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NASA NTRS1990

Automation software for a materials testing laboratory

The software environment in use at the NASA-Lewis Research Center's High Temperature Fatigue and Structures Laboratory is reviewed. This software environment is aimed at supporting the tasks involved in performing materials behavior research. The features and capabilities of the approach to specifying a materials test include static and dynamic control mode switching, enabling multimode test control; dynamic alteration of the control waveform based upon events occurring in the response variables; precise control over the nature of both command waveform generation and data acquisition; and the nesting of waveform/data acquisition strategies so that material history dependencies may be explored. To eliminate repetitive tasks in the coventional research process, a communications network software system is established which provides file interchange and remote console capabilities.

Mcgaw, Michael A.↗

NASA NTRSDate not supplied

Distributed Visual Sensing and Fusion for Advanced Air Mobility

Surveillance solutions for Advanced and Urban Air Mobility frameworks are a key factor to enable safe operations of highly automated aircraft in the civil airspace. To design solutions suitable for all types of aircraft, non-cooperative sensors can be used, though many challenges arise when the small dimensions of the vehicles and their proximity to the ground during low-altitude missions are considered. A distributed sensing concept can be efficiently applied to address these challenges by exploiting multiple sensors within a surveillance network. This paper proposes a strategy to fuse the information collected by three ground-fixed cameras within a network of multiple distributed sensors and is tested with during experimental flight tests. The solution exploits standalone tracking estimates of each camera within a fusion center that performs triangulation and three-dimensional tracking. This approach is tested in a scenario involving two small UAVs flying at low altitude. The paper deals with the challenges of associating the two objects from independent and unrelated tracks to achieve robust triangulation, which produces meter-level mean errors with respect to GNSS-based ground truth.

Federica Vitiello↗

NASA NTRS2017

Application of Human-Autonomy Teaming to an Advanced Ground Station for Reduced Crew Operations

Within human factors there is burgeoning interest in the "human-autonomy teaming" (HAT) concept as a way to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous systems as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as "plays." It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations, healthcare and medicine, autonomous vehicles, photography, and aviation. The current paper presents one such effort to apply HAT. It details the design of a HAT agent, developed by Human Automation Teaming Solutions, Inc., to facilitate teamwork between the automation and the human operator of an advanced ground dispatch station. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO); consequently, we have named the agent R-HATS. Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by R-HATS, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, R-HATS determines what tasks need to be completed and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. R-HATS has been designed to both support end users and researchers in RCO and HAT. Additionally, R-HATS and its underlying architecture were developed with generalizability in mind as a modular software applicable outside of RCO/aviation domains. This paper will also discuss future further development and testing of RHATS.

automation↗

NASA NTRS1987

An evaluation of a real-time fault diagnosis expert system for aircraft applications

A fault monitoring and diagnosis expert system called Faultfinder was conceived and developed to detect and diagnose in-flight failures in an aircraft. Faultfinder is an automated intelligent aid whose purpose is to assist the flight crew in fault monitoring, fault diagnosis, and recovery planning. The present implementation of this concept performs monitoring and diagnosis for a generic aircraft's propulsion and hydraulic subsystems. This implementation is capable of detecting and diagnosing failures of known and unknown (i.e., unforseeable) type in a real-time environment. Faultfinder uses both rule-based and model-based reasoning strategies which operate on causal, temporal, and qualitative information. A preliminary evaluation is made of the diagnostic concepts implemented in Faultfinder. The evaluation used actual aircraft accident and incident cases which were simulated to assess the effectiveness of Faultfinder in detecting and diagnosing failures. Results of this evaluation, together with the description of the current Faultfinder implementation, are presented.

