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At least 433 records · Page 24

Cryogenic Quenching Process for Electronic Part Screening

The use of electronic parts at cryogenic temperatures (less than 100 C) for extreme environments is not well controlled or developed from a product quality and reliability point of view. This is in contrast to the very rigorous and well-documented procedures to qualify electronic parts for mission use in the 55 to 125 C temperature range. A similarly rigorous methodology for screening and evaluating electronic parts needs to be developed so that mission planners can expect the same level of high reliability performance for parts operated at cryogenic temperatures. A formal methodology for screening and qualifying electronic parts at cryogenic temperatures has been proposed. The methodology focuses on the base physics of failure of the devices at cryogenic temperatures. All electronic part reliability is based on the bathtub curve, high amounts of initial failures (infant mortals), a long period of normal use (random failures), and then an increasing number of failures (end of life). Unique to this is the development of custom screening procedures to eliminate early failures at cold temperatures. The ability to screen out defects will specifically impact reliability at cold temperatures. Cryogenic reliability is limited by electron trap creation in the oxide and defect sites at conductor interfaces. Non-uniform conduction processes due to process marginalities will be magnified at cryogenic temperatures. Carrier mobilities change by orders of magnitude at cryogenic temperatures, significantly enhancing the effects of electric field. Marginal contacts, impurities in oxides, and defects in conductor/conductor interfaces can all be magnified at low temperatures. The novelty is the use of an ultra-low temperature, short-duration quenching process for defect screening. The quenching process is designed to identify those defects that will precisely (and negatively) affect long-term, cryogenic part operation. This quenching process occurs at a temperature that is at least 25 C colder than the coldest expected operating temperature. This quenching process is the opposite of the standard burn-in procedure. Normal burn-in raises the temperature (and voltage) to activate quickly any possible manufacturing defects remaining in the device that were not already rejected at a functional test step. The proposed inverse burn-in or quenching process is custom-tailored to the electronic device being used. The doping profiles, materials, minimum dimensions, interfaces, and thermal expansion coefficients are all taken into account in determining the ramp rate, dwell time, and temperature.

Sheldon, Douglas J.↗

Finite Element Models for Electron Beam Freeform Fabrication Process

Electron beam freeform fabrication (EBF3) is a member of an emerging class of direct manufacturing processes known as solid freeform fabrication (SFF); another member of the class is the laser deposition process. Successful application of the EBF3 process requires precise control of a number of process parameters such as the EB power, speed, and metal feed rate in order to ensure thermal management; good fusion between the substrate and the first layer and between successive layers; minimize part distortion and residual stresses; and control the microstructure of the finished product. This is the only effort thus far that has addressed computer simulation of the EBF3 process. The models developed in this effort can assist in reducing the number of trials in the laboratory or on the shop floor while making high-quality parts. With some modifications, their use can be further extended to the simulation of laser, TIG (tungsten inert gas), and other deposition processes. A solid mechanics-based finite element code, ABAQUS, was chosen as the primary engine in developing these models whereas a computational fluid dynamics (CFD) code, Fluent, was used in a support role. Several innovative concepts were developed, some of which are highlighted below. These concepts were implemented in a number of new computer models either in the form of stand-alone programs or as user subroutines for ABAQUS and Fluent codes. A database of thermo-physical, mechanical, fluid, and metallurgical properties of stainless steel 304 was developed. Computing models for Gaussian and raster modes of the electron beam heat input were developed. Also, new schemes were devised to account for the heat sink effect during the deposition process. These innovations, and others, lead to improved models for thermal management and prediction of transient/residual stresses and distortions. Two approaches for the prediction of microstructure were pursued. The first was an empirical approach involving the computation of thermal gradient, solidification rate, and velocity (G,R,V) coupled with the use of a solidification map that should be known a priori. The second approach relies completely on computer simulation. For this purpose a criterion for the prediction of morphology was proposed, which was combined with three alternative models for the prediction of microstructure; one based on solidification kinetics, the second on phase diagram, and the third on differential scanning calorimetry data. The last was found to be the simplest and the most versatile; it can be used with multicomponent alloys and rapid solidification without any additional difficulty. For the purpose of (limited) experimental validation, finite element models developed in this effort were applied to three different shapes made of stainless steel 304 material, designed expressly for this effort with an increasing level of complexity. These finite element models require large computation time, especially when applied to deposits with multiple adjacent beads and layers. This problem can be overcome, to some extent, by the use of fast, multi-core computers. Also, due to their numerical nature coupled with the fact that solid mechanics- based models are being used to represent the material behavior in liquid and vapor phases as well, the models have some inherent approximations that become more pronounced when dealing with multi-bead and multi-layer deposits.

