scholarly journals Risks associated with the evolution in the compounding process of parenteral nutrition solutions: use of the “FMECA” method

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Gautier Dozias ◽  
Julie Thiec ◽  
Gwenola Le Den ◽  
Virginie Cogulet
Keyword(s):  
Parenteral Nutrition ◽  
Failure Modes ◽  
Preventive Measures ◽  
Daily Basis ◽  
Health Staff ◽  
Improvement Plan ◽  
New Process ◽  
Pharmacy Technicians ◽  
Set Up ◽  
Criticality Analysis

Abstract Objectives An audit of the practices of our compounding unit was performed in 2016: areas of improvement were proposed, such as the automatization of our process. An automated compounder was acquired (MediMixmulti® MF4120R). The aim of the study was to anticipate the risks of the new process, in order to improve its security and to support the professionals during this evolution of our compounding process. Methods The Failure Modes, Effects and Criticality Analysis (FMECA) method was carried out in order to detect potential failures brought by the automatization of parenteral nutrition (PN) manufacturing in the new process. The FMECA method included four steps that were divided into five work sessions of one and a half hour each over a period of two months. A working group made up of professionals involved in the PN production process was set up (pharmacists, pharmacy resident, manager and pharmaceutical technician). Results Fifty failure modes were determined by this analysis, of which 96% could have an impact on the patient, 90% on the health staff and 74% on the product. The FMECA shows that 18 failure modes have a tolerable or unacceptable CI (CI≥100) for which it is necessary to implement preventive measures as a priority. This work also made it possible to review the barrier measures already in place for the current process. Conclusions The risk analysis allowed us to analyze the failures of both the actual and the future manufacturing processes. Once the most critical failure modes were identified, specific recommendations were proposed and an improvement plan was established. First, the compounder needs to be fully qualified. Then, the quality manual of the PN process will be reviewed and updated. Once these steps are completed, the pharmacy professionals (pharmacists, pharmacy technicians) will be trained and the PN production will be performed using the automated compounder on a daily basis.

scholarly journals Controlling Risks in the Compounding Process of Individually Formulated Parenteral Nutrition: Use of the FMECA Method (Failure modes, effects, and Criticality Analysis)

2020 ◽  
Vol 4 (3-4) ◽  
pp. 105-112
Author(s):  
Mathilde Royer ◽  
Maïté Libessart ◽  
Jean-Marc Dubaele ◽  
Pierre Tourneux ◽  
Fréderic Marçon
Keyword(s):  
Intensive Care Unit ◽  
Functional Analysis ◽  
Intensive Care ◽  
Parenteral Nutrition ◽  
Neonatal Intensive Care ◽  
Failure Modes ◽  
Risk Priority Number ◽  
Multidisciplinary Working ◽  
Criticality Analysis

AbstractParenteral nutrition (PN) in the neonatal intensive care unit (NICU) involves a succession of risky processes. The objective was to identify and prioritize the risks associated with PN in order to improve the quality of the pathway. A failure modes, effects, and criticality analysis (FMECA) was used to identify potential PN pathway failure modes. A multidisciplinary working group conducted a functional analysis of the processes, then listed the failure modes (FM). The FM criticality was assessed on a scale from 1 to 5 for occurrence (O), severity (S), and detection (D). The risk priority number (RPN), ranging from 1 to 125, was calculated. The FMECA identified 99 FM (prescription (n=28), preparation (n=48), and administration (n=23)). The median RPN was 12, with scores ranging from 3 to 48. 25 % of the scores had an RPN>21.75.Among them, 12 were associated with prescription FM, 5 were associated with FM related to preparation and 8 were associated with a FM linked to administration. It allowed us to prioritize areas of potential quality improvement for parenteral nutrition of the preterm infant. The results demonstrated the need for the presence of a clinical pharmacist in the NICU to ensure the quality of PN process.