Schutte, Paul C.↗

NASA NTRS2003

Development of Poincare Software to Predict Arrythmias

The most distressing types of heart malfunction occur because of an abnormal rhythm of the heart. Cardiac arrythmias can be caused by abnormal rhythmicity of the pacemaker, electrolyte disturbances, blockage of the transmission of the electric impulse through the heart, and other abnormalities. There is strong evidence that space flight is associated with decreased cardiac electrical stability that may pose a life threatening risk to astronauts. For example, during the Skylab missions, a crewmember had a five beat run of ventricular tachycardia during lower body negative pressure. Also, analysis of nine 24-hour Holter monitor recordings obtained during long term spaceflight on Mir revealed one 14-beat run of ventricular tachycardia. A Mir cosmonaut was replaced in 1986 because of cardiac dysrhythmias. Most recently, in July of 1997, a Mir commander was unable to participate in the Spektr module repair due to complaints of an irregular heart rhythm. Despite these examples, possible mechanisms of arrhythmias and countermeasure strategies have barely been addressed. The Poincare method has been proposed as a technique that might potentially predict life-threatening arrhythmias before they occur. According to this method, each RR interval obtained from an EKG recording is plotted sequentially vs. the previous RR interval. Several studies using the method have demonstrated a strong correlation between the shape of the Poincare plot and ventricular arrhythmia. Our purpose was to develop an automated software program that detects the R peaks from an EKG recording while simultaneously displaying the Poincare plot and other related parameters.

Maaliki, Samer↗

NASA NTRS1986

The NASA SETI program - An overview

The development and objectives of the NASA SETI program are reviewed. The search strategy for the program is two phase, an all-sky survey and a targeted search; the capabilities and hardware for the searches are discussed. The use of a spectrum analyzer to search the GHz of the spectrum, and of a multichannel spectrum analyzer to detect pulses are examined; the designs and functions of the analyzers are described. A new method for detecting a drifting CW signal is proposed. A diagram of the automated SETI system is presented.

Oliver, Bernard M.↗

NASA NTRS2001

Report on Automated Semantic Analysis of Scientific and Engineering Codes

The loss of the Mars Climate Orbiter due to a software error reveals what insiders know: software development is difficult and risky because, in part, current practices do not readily handle the complex details of software. Yet, for scientific software development the MCO mishap represents the tip of the iceberg; few errors are so public, and many errors are avoided with a combination of expertise, care, and testing during development and modification. Further, this effort consumes valuable time and resources even when hardware costs and execution time continually decrease. Software development could use better tools! This lack of tools has motivated the semantic analysis work explained in this report. However, this work has a distinguishing emphasis; the tool focuses on automated recognition of the fundamental mathematical and physical meaning of scientific code. Further, its comprehension is measured by quantitatively evaluating overall recognition with practical codes. This emphasis is necessary if software errors-like the MCO error-are to be quickly and inexpensively avoided in the future. This report evaluates the progress made with this problem. It presents recommendations, describes the approach, the tool's status, the challenges, related research, and a development strategy.

Stewart. Maark E. M.↗

NASA NTRS1996

Earth benefits of interdisciplinary CELSS-related research by the NSCORT in Bioregenerative Life Support

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.

NASA Discipline Number 93-10↗

NASA NTRS2000

Aerospike Engine Post-Test Diagnostic System Delivered to Rocketdyne

The NASA Glenn Research Center at Lewis Field, in cooperation with Rocketdyne, has designed, developed, and implemented an automated Post-Test Diagnostic System (PTDS) for the X-33 linear aerospike engine. The PTDS was developed to reduce analysis time and to increase the accuracy and repeatability of rocket engine ground test fire and flight data analysis. This diagnostic system provides a fast, consistent, first-pass data analysis, thereby aiding engineers who are responsible for detecting and diagnosing engine anomalies from sensor data. It uses analytical methods modeled after the analysis strategies used by engineers. Glenn delivered the first version of PTDS in September of 1998 to support testing of the engine s power pack assembly. The system was used to analyze all 17 power pack tests and assisted Rocketdyne engineers in troubleshooting both data acquisition and test article anomalies. The engine version of PTDS, which was delivered in June of 1999, will support all single-engine, dual-engine, and flight firings of the aerospike engine.

