Ground Processing Affordability for Space Vehicles

Launch vehicles and most of their payloads spend the majority of their time on the ground. The cost of ground operations is very high. So, why so often is so little attention given to ground processing during development? The current global space industry and economic environment are driving more need for efficiencies to save time and money. Affordability and sustainability are more important now than ever. We can not continue to treat space vehicles as mere science projects. More RLV's (Reusable Launch Vehicles) are being developed for the gains of reusability which are not available for ELV's (Expendable Launch Vehicles). More human-rated vehicles are being developed, with the retirement of the Space Shuttles, and for a new global space race, yet these cost more than the many unmanned vehicles of today. We can learn many lessons on affordability from RLV's. DFO (Design for Operations) considers ground operations during design, development, and manufacturing-before the first flight. This is often minimized for space vehicles, but is very important. Vehicles are designed for launch and mission operations. You will not be able to do it again if it is too slow or costly to get there. Many times, technology changes faster than space products such that what is launched includes outdated features, thus reducing competitiveness. Ground operations must be considered for the full product Lifecycle, from concept to retirement. Once manufactured, launch vehicles along with their payloads and launch systems require a long path of processing before launch. Initial assembly and testing always discover problems to address. A solid integration program is essential to minimize these impacts, as was seen in the Constellation Ares I-X test rocket. For RLV's, landing/recovery and post-flight turnaround activities are performed. Multi-use vehicles require reconfiguration. MRO (Maintenance, Repair, and Overhaul) must be well-planned--- even for the unplanned problems. Defect limits and standard repairs need to be in-place as well as easily added. Many routine inspections and maintenance can be like an aircraft overhaul. Modifications and technology upgrades should be expected. Another factor affecting ground operations efficiency is trending. It is essential for RLV's, and also useful for ELV's which fly the same or similar models again. Good data analysis of technical and processing performance will determine fixes and improvements needed for safety, design, and future processing. Collecting such data on new or low-frequency vehicles is a challenge. Lessons can be learned from the Space Shuttle, or even the Concorde aircraft. For all of the above topics, efficient business systems must be established for comprehensive program management and good throughput. Drawings, specifications, and manuals for an entire launch vehicle are often in different formats from multiple vendors, plus they have proprietary constraints. Nonetheless, the integration team must ensure that all data needed is compatible and visible to each appropriate team member. Ground processing systems for scheduling, tracking, problem resolution, etc. must be well laid-out. The balance between COTS (commercial off the shelf) and custom software is difficult. Multiple customers, vendors, launch sites, and landing sites add to the complexity of efficient IT (Information Technology) tools

Space shuttle program information control and retrieval system feasibility study report

The feasibility of having a common information management network for space shuttle data, is studied. Identified are the information types required, sources and users of the information, and existing techniques for acquiring, storing and retrieving the data. The study concluded that a decentralized system is feasible, and described a recommended development plan for it

Design Supply Chain Based on Cost of Quality with Consideration of Quality Level

In the contemporary global market, organizations are striving to survive and compete not only by satisfying customer’s needs but also by fulfilling it with the least costs. Quality management experts determined that quality costs account for a substantial part of total production costs. Therefore, finding a way to improve the Quality Level (QL) while minimizing the Cost of Quality (COQ) is a crucial task. In the manufacturing industry, there are a variety of costs that are directly associated with the production; these costs can be considered as visible costs. However, another type of costs may indirectly arise during and after manufacturing processes or even after the product reaches the customer. These types of costs are considered as invisible (hidden) costs and in most cases are difficult to track. Measuring the effect of hidden costs such as the costs of unsatisfying a customer is not straightforward. Even though the hidden costs may have serious consequences for any organization if they are not considered in early stages, they are rarely incorporated in the COQ calculations. Furthermore, the COQ models found in the literature rarely go beyond the costs incurred within an individual firm and seldom attempt to estimate cost elements related to the customers or suppliers. This, however, does not reflect the reality, since not all the quality costs are generated internally. Suppliers, subcontractors, agents, dealers and customers each contribute (sometimes significantly) to an organization's indirect quality costs. It is therefore proposed to combine the internal measures of COQ with costs related to both upstream and downstream supply chain (SC) partners. In this thesis, pursuing the aforementioned motivations, we focus on designing SCs in framework of various COQs and QLs. The previous literature lacks a work that integrates the opportunity cost (OC), COQ and QL into SC and Supply Chain Network Design (SCND). The main objectives of this thesis are to consider OC in the COQ analysis, to incorporate it into the Prevention, Appraisal, and Failure (PAF) model, and to analyze it together with various QLs in a manufacturer SC. The purpose is to find an optimum QL that matches the minimum spending on the COQ and. This work proposes a reliable COQ model, which can be used to measure COQ in the whole SC. We carried out a case study in a manufacturing SC to collect the PAF data and the related data to OC i.e., customer satisfaction. The involved organization is an automobile manufacturing SC. A system dynamics model is used to simulate the COQ, while including OC and analyzing its effects at different QLs. In addition, PAF, OC, and QL are mathematically modeled in an uncapacitated SC. Different proposed scenarios were developed to allocate the PAF, OC, and QL in the SC. The model determines the best scenario of allocating the COQ at each facility while minimizing the COQ and OC, and thereby optimizing the QL. Based on the COQ, the mathematical model also reveals the difference between the centralized and decentralized SC. Moreover, we address the effects of spending limitations of PA costs on F, OC, and QL at each facility and in the SC as a whole. Afterwards, the thesis develops a mathematical model which is involved in designing of a capacitated SCND based on PAF, OC, and QL. The developed model is intended to highlight the importance of OC by show the difference between OC-included and OC-excluded SCND model. The SCND model is also used to determine the best improvement in the QL, i.e. the optimal value of investing in the COQ at each echelon. Finally, a hybrid decision support system (DSS) model which combines the mathematical model and the simulation model for COQ, OC, and QL is developed. The model implements the optimum results of the mathematical model in the simulation model. This aim is to increase spending on PA costs beyond the optimal results of the mathematical model. The model is intended to decrease the OC (increase the number of new customeers). The results show how the combined methodologies can provide better decision support for upper management. This research shows that COQ can be used as a meaningful measure of improvement not only in an organization but in the whole SC. The methods developed in this thesis will provide a powerful tool to management for assessing quality economics, facilitating quality programs and optimizing benefits of quality across SC

