Additively manufactured respirators: quantifying particle transmission and identifying system-level challenges for improving filtration efficiency

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy due to a lack of commensurate quality assurance processes. Many open-source respirator designs for AM indicate that they do not provide N95-equivalent protection (filtering 95% of SARS-CoV-2 particles) because they have either not passed aerosol generation tests or not been tested. Few studies have quantified particle transmission through respirator designs outside of the filter medium. This is concerning because several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. No study has isolated these failure mechanisms specifically for respirators. The goal of this paper is to measure particle transmission through printed respirators of different designs, materials, and AM processes. The authors compare the performance of printed respirators to N95 respirators and cloth masks. Respirators in this study printed using desktop- and industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes were not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection. Even while assuming a perfect seal between the respirator and the user’s face, although a few respirators provided >90% efficiency at the 100−300 nm particle range, almost all printed respirators provided <60% filtration efficiency. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but the printed respirators showed similar performance to various cloth masks. The authors further explore the process-driven aspects leading to low filtration efficiency. Although the design/printer/material combination dictates the AM respirator performance, the identified failure modes originate from system-level constraints and are therefore generalizable across multiple AM processes. Quantifying the limitations of AM in producing N95-type respiratory protective masks advances understanding of AM systems toward the development of better part and machine designs to meet the needs of reliable, functional, end-use parts.     

An effective coding approach for multiobjective integrated resource selection and operation sequences problem

In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions. Received: May 2005/Accepted: December 2005     

铝钛共渗钢的研制与工业应用

介绍了开发的铝钛共渗工艺及其特点,该工艺可根据需要调整渗剂配方,实现渗钛或铝钛共渗.研究了一种封闭剂,重点解决了渗剂高温氧化烧结问题,使渗层质量优良、性能稳定.描述了铝钛共渗层的特征和焊接性能及耐腐蚀效果.在中国石化扬子石油化工股份有限公司炼油厂的应用表明,铝钛共渗钢具有良好的抗低温H2S腐蚀的能力,并具有优良的耐冲刷、耐磨蚀性能.     

质量控制图系统的实现及在SMT中的应用

本文将控制图理论与计算机技术相结合,开发了质量控制图系统.介绍了该系统的设计方案和关键技术问题,并以电子产品制造中监控SMT机的焊膏厚度为例说明了系统的应用.     

积层板的制造方法

概述了积层板的开发背景、制造工艺和最近的开发动向。     

火炮身管内表面激光硬化处理的实验研究

提高身管寿命是火炮行业亟待解决的关键技术问题，激光表面改性技术是解决这一问题的有效方法之一。本文在分析激光表面相变硬化性能的基础上，对身管内表面进行了激光硬化处理实验研究，检测了其内表面阳线和阴线的硬化层硬度和深度，对比分析了离焦量和焦深对其内表面硬化层硬度的影响，并对激光相变硬化层金相组织进行了分析。经激光硬化处理后，身管的内表面硬度有明显提高，硬化层较深，且为很细的条状马氏体组织。     

Design and Implementation of a Flexible Manufacturing Control System Using Neural Network

Design and implementation of a sequential controller based on the concept of artificial neural networks for a flexible manufacturing system are presented. The recurrent neural network (RNN) type is used for such a purpose. Contrary to the programmable controller, an RNN-based sequential controller is based on a definite mathematical model rather than depending on experience and trial and error techniques. The proposed controller is also more flexible because it is not limited by the restrictions of the finite state automata theory. Adequate guidelines of how to construct an RNN-based sequential controller are presented. These guidelines are applied to different case studies. The proposed controller is tested by simulations and real-time experiments. These tests prove the successfulness of the proposed controller performances. Theoretical as well as experimental results are presented and discussed indicating that the proposed design procedure using Elman's RNN can be effective in designing a sequential controller for event-based type manufacturing systems. In addition, the simulation results assure the effectiveness of the proposed controller to outperform the effect of noisy inputs.     

技术转移对我国制造业企业创新绩效的影响

分别对高新技术企业与一般工业企业、大型企业与中小型企业进行了对比分析，发现高新技术企业比一般工业企业更有吸收能力，而技术转移对中小企业的影响比大型企业大。对参与技术转移及未参与技术转移的制造业企业进行了比较研究，结果证明有技术转移行为的企业具有更优的创新绩效。     

A Knowledge-Navigation System for Dimensional Metrology

Geometric dimensioning and tolerancing (GD&T) is a method to specify the dimensions and form of a part so that it will meet its design intent. GD&T is difficult to master for two main reasons. First, it is based on complex 3D geometric entities and relationships. Second, the geometry is associated with a large, diverse knowledge base of dimensional metrology with many interconnections. This paper describes an approach to create a dimensional metrology knowledge base that is organized around a set of key concepts and to represent those concepts as virtual objects that can be navigated with interactive, computer visualization techniques to access the associated knowledge. The approach can enable several applications. First is the application to convey the definition and meaning of GD&T over a broad range of tolerance types. Second is the application to provide a visualization of dimensional metrology knowledge within a control hierarchy of the inspection process. Third is the application to show the coverage of interoperability standards to enable industry to make decisions on standards development and harmonization efforts. A prototype system has been implemented to demonstrate the principles involved in the approach.