Chandra, Umesh↗

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Mizell, Carolyn Barrett↗

Evolution of International Space Station Program Safety Review Processes and Tools

The International Space Station Program at NASA is constantly seeking to improve the processes and systems that support safe space operations. To that end, the ISS Program decided to upgrade their Safety and Hazard data systems with 3 goals: make safety and hazard data more accessible; better support the interconnection of different types of safety data; and increase the efficiency (and compliance) of safety-related processes. These goals are accomplished by moving data into a web-based structured data system that includes strong process support and supports integration with other information systems. Along with the data systems, ISS is evolving its submission requirements and safety process requirements to support the improved model. In contrast to existing operations (where paper processes and electronic file repositories are used for safety data management) the web-based solution provides the program with dramatically faster access to records, the ability to search for and reference specific data within records, reduced workload for hazard updates and approval, and process support including digital signatures and controlled record workflow. In addition, integration with other key data systems provides assistance with assessments of flight readiness, more efficient review and approval of operational controls and better tracking of international safety certifications. This approach will also provide new opportunities to streamline the sharing of data with ISS international partners while maintaining compliance with applicable laws and respecting restrictions on proprietary data. One goal of this paper is to outline the approach taken by the ISS Progrm to determine requirements for the new system and to devise a practical and efficient implementation strategy. From conception through implementation, ISS and NASA partners utilized a user-centered software development approach focused on user research and iterative design methods. The user-centered approach used on the new ISS hazard system utilized focused user research and iterative design methods employed by the Human Computer Interaction Group at NASA Ames Research Center. Particularly, the approach emphasized the reduction of workload associated with document and data management activities so more resources can be allocated to the operational use of data in problem solving, safety analysis, and recurrence control. The methods and techniques used to understand existing processes and systems, to recognize opportunities for improvement, and to design and review improvements are described with the intent that similar techniques can be employed elsewhere in safety operations. A second goal of this paper is to provide and overview of the web-based data system implemented by ISS. The software selected for the ISS hazard systemMission Assurance System (MAS)is a NASA-customized vairant of the open source software project Bugzilla. The origin and history of MAS as a NASA software project and the rationale for (and advantages of) using open-source software are documented elsewhere (Green, et al., 2009).

Ratterman, Christian D.↗

Elevated Temperature, Notched Compression Performance of Out of Autoclave Processed Composites

Curved honeycomb sandwich panels composed of carbon fiber reinforced toughened-epoxy polymer facesheets are being evaluated for potential use as payload fairing components on the NASA heavy-lift space launch system (HL-SLS). These proposed composite sandwich panels provide the most efficient aerospace launch structures, and offer mass and thermal advantages when compared with existing metallic payload fairing structures. NASA and industry are investigating recently developed carbon fiber epoxy prepreg systems which can be fabricated using out-of autoclave (OOA) processes. Specifically, OOA processes using vacuum pressure in an oven and thereby significantly reducing the cost associated with manufacturing large (up to 10 m diameter) composite structures when compared with autoclave. One of these OOA composite material systems, CYCOM(R) 5320-1, was selected for manufacture of a 1/16th scale barrel portion of the payload fairing; such that, the system could be compared with the well-characterized prepreg system, CYCOM(R) 977-3, typically processed in an autoclave. Notched compression coupons for each material were obtained from the minimum-gauge flat laminate [60/-60/0]S witness panels produced in this manufacturing study. The coupons were also conditioned to an effective moisture equilibrium point and tested according to ASTM D6484M-09 at temperatures ranging from 25 C up to 177 C. The results of this elevated temperature mechanical characterization study demonstrate that, for thin coupons, the OHC strength of the OOA laminate was equivalent to the flight certified autoclave processed composite laminates; the limitations on the elevated temperature range are hot-wet conditions up to 163 C and are only within the margins of testing error. At 25 C, both the wet and dry OOA material coupons demonstrated greater OHC failure strengths than the autoclave processed material laminates. These results indicate a substantial improvement in OOA material development and processing since previous studies have consistently reported OOA material strengths on par or below those of autoclave processed composite laminates.