Meyer, Claudia M.↗

NASA NTRS2004

Toward Effective Shell Modeling of Wrinkled Thin-Film Membranes Exhibiting Stress Concentrations

Geometrically nonlinear shell finite element analysis has recently been applied to solar-sail membrane problems in order to model the out-of-plane deformations due to structural wrinkling. Whereas certain problems lend themselves to achieving converged nonlinear solutions that compare favorably with experimental observations, solutions to tensioned membranes exhibiting high stress concentrations have been difficult to obtain even with the best nonlinear finite element codes and advanced shell element technology. In this paper, two numerical studies are presented that pave the way to improving the modeling of this class of nonlinear problems. The studies address the issues of mesh refinement and stress-concentration alleviation, and the effects of these modeling strategies on the ability to attain converged nonlinear deformations due to wrinkling. The numerical studies demonstrate that excessive mesh refinement in the regions of stress concentration may be disadvantageous to achieving wrinkled equilibrium states, causing the nonlinear solution to lock in the membrane response mode, while totally discarding the very low-energy bending response that is necessary to cause wrinkling deformation patterns. An element-level, strain-energy density criterion is suggested for facilitating automated, adaptive mesh refinements specifically aimed at the modeling of thin-film membranes undergoing wrinkling deformations.

Tessler, Alexander↗

NASA NTRS2003

Automated Monitoring with a BCP Fault-Decision Test

The Bayesian conditional probability (BCP) technique is a statistical fault-decision technique that is suitable as the mathematical basis of the fault-manager module in the automated-monitoring system and method described in the immediately preceding article. Within the automated-monitoring system, the fault-manager module operates in conjunction with the fault-detector module, which can be based on any one of several fault-detection techniques; examples include a threshold-limit-comparison technique or the BSP or SPRT technique mentioned in the preceding article. The present BCP technique is used to evaluate a series of one or more fault-detection events for the purpose of filtering out occasional false alarms produced by many types of statistical fault-detection procedures. The BCP technique increases the probability that an automated monitoring system produces a correct decision regarding the presence or absence of a fault. Because occasional false alarms are an inevitable consequence of the SPRT, BSP, or any other statistically based fault-detection test, there is a need for a logical procedure to distinguish between true and false alarms. Heretofore, it has been common practice to make a fault decision on an ad hoc basis for example by following a multiple-observation voting strategy in which a signal is declared to be indicative of a fault if m of the last n observations produced a fault-detection alarm. The BCP technique was developed to obtain results more reliable than those afforded by a voting strategy. The BCP technique involves a test in which one applies Bayesian inference techniques to a series of one or more single-observation alarms produced by a fault-detection test. One considers the last n decisions generated by a fault-detection test in order to evaluate the conditional probability that a failure is indicated (see figure). Each new decision reached by a fault-detection test is treated as a new piece of evidence about the state of the monitored asset, and the conditional probability of failure for the system is updated on the basis of this new evidence. The conditional probability of failure is compared with a predefined limit. For a probability below the limit, the asset is declared to be healthy. For a probability above the limit, the asset is declared to be faulty.

Bickford, Randall L.↗

NASA NTRS2000

Intelligent Tutoring Systems for Procedural Task Training of Remote Payload Operations at NASA

Intelligent Tutoring Systems (ITSs) encode and apply the subject matter and teaching expertise of experienced instructors to provide students with individualized instruction automatically. ITSs complement training simulators by providing automated instruction when it is not economical or feasible to dedicate an instructor to each student during training simulations. Despite their proven training effectiveness and favorable operating cost, however, relatively few ITSs are in use. This is largely because it is usually costly and difficult to encode the task knowledge used by the ITS to evaluate the student's actions and assess the student's performance. Procedural tasks are tasks for which there exist procedures, guidelines, and strategies that determine the correct set of steps to be taken within each situation. To lower the cost and difficulty of creating tutoring systems for procedural task training, Stottler Henke Associates, Inc. (SHAI) worked closely with the Operations Training Group at NASA's Marshall Space Flight Center to develop the Task Tutor Toolkit (T (exp 3)), a generic tutoring system shell and scenario authoring tool. The Task Tutor Toolkit employs a case-based reasoning approach where the instructor creates a procedure template that specifies the range of student actions that are "correct" within each scenario. Because each procedure template is specific to a single scenario, the system can employ relatively simple reasoning methods to represent a correct set of actions and assess student performance. This simplicity enables a non-programmer to specify task knowledge quickly and easily by via graphical user interface, using a "demonstrate, generalize, and annotate" paradigm, that recognizes the range of possible valid actions and infers principles understood (or misunderstood) by the student when those actions are carried out. The Task Tutor Toolkit was also designed to be modular and general, so that it can be interfaced with a wide range of training simulators and support a variety of training domains. SHAI and NASA applied the Task Tutor Toolkit to create the Remote Payload Operations Tutor (RPOT). RPOT is a specific tutoring system application which lets scientists who are new to space mission operations learn to monitor and control their experiments aboard the International Space Station according to NASA payload regulations, guidelines, and procedures. The RPOT simulator lets students practice these skills by monitoring the telemetry variable values of a simple, hypothetical experiment, sending commands to the experiment, coordinating with NASA personnel via voice communication loops, and submitting and retrieving information via documents and forms. At the end of each scenario, RPOT displays the principles correctly or incorrectly demonstrated by the student, along with explanations and background information. The effectiveness of RPOT and the Task Tutor Toolkit are currently under evaluation at NASA.

