Individual Alarms Research Articles

Ten-Month Evaluation of the Routine Application of Patient Moving Average for Real-Time Quality Control in a Hospital Setting.

In recent years there has been renewed interest in patient-based real-time quality control (PBRTQC) techniques. This interest has been stimulated by the availability of new optimization and validation methods. Only a limited amount of research has focused on investigating the true operational value of PBRTQC. Therefore, we have evaluated the performance and value of recently implemented patient moving average quality control (MA QC) procedures. The MA QC settings and protocols were as previously described (Clin Chem Lab Med 2019;57:1329-38) and included MA QCs for 10 chemistry and 6 hematological tests, all performed on duplicate analyzer systems. All MA QC alarms that occurred during the first 10 months of routine clinical application were investigated for assay-specific alarm rate and occurrence in time. Furthermore, the causes of these MA QC alarms were investigated, and alarm relevance was determined on the basis of total allowable bias (TBa) and error (TEa) derived from biological variations. During the 10-month period, 202 individual MA QC alarms occurred, resulting in an overall MA QC alarm rate of 0.030% and a frequency of 4.67 per week. Most alarms were triggered by sodium MA QC. Based on all available fully executed and documented MA QC alarm work-ups, MA QC detected errors that in 26.0% of the alarms exceeded the TBa and in 13.7% the TEa. In 9.2% of the alarms, MA QC alarming triggered instant (technical) corrections. Routine clinical application of MA QC is feasible with maintaining a manageable number of alarms and enabling detection of relevant analytical errors.

Cluster analysis of wind turbine alarms for characterising and classifying stoppages

Turbine alarm systems can give useful information to remote technicians on the cause of a fault or stoppage. However, alarms are generally generated at much too high a rate to gain meaningful insight from on their own, so generally require extensive domain knowledge to interpret. By grouping together commonly occurring alarm sequences, the burden of analysis can be reduced. Instead of analysing many individual alarms that occur during a stoppage, the stoppage can be linked to a commonly occurring sequence of alarms. Hence, maintenance technicians can be given information about the shared characteristics or root causes of stoppages where that particular alarm sequence appeared in the past. This research presents a methodology to identify relevant alarms from specific turbine assemblies and group together similar alarm sequences as they appear during stoppages. Batches of sequences associated with 456 different stoppages are created, and features are extracted from these batches representing the order the alarms appeared in. The batches are grouped together using clustering techniques, and evaluated using silhouette analysis and manual inspection. Results show that almost half of all stoppages can be attributed to one of 15 different clusters of alarm sequences.

Similarity Analysis of Sequential Alarms in Plant Operation Data by using Levenshtein Distance

Sequential alarms are a collection of many alarms that occur almost simultaneously with specific time lags within a short period of time. They reduce the ability of operators to cope with abnormalities at plants because critical alarms are buried under many unnecessary ones. The grouping of correlated sequential alarms according to the degree of similarity helps to reduce them more effectively than by analyzing individual sequential alarms. We propose a new method of analyzing similarities between sequential alarms by using the Levenshtein distance, which is a string metric for measuring the difference between two sequences defined as the minimum number of edit operations such as insertion, deletion, and substitution of a single character needed to transform one string into another. The proposed method first converts the plant operation data, which consist of the occurrence times and tag names of alarms, into sequential alarm data. Then, the similarities between all combinations of any two sequential alarms in the plant operation data are evaluated using the Levenshtein distance. The proposed method was applied to the simulation data of an azeotropic distillation column and the results revealed our method was able to correctly identify similarities between correlated sequential alarms, even when a conventional method of analysis failed due to deletions, substitutions, and transpositions in the alarm sequence.

SU‐E‐T‐207: Flatness and Symmetry Threshold Detection Using Statistical Process Control

AAPM TG-142 guidelines state that beam uniformity (flatness and symmetry) should maintain a constancy of 1 % relative to baseline. The focus of this study is to determine if statistical process control (SPC) methodology using process control charts (PCC) of steering coil currents (SCC) can detect changes in beam uniformity prior to exceeding the 1% constancy criteria. SCCs for the transverse and radial planes are adjusted such that a reproducibly useful photon or electron beam is available. Transverse and radial - positioning and angle SCC are routinely documented in the Morning Check file during daily warm-up. The 6 MV beam values for our linac were analyzed using average and range (Xbar/R) PCC. Using this data as a baseline, an experiment was performed in which each SCC was changed from its mean value (steps of 0.01 or 0.02 Ampere) while holding the other SCC constant. The effect on beam uniformity was measured using a beam scanning system. These experimental SCC values were plotted in the PCC to determine if they would exceed the predetermined limits. The change in SCC required to exceed the 1% constancy criteria was detected by the PCC for 3 out of the 4 steering coils. The reliability of the result in the one coil not detected (transverse position coil) is questionable because the SCC slowly drifted during the experiment (0.05 A) regardless of the servo control setting. X-bar/R charts of SCC can detect exceptional variation prior to exceeding the beam uniformity criteria set forth in AAPM TG-142. The high level of PCC sensitivity to change may result in an alarm when in fact minimal change in beam uniformity has occurred. Further study is needed to determine if a combination of individual SCC alarms would reduce the false positive rate for beam uniformity intervention. This project was supoorted by a grant from Varian Medical Systems, Inc.

