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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

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.↗
NASA NTRS1994

Application of statistical process control and process capability analysis procedures in orbiter processing activities at the Kennedy Space Center

Successful ground processing at KSC requires that flight hardware and ground support equipment conform to specifications at tens of thousands of checkpoints. Knowledge of conformance is an essential requirement for launch. That knowledge of conformance at every requisite point does not, however, enable identification of past problems with equipment, or potential problem areas. This paper describes how the introduction of Statistical Process Control and Process Capability Analysis identification procedures into existing shuttle processing procedures can enable identification of potential problem areas and candidates for improvements to increase processing performance measures. Results of a case study describing application of the analysis procedures to Thermal Protection System processing are used to illustrate the benefits of the approaches described in the paper.

Safford, Robert R.↗
NASA NTRS1996

Statistical Process Control for KSC Processing

The 1996 Summer Faculty Fellowship Program and Kennedy Space Center (KSC) served as the basis for a research effort into statistical process control for KSC processing. The effort entailed several tasks and goals. The first was to develop a customized statistical process control (SPC) course for the Safety and Mission Assurance Trends Analysis Group. The actual teaching of this course took place over several weeks. In addition, an Internet version of the same course complete with animation and video excerpts from the course when it was taught at KSC was developed. The application of SPC to shuttle processing took up the rest of the summer research project. This effort entailed the evaluation of SPC use at KSC, both present and potential, due to the change in roles for NASA and the Single Flight Operations Contractor (SFOC). Individual consulting on SPC use was accomplished as well as an evaluation of SPC software for KSC use in the future. A final accomplishment of the orientation of the author to NASA changes, terminology, data format, and new NASA task definitions will allow future consultation when the needs arise.

Ford, Roger G.↗
NASA NTRS1992

Design issues of a reinforcement-based self-learning fuzzy controller for petrochemical process control

Fuzzy logic controllers have some often-cited advantages over conventional techniques such as PID control, including easier implementation, accommodation to natural language, and the ability to cover a wider range of operating conditions. One major obstacle that hinders the broader application of fuzzy logic controllers is the lack of a systematic way to develop and modify their rules; as a result the creation and modification of fuzzy rules often depends on trial and error or pure experimentation. One of the proposed approaches to address this issue is a self-learning fuzzy logic controller (SFLC) that uses reinforcement learning techniques to learn the desirability of states and to adjust the consequent part of its fuzzy control rules accordingly. Due to the different dynamics of the controlled processes, the performance of a self-learning fuzzy controller is highly contingent on its design. The design issue has not received sufficient attention. The issues related to the design of a SFLC for application to a petrochemical process are discussed, and its performance is compared with that of a PID and a self-tuning fuzzy logic controller.

Yen, John↗
DOE OSTI2014

Multileaf collimator performance monitoring and improvement using semiautomated quality control testing and statistical process control

Purpose: High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. Methods: The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3–4 times/week over a period of 10–11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ±0.5 and ±1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. Results: The precision of the MLC performance monitoring QC test and the MLC itself was within ±0.22 mm for most MLC leaves and the majority of the apparent leaf motion was attributed to beam spot displacements between irradiations. The MLC QC test was performed 193 and 162 times over the monitoring period for the studied units and recalibration had to be repeated up to three times on one of these units. For both units, rate of MLC interlocks was moderately associated with MLC servicing events. The strongest association with the MLC performance was observed between the MLC servicing events and the total number of out-of-control leaves. The average elapsed time for which the number of out-of-specification or out-of-control leaves was within a given performance threshold was computed and used to assess adequacy of MLC test frequency. Conclusions: A MLC performance monitoring system has been developed and implemented to acquire high-quality QC data at high frequency. This is enabled by the relatively short acquisition time for the images and automatic image analysis. The monitoring system was also used to record and track the rate of MLC-related interlocks and servicing events. MLC performances for two commercially available MLC models have been assessed and the results support monthly test frequency for widely accepted ±1 mm specifications. Higher QC test frequency is however required to maintain tighter specification and in-control behavior.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1994

Adaptation of a Control Center Development Environment for Industrial Process Control

