On the Selection of Parts and Processes during Design of Printed Circuit Board Assemblies

We consider a multiobjective optimization model that determines components and processes for given conceptual designs of printed circuit board assemblies. Specifically, out model outputs a set of solutions that are Pareto optimal with respect to a cost and a quality metric. The discussion here broadly outlines an integer programming based solution strategy, and represents in-progress work being carried out in collaboration with a manufacturing firm

Integrated Product and Process Design Environment Tool for Manufacturing T/R Modules

We present a decision making assistant tool for integrated product and process design environment for manufacturing applications. Specifically, we target microwave modules which use Electro-mechanical components and require optimal solutions to reduce cost, improve quality, and gain leverage in time to market the product. This tool will assist the product and process designer to improve their productivity and also enable to cooperate and coordinate their designs through a common design interface. We consider a multiobjective optimization model that determines components and processes for a given conceptual designs for microwave modules. This model outputs a set of solutions that are Pareto optimal with respect to cost, quality, and other metrics. In addition, we identify system integration issues for manufacturing applications, and propose an architecture which will serve as a building block to our continuing research in virtual manufacturing applications

SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion

Abstract: The B.1.617.2 (Delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in the state of Maharashtra in late 2020 and spread throughout India, outcompeting pre-existing lineages including B.1.617.1 (Kappa) and B.1.1.7 (Alpha)1. In vitro, B.1.617.2 is sixfold less sensitive to serum neutralizing antibodies from recovered individuals, and eightfold less sensitive to vaccine-elicited antibodies, compared with wild-type Wuhan-1 bearing D614G. Serum neutralizing titres against B.1.617.2 were lower in ChAdOx1 vaccinees than in BNT162b2 vaccinees. B.1.617.2 spike pseudotyped viruses exhibited compromised sensitivity to monoclonal antibodies to the receptor-binding domain and the amino-terminal domain. B.1.617.2 demonstrated higher replication efficiency than B.1.1.7 in both airway organoid and human airway epithelial systems, associated with B.1.617.2 spike being in a predominantly cleaved state compared with B.1.1.7 spike. The B.1.617.2 spike protein was able to mediate highly efficient syncytium formation that was less sensitive to inhibition by neutralizing antibody, compared with that of wild-type spike. We also observed that B.1.617.2 had higher replication and spike-mediated entry than B.1.617.1, potentially explaining the B.1.617.2 dominance. In an analysis of more than 130 SARS-CoV-2-infected health care workers across three centres in India during a period of mixed lineage circulation, we observed reduced ChAdOx1 vaccine effectiveness against B.1.617.2 relative to non-B.1.617.2, with the caveat of possible residual confounding. Compromised vaccine efficacy against the highly fit and immune-evasive B.1.617.2 Delta variant warrants continued infection control measures in the post-vaccination era

Optimization of (s,S) Inventory Systems with Random Lead Times and a Service Level Constraint

A major assumption in the analysis of (s; S) inventory systems with stochastic lead times is that orders are received in the same sequence as they are placed. Even under this assumption, much of the work to date has focused on the unconstrained optimization of the system, in which a penalty cost for unsatisfied demand is assigned. The literature on constrained optimization, wherein a service level requirement needs to be met, is more sparse. In this paper, we consider the constrained optimization problem, where orders are allowed to cross in time. We propose a feasible directions procedure that is simulation-based, and present computational results for a large number of test cases. In the vast majority of cases, we come within 5% of estimated optimality. Keywords: (s; S) inventory systems, random lead times, service level constraint, constrained simulation optimization, feasible directions search, perturbation analysis. 1 Introduction The case of random lead times for (s; S) invent..

Application of Perturbation Analysis to Multiproduct Capacitated Production-Inventory Control

We consider a multiproduct periodic review system with a capacity constraint and no setup cost. Since the optimal stationary control policy for such a system is characterized by a complex switching curve that is usually computationally intractable, we propose a linear approximation to the optimal switching curve. We apply perturbation analysis in a stochastic approximation algorithm to estimate the parameters in the linear approximation. For a randomly chosen test example, we compare numerical results using the linear approximation with results using the optimal dynamic programming formulation. We find that the proposed procedure provides a very good approximation to the optimal solution in a computational time orders of magnitude faster than the dynamic programming solution

Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint

A major assumption in the analysis of (s, S) inventory systems with stochastic lead times is that orders are received in the same sequence as they are placed. Even under this assumption, much of the work to date has focused on the unconstrained optimization of the system, in which a penalty cost for unsatisfied demand is assigned. The literature on constrained optimization, wherein a service level requirement needs to be met, is more sparse. In this paper, we consider the constrained optimization problem, where orders are allowed to cross in time. We propose a feasible directions procedure that is simulation based, and present computational results for a large number of test cases. In the vast majority of cases, we come within 5% of estimated optimality.(s, S) Inventory Systems, Random Lead Times, Service Level Constraint, Constrained Simulation Optimization, Feasible Directions Search, Perturbation Analysis

Transmission of B.1.617.2 Delta variant between vaccinated healthcare workers

AbstractBreakthrough infections with SARS-CoV-2 Delta variant have been reported in doubly-vaccinated recipients and as re-infections. Studies of viral spread within hospital settings have highlighted the potential for transmission between doubly-vaccinated patients and health care workers and have highlighted the benefits of high-grade respiratory protection for health care workers. However the extent to which vaccination is preventative of viral spread in health care settings is less well studied. Here, we analysed data from 118 vaccinated health care workers (HCW) across two hospitals in India, constructing two probable transmission networks involving six HCWs in Hospital A and eight HCWs in Hospital B from epidemiological and virus genome sequence data, using a suite of computational approaches. A maximum likelihood reconstruction of transmission involving known cases of infection suggests a high probability that doubly vaccinated HCWs transmitted SARS-CoV-2 between each other and highlights potential cases of virus transmission between individuals who had received two doses of vaccine. Our findings show firstly that vaccination may reduce rates of transmission, supporting the need for ongoing infection control measures even in highly vaccinated populations, and secondly we have described a novel approach to identifying transmissions that is scalable and rapid, without the need for an infection control infrastructure.</jats:p