Grimsley, Brian W.↗

Human Integration Design Processes (HIDP)

The purpose of the Human Integration Design Processes (HIDP) document is to provide human-systems integration design processes, including methodologies and best practices that NASA has used to meet human systems and human rating requirements for developing crewed spacecraft. HIDP content is framed around human-centered design methodologies and processes in support of human-system integration requirements and human rating. NASA-STD-3001, Space Flight Human-System Standard, is a two-volume set of National Aeronautics and Space Administration (NASA) Agency-level standards established by the Office of the Chief Health and Medical Officer, directed at minimizing health and performance risks for flight crews in human space flight programs. Volume 1 of NASA-STD-3001, Crew Health, sets standards for fitness for duty, space flight permissible exposure limits, permissible outcome limits, levels of medical care, medical diagnosis, intervention, treatment and care, and countermeasures. Volume 2 of NASASTD- 3001, Human Factors, Habitability, and Environmental Health, focuses on human physical and cognitive capabilities and limitations and defines standards for spacecraft (including orbiters, habitats, and suits), internal environments, facilities, payloads, and related equipment, hardware, and software with which the crew interfaces during space operations. The NASA Procedural Requirements (NPR) 8705.2B, Human-Rating Requirements for Space Systems, specifies the Agency's human-rating processes, procedures, and requirements. The HIDP was written to share NASA's knowledge of processes directed toward achieving human certification of a spacecraft through implementation of human-systems integration requirements. Although the HIDP speaks directly to implementation of NASA-STD-3001 and NPR 8705.2B requirements, the human-centered design, evaluation, and design processes described in this document can be applied to any set of human-systems requirements and are independent of reference missions. The HIDP is a reference document that is intended to be used during the development of crewed space systems and operations to guide human-systems development process activities.

Boyer, Jennifer↗

Mars Soil-Based Resource Processing and Planetary Protection

The ability to extract and process resources at the site of exploration into products and services, commonly referred to as In Situ Resource Utilization (ISRU), can have significant benefits for robotic and human exploration missions. In particular, the ability to use in situ resources to make propellants, fuel cell reactants, and life support consumables has been shown in studies to significantly reduce mission mass, cost, and risk, while enhancing or enabling missions not possible without the incorporation of ISRU. In December 2007, NASA completed the Mars Human Design Reference Architecture (DRA) 5.0 study. For the first time in a large scale Mars architecture study, water from Mars soil was considered as a potential resource. At the time of the study, knowledge of water resources (their form, concentration, and distribution) was extremely limited. Also, due to lack of understanding of how to apply planetary protection rules and requirements to ISRU soil-based excavation and processing, an extremely conservative approach was incorporated where only the top several centimeters of ultraviolet (UV) radiated soil could be processed (assumed to be 3% water by mass). While results of the Mars DRA 5.0 study showed that combining atmosphere processing to make oxygen and methane with soil processing to extract water provided the lowest mission mass, atmosphere processing to convert carbon dioxide (CO2) into oxygen was baselined for the mission since it was the lowest power and risk option. With increased knowledge and further clarification of Mars planetary protection rules, and the recent release of the Mars Exploration Program Analysis Group (MEPAG) report on "Special Regions and the Human Exploration of Mars", it is time to reexamine potential water resources on Mars, options for soil processing to extract water, and the implications with respect to planetary protection and Special Regions on Mars.

