Considerations for a design and operations knowledge support system for Space Station Freedom

Engineering and operations of modern engineered systems depend critically upon detailed design and operations knowledge that is accurate and authoritative. A design and operations knowledge support system (DOKSS) is a modern computer-based information system providing knowledge about the creation, evolution, and growth of an engineered system. The purpose of a DOKSS is to provide convenient and effective access to this multifaceted information. The complexity of Space Station Freedom's (SSF's) systems, elements, interfaces, and organizations makes convenient access to design knowledge especially important, when compared to simpler systems. The life cycle length, being 30 or more years, adds a new dimension to space operations, maintenance, and evolution. Provided here is a review and discussion of design knowledge support systems to be delivered and operated as a critical part of the engineered system. A concept of a DOKSS for Space Station Freedom (SSF) is presented. This is followed by a detailed discussion of a DOKSS for the Lyndon B. Johnson Space Center and Work Package-2 portions of SSF

The Sixth Annual Workshop on Space Operations Applications and Research (SOAR 1992)

This document contains papers presented at the Space Operations, Applications, and Research Symposium (SOAR) hosted by the U.S. Air Force (USAF) on 4-6 Aug. 1992 and held at the JSC Gilruth Recreation Center. The symposium was cosponsored by the Air Force Material Command and by NASA/JSC. Key technical areas covered during the symposium were robotic and telepresence, automation and intelligent systems, human factors, life sciences, and space maintenance and servicing. The SOAR differed from most other conferences in that it was concerned with Government-sponsored research and development relevant to aerospace operations. The symposium's proceedings include papers covering various disciplines presented by experts from NASA, the USAF, universities, and industry

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

Reducing risk in pre-production investigations through undergraduate engineering projects.

This poster is the culmination of final year Bachelor of Engineering Technology (B.Eng.Tech) student projects in 2017 and 2018. The B.Eng.Tech is a level seven qualification that aligns with the Sydney accord for a three-year engineering degree and hence is internationally benchmarked. The enabling mechanism of these projects is the industry connectivity that creates real-world projects and highlights the benefits of the investigation of process at the technologist level. The methodologies we use are basic and transparent, with enough depth of technical knowledge to ensure the industry partners gain from the collaboration process. The process we use minimizes the disconnect between the student and the industry supervisor while maintaining the academic freedom of the student and the commercial sensitivities of the supervisor. The general motivation for this approach is the reduction of the entry cost of the industry to enable consideration of new technologies and thereby reducing risk to core business and shareholder profits. The poster presents several images and interpretive dialogue to explain the positive and negative aspects of the student process

Efficient Data Streaming Analytic Designs for Parallel and Distributed Processing

Today, ubiquitously sensing technologies enable inter-connection of physical\ua0objects, as part of Internet of Things (IoT), and provide massive amounts of\ua0data streams. In such scenarios, the demand for timely analysis has resulted in\ua0a shift of data processing paradigms towards continuous, parallel, and multitier\ua0computing. However, these paradigms are followed by several challenges\ua0especially regarding analysis speed, precision, costs, and deterministic execution.\ua0This thesis studies a number of such challenges to enable efficient continuous\ua0processing of streams of data in a decentralized and timely manner.In the first part of the thesis, we investigate techniques aiming at speeding\ua0up the processing without a loss in precision. The focus is on continuous\ua0machine learning/data mining types of problems, appearing commonly in IoT\ua0applications, and in particular continuous clustering and monitoring, for which\ua0we present novel algorithms; (i) Lisco, a sequential algorithm to cluster data\ua0points collected by LiDAR (a distance sensor that creates a 3D mapping of the\ua0environment), (ii) p-Lisco, the parallel version of Lisco to enhance pipeline- and\ua0data-parallelism of the latter, (iii) pi-Lisco, the parallel and incremental version\ua0to reuse the information and prevent redundant computations, (iv) g-Lisco, a\ua0generalized version of Lisco to cluster any data with spatio-temporal locality\ua0by leveraging the implicit ordering of the data, and (v) Amble, a continuous\ua0monitoring solution in an industrial process.In the second part, we investigate techniques to reduce the analysis costs\ua0in addition to speeding up the processing while also supporting deterministic\ua0execution. The focus is on problems associated with availability and utilization\ua0of computing resources, namely reducing the volumes of data, involving\ua0concurrent computing elements, and adjusting the level of concurrency. For\ua0that, we propose three frameworks; (i) DRIVEN, a framework to continuously\ua0compress the data and enable efficient transmission of the compact data in the\ua0processing pipeline, (ii) STRATUM, a framework to continuously pre-process\ua0the data before transferring the later to upper tiers for further processing, and\ua0(iii) STRETCH, a framework to enable instantaneous elastic reconfigurations\ua0to adjust intra-node resources at runtime while ensuring determinism.The algorithms and frameworks presented in this thesis contribute to an\ua0efficient processing of data streams in an online manner while utilizing available\ua0resources. Using extensive evaluations, we show the efficiency and achievements\ua0of the proposed techniques for IoT representative applications that involve a\ua0wide spectrum of platforms, and illustrate that the performance of our work\ua0exceeds that of state-of-the-art techniques

Programmed \u27Treasuries of Eloquence’: A Rhetorical Take on Productivity Aids in Audio Engineering Software

This project examines the influence of productivity aids in digital audio production software on matters of professional expertise, user experience, and workflow. The research is based on both the public reflections of 25 leading audio engineers about the state of the craft and the field as well as close content analyses of the most widely used software solutions for music mixing. Using the practical tenets of the fourth canon of rhetoric, memory, as a heuristic lens and emphasizing its role as an arbiter of professional expertise, this study contextualizes memory as both recollection strategy and programmed practice. It examines the extent to which embedded productivity aids take over the work of audio engineers and what effects this has on the craft and its community of practitioners. The study culminates in a larger argument about the potentially detrimental effects of automation on creative practice and promotes an appreciation of memory and recollection strategies that inform a pedagogy of critical reflection and active engagement— especially in view of higher education where students prepare for their careers post-graduation

Testing and Developing a Remote Controlled and Supervised Container Handling Equipment

The introduction of Automation is gaining speed in many application fields due the latest technological, social and economic developments. The field of harbour terminals is not an exception, with up to 500 large scale terminals searching for new automation systems. This MSc thesis was carried out at Kalmar and it is taking into consideration company policies and procedures in order to provide a realistic scenario. However, the literature review was not limited to Kalmar solutions and is taking into consideration other practices, especially those related to networks and video and audio protocols. The main objective of this MSc thesis is the development of an automatic rubber tyred gantry crane. Special consideration is provided on how the crane can remotely be controlled and supervised within a specific area. The supervision is desired because by safety reasons the operator supervises the automatic movements of the gantry direction in X coordinate and the Y trolley coordinate for a potential “dead man´s” switch. The hoist direction along Z and the truck lane operation are remotely controlled by the operator. As an engineering requirement, Kalmar´s Software Architecture, and its reconfiguration features, play an important role at the time of configuring and installing the system. The Thesis pays special attention on how to solve network issues due the increase of crane´s load. The final approach is complemented by the development of a User Interface in order to host the increased amount of information due the new automation system. The Thesis also presents the results for testing the new solution on Cargotec final product, and outline the main issues reported during the testing period. The resulting solution is a market ready product

Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments