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At least 91 records · Page 5

An overview of process systems engineering approaches for process intensification: State of the art

Process intensification offers the potential to drastically reduce the energy consumption and cost of producing chemicals from both bulk and distributed feedstocks. This review article aims to offer an extensive survey on state-of-the-art process systems engineering (PSE) approaches for process intensification. From both academic and industrial perspectives, this paper provides an overview of the development of various process intensification technologies, specifically those under the categories of separation, reaction, hybrid reaction/separation, and alternative energy sources. A current status analysis in the areas of modeling and simulation is then provided. An indicative list of PSE publications specialized on process intensification is presented to illustrate the progresses made so far towards the deployment of novel process intensification technologies. We also highlight some recent advances for the modeling, design, and synthesis of intensified systems, as well as for the assessment of their controllability/operability/safety performance. As a result, key open questions in these areas include: (i) how to systematically derive intensified designs, and (ii) how to ensure the operability and optimality of the derived intensified structures while delivering their expected functionality.

42 ENGINEERING↗

A Process for Design Engineering

The American Institute of Aeronautics and Astronautics Design Engineering Technical Committee has developed a draft Design Engineering Process with the participation of the technical community. This paper reviews similar engineering activities, lays out common terms for the life cycle and proposes a Design Engineering Process.

engineering process↗

Idea to Deliverable: The Engineering Design Process

The engineering design process is utilized to evolve an idea into a deliverable. This progression can take years, so to experience as much of the full design process as possible, this internship period was dedicated to working on several projects in different phases of the process. The result is a completed engineering project which provides a foundation that can be used to conduct research on a system by performing experiments, collecting data, and making changes as necessary to improve the system and answer new questions.

42 ENGINEERING↗

A New Digital Holographic Instrument for Measuring Microphysical Properties of Contrails in the SASS (Subsonic Assessment) Program

SPEC incorporated designed, built and operated a new instrument, called a pi-Nephelometer, on the NASA DC-8 for the SUCCESS field project. The pi-Nephelometer casts an image of a particle on a 400,000 pixel solid-state camera by freezing the motion of the particle using a 25 ns pulsed, high-power (60 W) laser diode. Unique optical imaging and particle detection systems precisely detect particles and define the depth-of-field so that at least one particle in the image is almost always in focus. A powerful image processing engine processes frames from the solid-state camera, identifies and records regions of interest (i.e. particle images) in real time. Images of ice crystals are displayed and recorded with 5 micron pixel resolution. In addition, a scattered light system simultaneously measures the scattering phase function of the imaged particle. The system consists of twenty-eight 1-mm optical fibers connected to microlenses bonded on the surface of avalanche photo diodes (APDs). Data collected with the pi-Nephelometer during the SUCCESS field project was reported in a special issue of Geophysical Research Letters. The pi-Nephelometer provided the basis for development of a commercial imaging probe, called the cloud particle imager (CPI), which has been installed on several research aircraft and used in More than a dozen field programs.

Lawson, R. Paul↗

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↗

Working on the Boundaries: Philosophies and Practices of the Design Process

While systems engineering process is a program formal management technique and contractually binding, the design process is the informal practice of achieving the design project requirements throughout all design phases of the systems engineering process. The design process and organization are systems and component dependent. Informal reviews include technical information meetings and concurrent engineering sessions, and formal technical discipline reviews are conducted through the systems engineering process. This paper discusses and references major philosophical principles in the design process, identifies its role in interacting systems and disciplines analyses and integrations, and illustrates the process application in experienced aerostructural designs.

Ryan, R.↗

CIE Analysis Process for Engineered Systems

"CIE Analysis Process for Engineered Systems" outlines a comprehensive methodology for integrating Cyber-Informed Engineering (CIE) principles into both new and existing engineered systems. Sponsored by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (DOE CESER), the process aims to achieve cyber-informed decisions by producing functional security requirements for new systems and retrofitting existing systems to mitigate digital risks. The document details a step-by-step approach, including mission and function definition, digital asset awareness, consequence analysis, and mitigation analysis. It emphasizes the importance of documenting mechanical, electrical, programmable, and network components to protect system functions and provides examples and considerations for each step. The ultimate goal is to ensure that engineered systems remain resilient against cyber threats, maintaining safety, performance, and reliability.

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The systems engineering overview and process (from the Systems Engineering Management Guide, 1990)

The past several decades have seen the rise of large, highly interactive systems that are on the forward edge of technology. As a result of this growth and the increased usage of digital systems (computers and software), the concept of systems engineering has gained increasing attention. Some of this attention is no doubt due to large program failures which possibly could have been avoided, or at least mitigated, through the use of systems engineering principles. The complexity of modern day weapon systems requires conscious application of systems engineering concepts to ensure producible, operable and supportable systems that satisfy mission requirements. Although many authors have traced the roots of systems engineering to earlier dates, the initial formalization of the systems engineering process for military development began to surface in the mid-1950s on the ballistic missile programs. These early ballistic missile development programs marked the emergence of engineering discipline 'specialists' which has since continued to grow. Each of these specialties not only has a need to take data from the overall development process, but also to supply data, in the form of requirements and analysis results, to the process. A number of technical instructions, military standards and specifications, and manuals were developed as a result of these development programs. In particular, MILSTD-499 was issued in 1969 to assist both government and contractor personnel in defining the systems engineering effort in support of defense acquisition programs. This standard was updated to MIL-STD499A in 1974, and formed the foundation for current application of systems engineering principles to military development programs.

