patients diagnosed with AFOP by surgical lung biopsy between January 2011 and May 2018 at Seoul National University Bundang Hospital. We retrospectively reviewed clinical and radiologic findings, treatment, and outcomes of AFOP. Results Fifteen patients with histologically confirmed lung biopsies were included. The median follow-up duration was 2.4 (range, 0.1–82) months. The median age was 55 (range, 33–75) years, and four patients were immunocompromised. Fever was the most common clinical presentation (86.7%). Patchy ground-glass opacities and/or consolidations were the most predominant findings on chest computed tomography images. Nine patients (60%) received mechanical ventilator care, and eight patients (53.3%) died. The non-survivors tended to have slightly higher body mass index (BMI) and a long interval between symptom onset and diagnosis than the survivors, but these findings were not statistically significant. Among seven survivors, five patients were discharged without dyspnea and oxygen supplement. Conclusions The clinical course of AFOP was variable. Although AFOP was fatal, most of the patients who recovered from AFOP maintained normal life without supplemental oxygen therapy and respiratory symptoms

A logical network-based drug-screening platform for Alzheimer’s disease representing pathological features of human brain organoids

Developing effective drugs for Alzheimer’s disease (AD), the most common cause of dementia, has been difficult because of complicated pathogenesis. Here, we report an efficient, network-based drug-screening platform developed by integrating mathematical modeling and the pathological features of AD with human iPSC-derived cerebral organoids (iCOs), including CRISPR-Cas9-edited isogenic lines. We use 1300 organoids from 11 participants to build a high-content screening (HCS) system and test blood–brain barrier-permeable FDA-approved drugs. Our study provides a strategy for precision medicine through the convergence of mathematical modeling and a miniature pathological brain model using iCOs. © 2021, The Author(s).1