Event correlation analysis for alarm system rationalization

AbstractEvent correlation analysis is a data‐mining method that detects statistical similarities among discrete occurrences of alarms or operations. By grouping correlated events based on degree of similarity, a policy for reducing alarms and operations can be designed more easily than by analyzing individual alarms and operations. In this study, event correlation analysis was applied to event log data at an Idemitsu Kosan ethylene plant in Japan to reduce the number of alarms and operations, where events are defined by both tag names and types of tag. The obtained results were helpful for identifying unnecessary alarms and operations, such as sequential alarms and routine operations, buried in a lot of noisy plant data. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.

Smart Alerts: Development of Software to Optimize Data Monitoring

Monitoring is useful for vital follow-ups and prevention, diagnosis, and treatment of several events in anesthesia. Although alarms can be useful in monitoring they can cause dangerous user's desensitization. The objective of this study was to describe the development of specific software to integrate intraoperative monitoring parameters generating "smart alerts" that can help decision making, besides indicating possible diagnosis and treatment. A system that allowed flexibility in the definition of alerts, combining individual alarms of the parameters monitored to generate a more elaborated alert system was designed. After investigating a set of smart alerts, considered relevant in the surgical environment, a prototype was designed and evaluated, and additional suggestions were implemented in the final product. To verify the occurrence of smart alerts, the system underwent testing with data previously obtained during intraoperative monitoring of 64 patients. The system allows continuous analysis of monitored parameters, verifying the occurrence of smart alerts defined in the user interface. With this system a potential 92% reduction in alarms was observed. We observed that in most situations that did not generate alerts individual alarms did not represent risk to the patient. Implementation of software can allow integration of the data monitored and generate information, such as possible diagnosis or interventions. An expressive potential reduction in the amount of alarms during surgery was observed. Information displayed by the system can be oftentimes more useful than analysis of isolated parameters.

Performance of Dual Photoelectric/Ionization Smoke Alarms in Full-Scale Fire Tests

Data from two full-scale residential smoke alarm fire test series were analyzed to estimate the performance of dual sensor photoelectric/ionization alarms as compared to co-located individual photoelectric and ionization alarms. Dual alarms and aggregated photoelectric and ionization alarm responses were used to estimate dual alarm performance. It was observed that dual alarms with equivalent or higher sensitivity settings performed better than individual photoelectric or ionization alarms over a range of flaming and smoldering fire scenarios. In one test series, dual alarms activated 539 s faster than ionization alarms and 79 s faster than photoelectric alarms on average. In another test series, individual alarm sensor outputs were calibrated against a reference smoke source in terms of light obscuration over a path length (percent smoke obscuration per unit length) so that alarm thresholds could be defined by the sensor outputs. In that test series, dual alarms, with individual sensor sensitivities equal to their counterpart alarm sensitivities, activated 261 s faster on average than ionization alarms (with sensitivity settings of 4.3%/m smoke obscuration for the ionization sensors) and 35 s faster on average than the photoelectric alarms (with sensitivity settings of 6.6%/m, for the photoelectric sensors.) In cases where an ionization sensor was the first to reach the alarm threshold, the dual alarm activated 67 s faster on average than the photoelectric alarm. While in cases were a photoelectric sensor was the first to reach the alarm threshold, the dual alarm activated 523 s faster on average than the ionization alarm. Over a range of ionization sensor settings examined, dual alarm response was insensitive to the ionization sensor setting for initially smoldering fires and fires with the bedroom door closed, while dual alarm response to the kitchen fires was very sensitive to the ionization sensor setting. Tests conducted in the National Institute of Standards and Technology (NIST) fire emulator/detector evaluator showed that the ionization sensors in off-the-shelf ionization alarms and dual alarms span a range of sensitivity settings. While there appears to be no consensus on sensitivity setting for ionization sensors, it may be desirable to tailor sensor sensitivities in dual alarms for specific applications, such as near kitchens where reducing nuisance alarms may be a goal, or in bedrooms where higher smoke sensitivity may be a goal.

Effects of Single Versus Multiple Warnings on Driver Performance

To explore how a single master alarm system affects drivers' responses when compared with multiple, distinct warnings. Advanced driver warning systems are intended to improve safety, yet inappropriate integration may increase the complexity of driving, especially in high workload situations. This study investigated the effects of auditory alarm scheme, reliability, and collision event type on driver performance. Using a 2 x 2 x 4 mixed factorial design, we investigated the impact of two alarm schemes (master vs. individual) and two levels of alarm reliability (high and low) on distracted drivers' performance across four collision event types (frontal collision warnings, left and right lane departure warnings, and warnings for a fast-approaching following vehicle). Participants' reaction times and accuracy rates were significantly affected by the type of collision event and alarm reliability. The use of individual alarms, rather than a single master alarm, did not significantly affect driving performance in terms of reaction time or response accuracy. Even though a master alarm is a relatively uninformative warning, it produced statistically no different reaction times or accuracy results when compared with information-rich auditory icons, some of which were spatially located. In addition, unreliable alarms negatively impacted driver performance, regardless of event type or alarm scheme. These results have important implications for the development and implementation of multiple driver warning systems.