Ong, James↗

NASA NTRS2011

Relative Effects of Trajectory Prediction Errors on the AAC Autoresolver

Trajectory prediction is fundamental to automated separation assurance. Every missed alert, false alert and loss of separation can be traced to one or more errors in trajectory prediction. These errors are a product of many different sources including wind prediction errors, inferred pilot intent errors, surveillance errors, navigation errors and aircraft weight estimation errors. This study analyzes the impact of six different types of errors on the performance of an automated separation assurance system composed of a geometric conflict detection algorithm and the Advanced Airspace Concept Autoresolver resolution algorithm. Results show that, of the error sources considered in this study, top-of-descent errors were the leading contributor to missed alerts and failed resolution maneuvers. Descent-speed errors were another significant contributor, as were cruise-speed errors in certain situations. The results further suggest that increasing horizontal detection and resolution standards are not effective strategies for mitigating these types of error sources.

Lauderdale, Todd↗

NASA NTRS2015

Methodology to Define Delivery Accuracy Under Current Day ATC Operations

In order to enable arrival management concepts and solutions in a NextGen environment, ground- based sequencing and scheduling functions have been developed to support metering operations in the National Airspace System. These sequencing and scheduling algorithms as well as tools are designed to aid air traffic controllers in developing an overall arrival strategy. The ground systems being developed will support the management of aircraft to their Scheduled Times of Arrival (STAs) at flow-constrained meter points. This paper presents a methodology for determining the undelayed delivery accuracy for current day air traffic control operations. This new method analyzes the undelayed delivery accuracy at meter points in order to understand changes of desired flow rates as well as enabling definition of metrics that will allow near-future ground automation tools to successfully achieve desired separation at the meter points. This enables aircraft to meet their STAs while performing high precision arrivals. The research presents a possible implementation that would allow delivery performance of current tools to be estimated and delivery accuracy requirements for future tools to be defined, which allows analysis of Estimated Time of Arrival (ETA) accuracy for Time-Based Flow Management (TBFM) and the FAA's Traffic Management Advisor (TMA). TMA is a deployed system that generates scheduled time-of-arrival constraints for en- route air traffic controllers in the US. This new method of automated analysis provides a repeatable evaluation of the delay metrics for current day traffic, new releases of TMA, implementation of different tools, and across different airspace environments. This method utilizes a wide set of data from the Operational TMA-TBFM Repository (OTTR) system, which processes raw data collected by the FAA from operational TMA systems at all ARTCCs in the nation. The OTTR system generates daily reports concerning ATC status, intent and actions. Due to its availability, ease of use, and vast collection of data across several airspaces it was determined that the OTTR data set would be the best method to utilize moving forward with this analysis. The particular variables needed for further analysis were determined along with the necessary OTTR reports, by working closely with the repository team additional analysis reports were developed that provided key ETA and STA information at the freeze horizon. One major benefit of the OTTR data is that using the correct reports the data across several airports could be analyzed over large periods of time. The OTTR data processes the TBFM data daily and is stored in various formats across several airspaces. This allowed us to develop our own parsing methods and raw data processing that would not rely on other computationally expensive tools that perform more in depth analysis of similar sets of data. The majority of this work consisted of the development of the ability to filter flights to create a subset of flights that could be considered undelayed, which is defined as a flight at the freeze horizon with an ETA and STA difference that was minimal or close to zero. This was a broad method that allowed the consideration of a large data set which consisted of all the traffic across a two month period in 2013, the hottest and coldest months, arriving into four airports: George Bush Intercontinental, Denver International, Los Angeles International, and Phoenix Sky Harbor.