Site Environmental Report for 2018

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multi-program scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences, with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from LBNL operations conducted in 2018. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31). LBNL activities are planned and conducted with full regard to protecting employees, the public, and the environment, as well as complying with all applicable environmental, safety, and health laws and regulations. As presented in Chapter 2, Berkeley Lab implements an Environmental Management System (EMS) to oversee environmental compliance activities and continually improve overall environmental performance while maintaining operational capability and sustaining its overall mission. The effectiveness of the EMS and environmental programs is reviewed annually as part of the performance evaluation process of Contract 31. For fiscal year (FY) 2018, which began October 1, 2017, and ended September 30, 2018, the EMS was given a performance rating of B plus for its management of environmental activities (on a scale from A plus as the highest grade, to F as the lowest). The measurement and rating system was developed jointly by Berkeley Lab, UC, and DOE. The FY 2018 rating was based on how Berkeley Lab met the objective in DOE’s FY 2018 Performance Evaluation and Measurement Plan (Appendix B in Contract 31, Section J) of providing an efficient and effective EMS. Six significant accomplishments, which ranged from effective teaming on projects and with regulatory agencies to improved program assessment approaches, were factors in the rating. The EMS was also graded through the federal Office of Management and Budget’s annual EMS performance metrics, in which a reporting scorecard rates elements of the International Organization for Standardization (ISO) 14001 standard and the degree of integration between the EMS and Berkeley Lab’s sustainable practices. Overall scores fall into one of three categories: green (highest), yellow (middle), or red (lowest). For FY 2018, Berkeley Lab received a score of green. A week-long formal conformity audit of the EMS was conducted at the end of July by a qualified external party, as is required every three years. The audit team found that Berkeley Lab’s EMS continues to conform to the ISO standard with no major nonconformance. An overview of environmental protection and restoration programs is provided in Chapter 3, including information about compliance activities, operating permits, and regulatory agency inspections and audits that occurred during 2018. Twenty-one minor violations and two Class II violations were issued during agency inspections of programs governing aboveground and underground storage tanks, hazardous waste treatment units, hazardous waste storage areas, hazardous materials management, and wastewater, stormwater, and air emission sources. This report also includes information on environmental monitoring performed in 2018 (Chapter 4). The results of these monitoring activities confirmed that groundwater cleanup actions have been effective in reducing concentrations of volatile organic compounds (VOCs) in the groundwater, although concentrations appear to be reaching asymptotic levels in some areas. Site groundwater plumes are stable or are attenuating, and VOCs are not migrating off site. All emissions and discharges from LBNL operations were within environmental compliance release limits except oxides of nitrogen and carbon monoxide from boilers (under 5 million BTUs) from Buildings 2, 66, and 88. The radiological dose assessments (Chapter 5) performed in 2018 concluded that the maximum potential dose to a hypothetical resident from Berkeley Lab’s airborne radionuclide releases was approximately 0.04% of the DOE and U.S. Environmental Protection Agency annual limit of 10 millirem per year (mrem/yr); the potential dose from all radiation sources at Berkeley Lab was approximately 0.15% of the average natural background radiation dose of 310 mrem/yr in the United States, and about 0.5% of the DOE annual limit of 100 mrem/yr from all sources

A survey of AI in operations management from 2005 to 2009

Purpose: the use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the ten-year period 1995-2004. Like the previous survey, it uses Elsevier’s Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case-based reasoning (CBR), fuzzy logic (FL), knowledge-Based systems (KBS), data mining, and hybrid AI in the four application areas are identified. Findings: the survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004 (Kobbacy et al. 2007). Like the previous survey, it uses the Elsevier’s ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings: The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research

Space transportation system and associated payloads: Glossary, acronyms, and abbreviations

A collection of some of the acronyms and abbreviations now in everyday use in the shuttle world is presented. It is a combination of lists that were prepared at Marshall Space Flight Center and Kennedy and Johnson Space Centers, places where intensive shuttle activities are being carried out. This list is intended as a guide or reference and should not be considered to have the status and sanction of a dictionary

Glossary, acronyms, abbreviations: Space transportation system and associated payloads

A glossary of terms (and definitions) in current usage for the Space Transportation System (STS) and Associated Payloads is presented

Glossary, Acronyms, Abbreviations: Space transportation system and associated payloads

A glossary of terms (and definitions) in current usage for the space transportation system and associated payloads, as well as acronyms and abbreviations, are presented