Response to Nocturnal Alarms Using a Real-Time Glucose Sensor

The objective of this study was to determine how subjects responded to alarms for hypo- and hyperglycemia while they were sleeping. Twenty subjects with type 1 diabetes (4-17 years old) were admitted to a clinical research center for approximately 24 h. Each subject wore two GlucoWatch G2 Biographers (GW2B) (Cygnus, Inc., Redwood City, CA) and was videotaped using an infrared camera from 9 p.m. to 7 a.m. The videotapes were reviewed to determine if the GW2B alarms were audible on the tape and to document the subject's response to the alarms. Because many alarms can occur surrounding a change in blood glucose, GW2B alarm "events" are defined as a one or more alarms separated from previous alarms by more than 30 min. Downloaded data from the biographers identified 240 individual alarms, 75% of which occurred while the subject was sleeping. Of the 240 alarms 68% were audible on the videotape. Subjects awoke to 29% of individual alarms and to 66% of alarm events. Subjects 4-6 years old responded to 17% of alarms, 7-11 year olds responded to 20% of alarms, adolescents responded to 53% of alarms, and parents responded to 37% of alarms. Subjects awoke to 40% of the first alarm during the night, but to only 28% of subsequent alarms. There were 11 events when the glucose was confirmed to be < or = 70 mg/dL, and in each case the subject was awoken. Fifty-five percent of alarm events occurred when there was no hypo- or hyperglycemia confirmed by a reference glucose value. Subjects awoke to 29% of individual alarms and to 66% of alarm events. Subjects awoke during all alarm events when hypoglycemia was confirmed, but there was a high incidence of false alarms.

Automation-Several Big Horn Basin Fields Monitored From One Point

Abstract This paper presents a new mode of operations for monitoring and controlling five oil fields in Wyoming- the largest fully automated telemetering system of this type in the history of the petroleum industry. This is an integrated automated program which monitors or controls through a telemetering system, lease automatic custody transfer (LACT) units, automatic well test units, flow/ no-flow sensors for the individual wells, and lease alarm units. The paper reviews the general field automation program and discusses the components of the telemetering system. Introduction The five fields in Wyoming included in the field automation and telemetering system are the 92-well Frannie field and the 14-well South Elk Basin Tensleep unit, both north of Powell; the 23-well Bonanza field near Worland; the 39-well Gebo field near Thermopolis; and the 84-well Circle Ridge field west of Riverton. The five fields are within a radius of 60 miles and range from 50 to 100 miles apart. Total production of the five fields is currently 12,000 BOPD.The field automation program is divided into four systems: LACT units; AWT units; monitoring systems for determining whether a well is producing (which in this paper are referred to as flow/no-flow systems); and general lease alarm systems. The operation of the fields is monitored and controlled by telemetering through a programmable central facility located in the district production office at Billings, Mont. The Billings district telemetering system consists of two major components- the programmable central facility, which is actually an on-line computer similar to those used in manufacturing facilities, and the remote field installation called the satellite. Both components are designed around transistorized solid-state circuitry. The two major components are linked together by a conventional telegraph- grade 0–15 cycle line. The pilot installation of automation and telemetering, including the monitoring and controlling of automatic well testing, the shipping of oil through LACT units, the reporting of individual well flow conditions and lease alarms, has been operating successfully in Gebo since June, 1962, and demonstrated the reliability of the system. The system was expanded to include the Frannie, South Elk Basin, Circle Ridge and Bonanza fields in Aug, 1963. Field Automation Systems The field automation program varies from field to field. Each field has individual LACT units and a general lease alarm system, but not all fields are equipped with automatic well test units or flow/no-flow sensors. Gebo, the pilot area, is equipped with all four systems. In this field, production is from the Tensleep and Embar reservoirs. Although the Gebo field is a unit, production from each reservoir is segregated and has its own treating system, LACT unit, automatic well test unit, general lease alarm system and flow/no-flow system. The LACT unit for each reservoir consists of one positive displacement meter, BS and W monitor, sampler and recirculating pump. Each system has its own bad oil tank. Production in this field is moved from the well through individual flow lines to headers at the battery location. The headers are eight-way electrically operated selector valves capable of handling the flow lines of seven wells. The header is designed so that production is normally routed through a common flow line to the lease treating unit, but one well at a time can be routed to its particular test treater. The system has a test treater for the Embar and one for the Tensleep production. Each test treater is equipped with PD oil and water meters. Each well is equipped with a mechanical flow/no-flow sensor located at the header. All pump units are equipped with vibration detectors for shutting down the pumping unit when a malfunction of the unit or down-hole equipment occurs. JPT P. 983ˆ