INVESTIGATION OF EROSION RESISTANCE OF GRAY-BROWN SOILS IN THE SOUTHEASTERN SLOPES OF THE GREATER CAUCASUS

2020 ◽  
pp. 47-49
Author(s):  
Aliyev Z.H.
Keyword(s):  
Erosion Resistance ◽  
Preventive Measures ◽  
Chemical Properties ◽  
Anthropogenic Factors ◽  
Erosion Process ◽  
Greater Caucasus ◽  
Sloping Lands ◽  
Set Up ◽  
Physical And Chemical ◽  
And Chemical Properties

In recent years, sharp changes have occurred in the state of sloping lands of Azerbaijan. There was tension from the influence of the anthropogenic factors on the mountain slopes. The fact that the erosion process is rein-forced in the research site. Due to lack of agrotechnical measures on the slopes erosion process has been strength-ened, soil flooded with soil, physical and chemical properties of the soil have deteriorated, nutritional elements are reduced, vegetation is reduced and destruction limit. For some reason, the purpose of the research was Aqsu, two land cuts were set up to determine the degree of actual erosion in the Qizmeydan village. prevent erosion intensity, take preventive measures to take and implement appropriate measures.

ANN-Based Relaying Algorithm for Protection of SVC- Compensated AC Transmission Line and Criticality Analysis of a Digital Relay

2020 ◽  
Vol 13 (3) ◽  
pp. 381-393
Author(s):  
Farhana Fayaz ◽  
Gobind Lal Pahuja
Keyword(s):  
Transmission Line ◽  
Failure Modes ◽  
Reactive Power ◽  
Circuit Breaker ◽  
Research Work ◽  
Back Propagation ◽  
Static Var Compensator ◽  
Data Set ◽  
Ac Transmission ◽  
Criticality Analysis

Background:The Static VAR Compensator (SVC) has the capability of improving reliability, operation and control of the transmission system thereby improving the dynamic performance of power system. SVC is a widely used shunt FACTS device, which is an important tool for the reactive power compensation in high voltage AC transmission systems. The transmission lines compensated with the SVC may experience faults and hence need a protection system against the damage caused by these faults as well as provide the uninterrupted supply of power.Methods:The research work reported in the paper is a successful attempt to reduce the time to detect faults on a SVC-compensated transmission line to less than quarter of a cycle. The relay algorithm involves two ANNs, one for detection and the other for classification of faults, including the identification of the faulted phase/phases. RMS (Root Mean Square) values of line voltages and ratios of sequence components of line currents are used as inputs to the ANNs. Extensive training and testing of the two ANNs have been carried out using the data generated by simulating an SVC-compensated transmission line in PSCAD at a signal sampling frequency of 1 kHz. Back-propagation method has been used for the training and testing. Also the criticality analysis of the existing relay and the modified relay has been done using three fault tree importance measures i.e., Fussell-Vesely (FV) Importance, Risk Achievement Worth (RAW) and Risk Reduction Worth (RRW).Results:It is found that the relay detects any type of fault occurring anywhere on the line with 100% accuracy within a short time of 4 ms. It also classifies the type of the fault and indicates the faulted phase or phases, as the case may be, with 100% accuracy within 15 ms, that is well before a circuit breaker can clear the fault. As demonstrated, fault detection and classification by the use of ANNs is reliable and accurate when a large data set is available for training. The results from the criticality analysis show that the criticality ranking varies in both the designs (existing relay and the existing modified relay) and the ranking of the improved measurement system in the modified relay changes from 2 to 4.Conclusion:A relaying algorithm is proposed for the protection of transmission line compensated with Static Var Compensator (SVC) and criticality ranking of different failure modes of a digital relay is carried out. The proposed scheme has significant advantages over more traditional relaying algorithms. It is suitable for high resistance faults and is not affected by the inception angle nor by the location of fault.

scholarly journals Prediction of Pest Insect Appearance Using Sensors and Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4846
Author(s):  
Dušan Marković ◽  
Dejan Vujičić ◽  
Snežana Tanasković ◽  
Borislav Đorđević ◽  
Siniša Ranđić ◽  
...  
Keyword(s):  
Machine Learning ◽  
Relative Humidity ◽  
Weather Conditions ◽  
Daily Basis ◽  
Machine Learning Algorithms ◽  
Lower Percentage ◽  
Timely Manner ◽  
Proposed Model ◽  
Set Up ◽  
Accuracy Of Prediction