Sanders, G. B.↗

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

Verification↗

Robust Bonding Through Process Control

Process control has been proven to be the most reliable means of safeguarding the quality of adhesive bonds according to Federal Aviation Administration (FAA). A method for implementing process control for reduction in risk in a bonded joint fabrication process is demonstrated in this study using a selected bonding system. The stepwise method included risk analysis to identify defects with the highest impact and likelihood to occur, evaluation of various pre-bond surface analysis tools to monitor for the selected defects, and demonstration of the benefits of in-process monitoring utilizing threshold limits determined from bond performance tests. The bonded system selected for investigation was an aerospace carbon fiber epoxy composite substrate surface prepared with random orbital sanding using 180 grit aluminum oxide sand paper. A series of portable, pre-bond surface analysis tools were investigated for their ability to be used for in-line bond process control. Results and threshold limits are presented from roughness, ballistic water contact angle (WCA), color, gloss, and Fourier transform infrared spectroscopy (FTIR) surface analysis tools. Results demonstrated how in-process inspection methods can be used to ensure quality of a surface preparation for a selected bonding system. A framework is provided for implementation of bond process control for robust bonding.

Kutscha, Eileen O.↗

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a givensystem. As such, it simulates the propagation of failure effects along paths between the origin ofthe system failure modes and points within the system capable of observing the failure effects. Asa result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMsnecessarily contain a significant amount of information about the design, operations, and failuremodes and effects. One of the important benefits of FFMs is that they may be qualitative, ratherthan quantitative and, as a result, may be implemented early in the design process when there ismore potential to positively impact the system design. FFMs may therefore be developed andmatured throughout the monitored system's design process and may subsequently be used toprovide real-time diagnostic assessments that support system operations. This paper provides anoverview of a generalized NASA process that is being used to develop and apply FFMs. FFMtechnology has been evolving for more than 25 years. The FFM development process presented inthis paper was refined during NASA's Ares I, Space Launch System, and Ground SystemsDevelopment and Operations programs (i.e., from about 2007 to the present). Process refinementtook place as new modeling, analysis, and verification tools were created to enhance FFMcapabilities. In this paper, standard elements of a model development process (i.e., knowledgeacquisition, conceptual design, implementation & verification, and application) are describedwithin the context of FFMs. Further, newer tools and analytical capabilities that may benefit thebroader systems engineering process are identified and briefly described. The discussion isintended as a high-level guide for future FFM modelers.

Melcher, Kevin J.↗

Leveraging the Usage of GPUs in SAR Processing for the NISAR Mission

The NASA ISRO Synthetic Aperture Radar (NISAR) mission will redefine the future of earth science in terms of both the quality as well as the quantity of data that will be downlinked daily. The current software architecture used to process this data is the InSAR Scientific Computing Environment (ISCE), a powerful and modular platform that applies a combination of novel and legacy processing modules to many sources of SAR data. Until recently, this architecture could process most images in a reasonable amount of time; however in the case of the NISAR mission (where the daily influx as well as the size of the images themselves are significantly larger) the current architecture can take hours to process even a single image. This paper explores new efforts to use a Graphics Processing Unit (GPU) to accelerate one of the processing modules to achieve unprecedented runtimes with no loss in precision, potentially setting a new standard in radar processing in the world of “Big Data”.

Cohen, Joshua↗

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗

Automation of the Uncertainty Quantification Process Based on Probability Boxes with DAKOTA

To date, while the use of CFD is prevalent, very few efforts have been undertaken that truly attempt to document all (or even most) of the sources of uncertainty in the simulations. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the design research and engineering community, test and evaluation community, and ultimately certification for flight. This is especially true for hypersonic air-breathing propulsion systems due to the environment, scale, and duration limitations of ground test facilities. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. Hence, a major obstacle that has prevented the adoption of UQ methods for engineering design and development work is the lack of a tool set to automate most (if not all) of the UQ workflow. Towards this end, the SANDIA package DAKOTA (which has been developed to drive both UQ and optimization processes) will be tightly wrapped around the VULCAN-CFD code to automate the uncertainty quantification process. The automated process will be applied to an isolator turbulence model validation exercise that has previously been documented using a manual approach to the UQ process. Hence, the focus of this paper will be documenting the level to which automation can hide the UQ process details from the CFD practitioner rather than the UQ method itself.