delivery accuracy↗

NASA NTRS1993

DESSY: Making a real-time expert system robust and useful

As the complexity and expected life-span of modern space systems continue to increase, the need for real-time data monitoring and failure analysis becomes more critical to their successful operation. The DEcision Support SYstem (DESSY) is a joint effort by the Intelligent Systems Branch/ER2 and the Remote Manipulator System (RMS) Section/DF44 to develop an expert system for the monitoring of the Payload Deployment and Retrieval System (PDRS). DESSY users, the RMS flight controllers, are provided with user interface enhancements and automated monitoring of system state (physical orientation) and status (operational health). Currently, a DESSY prototype for the Manipulator Positioning Mechanism (MPM) and Manipulator Retention Latches (MRL) of the PDRS has been developed and successfully demonstrated during the STS-49 and STS-46 missions. Expert systems for monitoring real-time operations must not only accurately represent domain knowledge, but also address the challenges of using unfiltered real-time data as input. This paper describes the methods and design strategies developed to overcome problems with real-time data in the NASA Mission Control Center. Types of data problems addressed are as follows: (1) loss of data; (2) erratic data; and (3) data lags and irregularities during state transition. Methods used to handle data problems include rule disabling for ignoring data when data quality is uncertain, context-sensitive bounded pattern recognition for minimizing incorrect conclusions based on bad data, and graceful recovery through system correction when reliable data returns. This combination of methods with an object-based modular DESSY design assures a robust program capable of lengthy periods of uninterrupted use in operations.

Land, Sherry A.↗

NASA NTRS1988

Automated generation of reliability models

The abstract semi-Markov specification interface to the SURE (Semi-Markov Range Evaluator) tool (ASSIST) program allows the user to describe the Markov model in a high-level language. Instead of listing the individual states of the model, the user specifies the rules governing the behavior of the system, and these are used to automatically generate the model. A small number of statements in the abstract language can describe a large, complex model. Becuase no assumptions are made about the system being modeled, ASSIST can be used to generate models describing the behavior of any type of system. The abstract model definition and the automatic model generation strategy are described. Analysis of an example fault-tolerant architecture, a triad of processor with cold spare processors, shows how the behavior of a system can be captured by a few general rules. The syntax of the ASSIST input language is then described and demonstrated by creating a model to describe the fault behavior of the example architecture. The flexibility of the abstract language is demonstrated by expanding the example to model multiple triads of processors sharing a pool of cold spare processors.

Johnson, Sally C.↗

NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗

NASA NTRSDate not supplied

Building Automation System Replacement and Improvements during Concurrent Integration and Testing for the Spacecraft Systems Development and Integration Facility

The Spacecraft Systems Development and Integration Facility (SSDIF), the premier cleanroom for NASA Goddard Space Flight Center (GSFC), has gone through multiple iterations of changes to its building automation system (BAS). NASA flight projects require more stringent environmental controls for temperature, humidity, air exchange rates, and pressurization. This led to increasingly difficult circumstances with replacing and improving the BAS during Integration and Testing (I&T) operations. The SSDIF was partially transitioned to a new BAS during November and December of 2023. Transition occurred in a live environment, while regular I&T activities resumed for the Roman Space Telescope. This resulted in the development and execution of a comprehensive method of procedure. Strategies such as sequencing equipment transition, and using temporary controls for critical equipment, avoided detriments to cleanroom environment. While the new BAS was being built, data points on the previous system would become obsolete, leading to data gaps and uncertainties. Critical data points were distinguished and trended on the new system, providing key insights on equipment functionality, while the BAS was completed. Control hunting and environmental deviations were persistent cases with the SSDIF. In some instances, proportional-integral-derivative (PID) tuning was implemented on current logic to bring smooth PID loop hunting. In other situations, controls logic was completely altered by changing setpoints or sequences. This provided greater laminar flow, more stable pressurization, and improved temperature and humidity controls. This paper documents the transitionary procedure to a new BAS, the improvements made, and challenges faced when altering a BAS during I&T operations.

Cleanroom↗