In the control center, raw telemetry data is received for storage, display, and analysis. This raw data must be combined and manipulated in various ways by mathematical computations to facilitate analysis, provide diversified fault detection mechanisms, and enhance display readability. A development tool called the Graphical Computation Builder (GCB) has been implemented which provides flight controllers with the capability to implement computations for use in the control center. The GCB provides a language that contains both general programming constructs and language elements specifically tailored for the control center environment. The GCB concept allows staff who are not skilled in computer programming to author and maintain computer programs. The GCB user is isolated from the details of external subsystem interfaces and has access to high-level functions such as matrix operators, trigonometric functions, and unit conversion macros. The GCB provides a high level of feedback during computation development that improves upon the often cryptic errors produced by computer language compilers. An equivalent need can be identified in the industrial data acquisition and process control domain: that of an integrated graphical development tool tailored to the application to hide the operating system, computer language, and data acquisition interface details. The GCB features a modular design which makes it suitable for technology transfer without significant rework. Control center-specific language elements can be replaced by elements specific to industrial process control.

Killough, Ronnie L.↗
DOE OSTI2014

Assessment of Controlling Processes for Field-Scale Uranium Reactive Transport under Highly Transient Flow Conditions

This paper presents the results of a comprehensive model-based analysis of a uranium tracer test conducted at the U.S Department of Energy Hanford 300 Area (300A) IFRC site. A three-dimensional multi-component reactive transport model was employed to assess the key factors and processes that control the field-scale uranium reactive transport. Taking into consideration of relevant physical and chemical processes, the selected conceptual/numerical model replicates the spatial and temporal variations of the observed U(VI) concentrations reasonably well in spite of the highly complex field conditions. A sensitivity analysis was performed to interrogate the relative importance of various processes and factors for reactive transport of U(VI) at the field-scale. The results indicate that multi-rate U(VI) sorption/desorption, U(VI) surface complexation reactions, and initial U(VI) concentrations were the most important processes and factors controlling U(VI) migration. On the other hand, cation exchange reactions, the choice of the surface complexation model, and dual-domain mass transfer processes, which were previously identified to be important in laboratory experiments, played less important roles under the field-scale experimental condition at the 300A site. However, the model simulations also revealed that the groundwater chemistry was relatively stable during the uranium tracer experiment and therefore presumably not dynamic enough to appropriately assess the effects of ion exchange reaction and the choice of surface complexation models on U(VI) sorption and desorption. Furthermore, it also showed that the field experimental duration (16 days) was not sufficiently long to precisely assess the role of a majority of the sorption sites that were accessed by slow kinetic processes within the dual domain model. The sensitivity analysis revealed the crucial role of the intraborehole flow that occurred within the long-screened monitoring wells and thus significantly affected both field-scale measurements and simulated U(VI) concentrations as a combined effect of aquifer heterogeneity and highly dynamic flow conditions. Overall, this study, which provides one of the few detailed and highly data-constrained uranium transport simulations, highlights the difference in controlling processes between laboratory and field scale that prevent a simple direct upscaling of laboratory-scale models.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1985

Materials and processes control for space applications

Materials and processes control relative to space applications is discussed. The components of a total material and process control system are identified, contamination control issues are listed, and recommendations are made.

Blackburn, G. A.↗
NASA NTRS1997

Development of Statistical Process Control Methodology for an Environmentally Compliant Surface Cleaning Process in a Bonding Laboratory

Bonding labs at both MSFC and the northern Utah production plant prepare bond test specimens which simulate or witness the production of NASA's Reusable Solid Rocket Motor (RSRM). The current process for preparing the bonding surfaces employs 1,1,1-trichloroethane vapor degreasing, which simulates the current RSRM process. Government regulations (e.g., the 1990 Amendments to the Clean Air Act) have mandated a production phase-out of a number of ozone depleting compounds (ODC) including 1,1,1-trichloroethane. In order to comply with these regulations, the RSRM Program is qualifying a spray-in-air (SIA) precision cleaning process using Brulin 1990, an aqueous blend of surfactants. Accordingly, surface preparation prior to bonding process simulation test specimens must reflect the new production cleaning process. The Bonding Lab Statistical Process Control (SPC) program monitors the progress of the lab and its capabilities, as well as certifies the bonding technicians, by periodically preparing D6AC steel tensile adhesion panels with EA-91 3NA epoxy adhesive using a standardized process. SPC methods are then used to ensure the process is statistically in control, thus producing reliable data for bonding studies, and identify any problems which might develop. Since the specimen cleaning process is being changed, new SPC limits must be established. This report summarizes side-by-side testing of D6AC steel tensile adhesion witness panels and tapered double cantilevered beams (TDCBs) using both the current baseline vapor degreasing process and a lab-scale spray-in-air process. A Proceco 26 inches Typhoon dishwasher cleaned both tensile adhesion witness panels and TDCBs in a process which simulates the new production process. The tests were performed six times during 1995, subsequent statistical analysis of the data established new upper control limits (UCL) and lower control limits (LCL). The data also demonstrated that the new process was equivalent to the vapor degreasing process.