CFD↗

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the-art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts. The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners. However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen Michael Middleton↗

AM Processes Part 2: Principles of Directed Energy Deposition

Directed Energy Deposition (DED) is one of the metal additive manufacturing processes which finds wider industrial applications, particularly for repair and reclamation, and for large structures. This course helps the attendees to understand the fundamental concepts of DED process and covers the topics such as, how the technology works, different DED processes, materials used, and typical applications where this technology is used. The discussion will have a focus on ASTM F3187 – Standard guide for Directed Energy Deposition of Metals. After completing this webinar the attendees will achieve the following: · Identify and understand the different types of DED processes · Understand how to select a DED process and trade criteria · Understand the various materials used for DED processes · Understand the core parameters for the DED processes · Determine potential parts and end application of DED technology

Additive Manufacturing↗

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts.1,2 The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners.1 However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen M Middleton↗

Print-Consistency and Process-Interaction for Inkjet-Printed Copper on Flexible Substrate

Printed electronics is a fastest growing and emerging technology that have shown much potential in several industries including automotive, wearables, healthcare, and aerospace. Its applications can be found not only in flexible but also in large area electronics. The technology provides an effective and convenient method to additively deposit conductive and insulating materials on any type of substrate. Comparing with traditional manufacturing processes, which involves chemical etching, this technology also comes to be relatively environmental friendly. Despite its status, it is not without its challenges. Starting from the material being compatible in the printer equipment to the point of achieving fine resolutions, and with excellent properties are some of the challenges that printed electronics face. Among the myriad of printing technologies such as Aerosol Jet, micro-dispensing, gravure printing, screen printing, Inkjet printing, Inkjet has gained much attention due to its low-cost, low material consumption, and roll-to-roll capability for mass manufacturing. The technology has been widely used in home and office, but recently gained interest in printed electronics in a research and development setting. Conductive materials used in Inkjet printing generally comprises of metal Nanoparticles that need to be thermally sintered for it to be conductive. The preferred metal of choice has been mostly silver due to its excellent electrical properties and ease in sintering. However, silver comes to be expensive than its counterpart copper. Since copper is prone to oxidation, much focus has been given towards photonic sintering that involves sudden burst of pulsed light at certain energy to sinter the copper Nanoparticles. With this technique, only the printed material gets sintered in a matter of seconds without having a great impact on its substrate, due to which it is also preferred in low temperature applications. With all the knowledge, there is still a large gap in the process side with copper where it is important to look how the print process affects the resolution of the print along with the effect of post-print processes on electrical and mechanical properties. In this paper, a copper Inkjet ink is utilized for understanding the effect of Inkjet print parameters on the ejected droplet and its resolution. Post-print process is also quantified using a photonic sintering equipment for excellent electrical and mechanical properties. To demonstrate the complete process, commercial-off-the-shelf components will also be mounted on the additively printed pads via Inkjet. Statistically, control charting technique will be utilized to understand the capability of the Inkjet process.

printed electronics↗

Oversimplification of Systems Engineering Goals, Processes, and Criteria in NASA Space Life Support

This paper investigates the oversimplification of the inherently complex systems engineering process in space life support. The standard systems engineering process steps are described. The International Space Station (ISS) life support system is explained with its goals and performance criteria. Although it is not usually emphasized, the essential function of developing a hierarchy of systems and subsystems is to simplify the design process. The System Complexity Metric (SCM) shows how this di-vide-and-conquer approach also reduces the system complexity. The complete systems engineering process has many detailed steps. It is often simplified because of the effort required and the human limitations on working memory and decision span. Systems analysis demands slow, logical, and fo-cused thinking but is often bypassed in favor of quick, intuitive, subconscious “gut feel.” A study of 100 system designs found examples of 12 specific mental mistakes, such as ignoring stakeholder needs, and these mistakes are essentially oversimplifications of the systems engineering process. An analysis of space life support goals, options, criteria, and processes found 11 examples of oversimplifications in systems engineering, such as neglecting safety and cost. All these 11 oversimplifications could be traced to one or more of the 12 previously identified mental mistakes or other well-known ones, such as ig-noring sunk costs. Oversimplification of the systems engineering process is rarely noticed but is a common and harmful problem. A study of failures in 50 different space systems found that problems in systems engineering caused failures and often led to errors in design, development, and test that further contributed to failure. It seems that more diligent systems engineering could prevent many project problems and failures, but projects seem to be more guided by “gut feel” based on tradition, authority, and consensus than on the logical, rational systems engineering approach.

Simplified systems engineering↗