Source record↗

CropEx Web-Based Agricultural Monitoring and Decision Support

CropEx is a Web-based agricultural Decision Support System (DSS) that monitors changes in crop health over time. It is designed to be used by a wide range of both public and private organizations, including individual producers and regional government offices with a vested interest in tracking vegetation health. The database and data management system automatically retrieve and ingest data for the area of interest. Another stores results of the processing and supports the DSS. The processing engine will allow server-side analysis of imagery with support for image sub-setting and a set of core raster operations for image classification, creation of vegetation indices, and change detection. The system includes the Web-based (CropEx) interface, data ingestion system, server-side processing engine, and a database processing engine. It contains a Web-based interface that has multi-tiered security profiles for multiple users. The interface provides the ability to identify areas of interest to specific users, user profiles, and methods of processing and data types for selected or created areas of interest. A compilation of programs is used to ingest available data into the system, classify that data, profile that data for quality, and make data available for the processing engine immediately upon the data s availability to the system (near real time). The processing engine consists of methods and algorithms used to process the data in a real-time fashion without copying, storing, or moving the raw data. The engine makes results available to the database processing engine for storage and further manipulation. The database processing engine ingests data from the image processing engine, distills those results into numerical indices, and stores each index for an area of interest. This process happens each time new data is ingested and processed for the area of interest, and upon subsequent database entries, the database processing engine qualifies each value for each area of interest and conducts a logical processing of results indicating when and where thresholds are exceeded. Reports are provided at regular, operator-determined intervals that include variances from thresholds and links to view raw data for verification, if necessary. The technology and method of development allow the code base to easily be modified for varied use in the real-time and near-real-time processing environments. In addition, the final product will be demonstrated as a means for rapid draft assessment of imagery.

Harvey. Craig↗

NTP comparison process

The systems engineering process for the concept definition phase of the program involves requirements definition, system definition, and consistent concept definition. The requirements definition process involves obtaining a complete understanding of the system requirements based on customer needs, mission scenarios, and nuclear thermal propulsion (NTP) operating characteristics. A system functional analysis is performed to provide a comprehensive traceability and verification of top-level requirements down to detailed system specifications and provides significant insight into the measures of system effectiveness to be utilized in system evaluation. The second key element in the process is the definition of system concepts to meet the requirements. This part of the process involves engine system and reactor contractor teams to develop alternative NTP system concepts that can be evaluated against specific attributes, as well as a reference configuration against which to compare system benefits and merits. Quality function deployment (QFD), as an excellent tool within Total Quality Management (TQM) techniques, can provide the required structure and provide a link to the voice of the customer in establishing critical system qualities and their relationships. The third element of the process is the consistent performance comparison. The comparison process involves validating developed concept data and quantifying system merits through analysis, computer modeling, simulation, and rapid prototyping of the proposed high risk NTP subsystems. The maximum amount possible of quantitative data will be developed and/or validated to be utilized in the QFD evaluation matrix. If upon evaluation of a new concept or its associated subsystems determine to have substantial merit, those features will be incorporated into the reference configuration for subsequent system definition and comparison efforts.

Corban, Robert↗

Parametric Cost Analysis: A Design Function

Parametric cost analysis uses equations to map measurable system attributes into cost. The measures of the system attributes are called metrics. The equations are called cost estimating relationships (CER's), and are obtained by the analysis of cost and technical metric data of products analogous to those to be estimated. Examples of system metrics include mass, power, failure_rate, mean_time_to_repair, energy _consumed, payload_to_orbit, pointing_accuracy, manufacturing_complexity, number_of_fasteners, and percent_of_electronics_weight. The basic assumption is that a measurable relationship exists between system attributes and the cost of the system. If a function exists, the attributes are cost drivers. Candidates for metrics include system requirement metrics and engineering process metrics. Requirements are constraints on the engineering process. From optimization theory we know that any active constraint generates cost by not permitting full optimization of the objective. Thus, requirements are cost drivers. Engineering processes reflect a projection of the requirements onto the corporate culture, engineering technology, and system technology. Engineering processes are an indirect measure of the requirements and, hence, are cost drivers.

Dean, Edwin B.↗

Quality Function Deployment for Large Systems

Quality Function Deployment (QFD) is typically applied to small subsystems. This paper describes efforts to extend QFD to large scale systems. It links QFD to the system engineering process, the concurrent engineering process, the robust design process, and the costing process. The effect is to generate a tightly linked project management process of high dimensionality which flushes out issues early to provide a high quality, low cost, and, hence, competitive product. A pre-QFD matrix linking customers to customer desires is described.

Dean, Edwin B.↗