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

Operation and approximation based on the history of failure modes recorded by SCADA system of Amougdoul Moroccan wind farm using FMECA maintenance model

2021 ◽  
pp. 0309524X2199245
Author(s):  
Kawtar Lamhour ◽  
Abdeslam Tizliouine
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Failure Modes ◽  
Wind Farms ◽  
Scada System ◽  
History Of ◽  
Criticality Analysis ◽  
Maintenance Model ◽  
Reliability And Availability ◽  
Critical Subsystems

The wind industry is trying to find tools to accurately predict and know the reliability and availability of newly installed wind turbines. Failure modes, effects and criticality analysis (FMECA) is a technique used to determine critical subsystems, causes and consequences of wind turbines. FMECA has been widely used by manufacturers of wind turbine assemblies to analyze, evaluate and prioritize potential/known failure modes. However, its actual implementation in wind farms has some limitations. This paper aims to determine the most critical subsystems, causes and consequences of the wind turbines of the Moroccan wind farm of Amougdoul during the years 2010–2019 by applying the maintenance model (FMECA), which is an analysis of failure modes, effects and criticality based on a history of failure modes occurred by the SCADA system and proposing solutions and recommendations.

Fuzzy risk assessment for electro-optical target tracker

2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Linear Equations ◽  
Mode Analysis ◽  
Failure Behavior ◽  
Membership Functions ◽  
Design And Development ◽  
Effect Analysis ◽  
Content Type ◽  
Criticality Analysis

Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

Development of Electromagnetic Swirling Flow in Immersion Nozzle in Continuous Casting Process of Steel

2011 ◽  
Vol 295-297 ◽  
pp. 1284-1288 ◽  
Author(s):  
De Wei Li ◽  
Zhi Jian Su ◽  
Li Wei Sun ◽  
Katsukiyo Marukawa ◽  
Ji Cheng He
Keyword(s):  
Continuous Casting ◽  
Swirling Flow ◽  
Casting Process ◽  
Continuous Casting Process ◽  
New Process ◽  
Electromagnetic Generator ◽  
Set Up ◽  
The Magnetic Field ◽  
Immersion Nozzle

Swirling flow in an immersion nozzle is effective on improving quality of casting block and casting speed in continuous casting process of steel. However, a refractory swirl blade installed in the nozzle is liable to cause clogging, which limit the application of the process. In this study a new process is proposed, that is a rotating electromagnetic field is set up around an immersion nozzle to induce a swirling flow in it by Lorentz force. New types of swirling flow electromagnetic generator are proposed and the effects of the structure of the generator, the coil current intensity and frequency on the magnetic field and on the flow field in the immersion nozzle are numerically analyzed.

Criticality Analysis for Maintenance Purposes of Platform Supply Vessels in Remote Areas

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
A. Marhaug ◽  
A. Barabadi ◽  
E. Stagrum ◽  
K. Karlsen ◽  
A. Olsen ◽  
...  
Keyword(s):  
Failure Modes ◽  
Oil And Gas Industry ◽  
Spare Parts ◽  
Acceptable Level ◽  
Component Level ◽  
Screening Process ◽  
Essential Information ◽  
Remote Areas ◽  
Critical Components ◽  
Criticality Analysis

The oil and gas industry is pushing toward new unexplored remote areas, potentially rich in resources but with limited industry presence, infrastructure, and emergency preparedness. Maintenance support is very important and challenging in such remote areas. A platform supply vessel (PSV) is an essential part of maintenance support. Hence, the acceptable level of its availability performance is high. Identification of critical components of the PSV provides essential information for optimizing maintenance management, defining a spare parts strategy, estimating competence needs for PSV operation, and achieving the acceptable level of availability performance. Currently, there are no standards or guidelines for the criticality analysis of PSVs for maintenance purposes. In this paper, a methodology for the identification of the critical components of PSVs has been developed, based on the available standard. It is a systematic screening process. The method considers functional redundancy and the consequences of loss of function as criticality criteria at the main and subfunction levels. Furthermore, at the component level, risk tools such as failure modes, effects and criticality analysis (FMECA), and fault tree analysis (FTA) will be applied in order to identify the most critical components. Moreover, the application of the proposed approach will be illustrated by a real case study.

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