Hutchens, Dale E.↗
DOE OSTI2015

SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignment of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic errors using routine measurement of electron beam energy constancy.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1991

Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

Shewhart, Mark↗
NASA NTRS1991

Process control integration requirements for advanced life support systems applicable to manned space missions

An overview of recent developments in process-control technology which might have applications in future advanced life support systems for long-duration space operations is presented. Consideration is given to design criteria related to control system selection and optimization, and process-control interfacing methodology. Attention is also given to current life support system process control strategies, innovative sensors, instrumentation and control, and innovations in process supervision.

Spurlock, Paul↗
NASA NTRS1991

Robot welding process control

This final report documents the development and installation of software and hardware for Robotic Welding Process Control. Primary emphasis is on serial communications between the CYRO 750 robotic welder, Heurikon minicomputer running Hunter & Ready VRTX, and an IBM PC/AT, for offline programming and control and closed-loop welding control. The requirements for completion of the implementation of the Rocketdyne weld tracking control are discussed. The procedure for downloading programs from the Intergraph, over the network, is discussed. Conclusions are made on the results of this task, and recommendations are made for efficient implementation of communications, weld process control development, and advanced process control procedures using the Heurikon.

Romine, Peter L.↗
DOE OSTI2018

Process Control Approach to Implement High Waste Loading Glass Formulations for Hanford Low Activity Waste Vitrification - 18435

Acceptable glass formulations for vitrification of Hanford low activity waste (LAW) at The Hanford Tank Waste Treatment and Immobilization Plant (WTP) must meet a variety of product quality, processability, and waste loading requirements. The glass formulation development work underpinning the WTP baseline LAW glasses was captured in a vitrification process control approach developed by the Vitreous State Laboratory (VSL) and Atkins Energy Federal EPC, Inc. that permits the calculation of the glass formulation required for each particular batch of LAW delivered to the LAW vitrification facility. Since that time, we have developed a wide range of glass formulations that achieve considerably higher waste loadings and which therefore are more economically attractive in terms of reduced amounts of glass produced and decreased time for treatment. That work was done in support of the Department of Energy's Office of River Protection program that is examining options to optimize the LAW facility and LAW glass waste form. Implementation of these high waste loading formulations at the WTP requires the development of a new LAW vitrification process control algorithm, which is the subject of this paper. Waste loadings in LAW glasses are typically limited by either the alkali loading for LAW with low sulfate content or the SO{sub 3} loading for LAW with high sulfate content. In the former case, waste loadings are limited by refractory corrosion and glass corrosion on the vapor hydration test (VHT) and product consistency test (PCT), all of which tend to increase with higher alkali concentrations. In the latter case, waste loadings are limited by the formation of a molten sulfate phase in the melter, which has deleterious effects. The LAW vitrification process control strategy must mitigate these effects while optimizing waste loadings. Given the composition of any LAW stream, the new LAW vitrification process control algorithm permits the calculation of a suitable high waste loading glass composition and the required glass forming additives such that all processing, waste loading, and product quality requirements are met. This algorithm was developed from data for a large number of glasses that were formulated, and characterized with respect to a variety of properties affecting processability and product quality; many of these formulations were also subjected to melter testing to verify acceptable processing characteristics, processing rates, and the absence of secondary sulfate phase formation. This paper describes the development of the present algorithm, comparisons to the present lower waste loading baseline WTP process control approach, and plans for further development and testing. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