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Go to Editorial ManagerThis work has studied the size of the mean time between failures (MTBF) because it has a vital role in assessing reliability in manufacturing systems. Previous studies have indicated that the reliability value depends on the size of MTBF, so they indicated only 11 types of time that reliability value depends on, and they used methods of DFR and RCM to enhance the reliability level. To assess and increase reliability value, this work referred to the four main times: mean time between failures (MTBF), mean time to diagnosis (MTTD), mean time to repair (MTTR), and mean time to failure (MTTF) in more detail. Also, it designed a new arrangement of failure notification time, failure diagnosis time, downtime, failure repair, testing time, and recovery periods for ongoing operations in manufacturing systems through a new redistribution of 19 times and time intervals in detail between the four main times, so it revealed and added 8 types of other times and time intervals more than previous studies because they have vital roles in increasing reliability value. Thus, the new arrangement contains two parallel pathways and 19 types of times and time intervals. The first pathway represents 5 positions and 11 types of start and end times; the second pathway represents 4 positions and 8 time intervals. Consequently, MTBF becomes longer because the new arrangement shortens the time distances between the start of failure and repair process end, between diagnosis end and test, and between inspection end and the system's return to normal operating conditions. The motivations are to raise the reliability value, quality level, and effective maintenance and save costs. This work used the data collection and analysis method. The results showed that there is a higher reliability for manufacturing systems when the time arrangement is better, MTBF is longer, MTTD is shorter, MTTR is smaller, MTTF is longer, and the error rate is lower.
The research proposed a developed methodology for evaluation the system performance in uncertainty associated with traditional modelling methodology is focused on either load L or resistance R variability, but not both. A two-dimensional (2D) fuzzy set (traditional model), represent with the one dimension for universe of discourse (in x-direction) and the second dimension of his membership degree (in y-direction), is not full sufficient to handle both, load and resistance variation of system performance. The theoretical principle basis of this research is based on development of the three dimensional (3D) of fuzzy set that includes system performance variability in load and resistance from two dimensional. The proposed methodology (traditional model) extends the acceptance level of partial performance of system concept to a 3D-dimantion representation. This representation allows to capturing the changing of preferences of decision makers in load and resistance. The major objective of the research is to proposed the original methodology for evaluate system performance and management that is capable of; (a) addressing uncertainty caused by load and resistance variability and ambiguity; (b) integrating objective and subjective evaluation; and (c) assisting system performance management decision making based on a more detailed certainty evaluation of load and resistance variability. The study proposed two models for fuzzy reliability performance indexes: first traditional model included (I) 2D fuzzy reliability-vulnerability Rv index, (II) 2D fuzzy robustness Ro index; the second developed model (i) 3D fuzzy reliability-vulnerability Rv index, (ii) 3D fuzzy robustness Ro index; and comparing between them. These indexes have the capability of evaluating the operational performance of complex systems. Proposed methodology is illustrated by using the Al-Wathba Water Supply System (WWSS) as a case study.
This research is devoted to design and implement a Supervisory Control and Data Acquisition system (SCADA) for monitoring and controlling the corrosion of a carbon steel pipe buried in soil. A smart technique equipped with a microcontroller, a collection of sensors and a communication system was applied to monitor and control the operation of an ICCP process for a carbon steel pipe. The integration of the built hardware, LabVIEW graphical programming and PC interface produces an effective SCADA system for two types of control namely: a Proportional Integral Derivative (PID) that supports a closed loop, and a traditional open loop control. Through this work, under environmental temperature of 30°C, an evaluation and comparison were done for two types of controls tested at low soil moisture (48%) and high soil moisture (80 %) to study the value of current, anode voltage, pipe to soil potential (PSP) and consumed power. The results show an decrease of 59.1% in consumed power when the moisture changes from the low to high level. It was reached that the closed loop controller PID is the best solution in terms of efficiency, reliability, fast response and power consumption.
In an original article, an addition was made to the well-known Taguchi’s methodical design literature by proposing how Poisson distribution may be incorporated into the Taguchi method for enhanced performance analysis in optimization. While the article is recent, it was found compelling enough to apply this novel concept of Poisson distribution to a growing area of maintenance research known as maintenance downtime analysis. Consequently, this paper contributes to the expanding research neighborhood through a Taguchi optimization method based on Poisson distribution related to the maintenance process optimization. A valuable method to optimize maintenance downtime was developed wherein the Poisson distribution was used to achieve the probability of maintenance downtime. An important foundation of the method is the Taguchi scheme. These elements were transformed into the factor-level design of the Poisson enhanced Taguchi scheme while the framework was tested using data from a process industry for validation. Interesting, the Taguchi's signal-to-noise quotient led to an enhanced set of limiting factors for better reliability of the system as G1H1I1J1K3. By interpretation, the following was found: downtime (204.61 mins), probability density function (0.00187), and cumulative density function (0.00776). The combination of these factors and levels will enhance maintenance downtime in the process industry as a result of their contributions. The outcome revealed the competence of the model to optimization schemes.
This study evaluates the performance of bridge projects in Iraq using international performance evaluation standards set by USAID. The assessment focuses on two major bridge projects in Baghdad: the Bridge Project over the Army Canal and the Design and Implementation Project for developing the Shaljia and Tobji Intersection. The evaluation standards include relevance, efficiency, effectiveness, impact, and sustainability. Data collected from these projects were analyzed to measure performance against these standards. The results revealed significant gaps between both projects' expected and actual performance. The Bridge Project over the Army Canal showed moderate performance in relevance and sustainability but had substantial weaknesses in effectiveness. The Shaljia and Tobji, Intersection Development project, exhibited major weaknesses across all standards. The study concludes a critical need for better planning, improved resource utilization, enhanced stakeholder communication, and more effective monitoring and evaluation mechanisms to address these performance gaps and achieve desired project outcomes. These findings highlight the importance of adopting comprehensive and adaptable evaluation standards to improve the efficiency and effectiveness of infrastructure projects in Iraq. The research provides valuable insights for stakeholders involved in bridge projects, emphasizing the need for ongoing improvement in project management practices to ensure infrastructure reliability and safety.
This study simulates a free-space optical communication system that uses optical beams with varying responses to atmospheric disturbances to secure transmitted data. Atmospheric turbulence was modeled with high accuracy to replicate real-world conditions closely. Non-diffracting beams were generated and used to represent optical beams and compared in two scenarios, conventional data transmission, and optifusion data protection. This approach facilitated a comprehensive analysis of the transmission environment and the effectiveness of optifusion, identifying the most suitable non-diffracting beam types for secure data propagation. By analyzing the values of key performance metrics of the selected non-diffracting beams across different weather conditions and long propagation distances, the study demonstrated the simulation system's reliability and the optifusion method's effectiveness in enhancing data security. The results showed that non-diffracting beams resist atmospheric turbulences strongly, emphasizing their potential for secure, long-range free-space optical communications.
Power outages are a common and persistent problem in Iraq, significantly impacting various aspects of life and business. These interruptions disrupt routine household tasks and hinder more complex technical operations in industries and services. Emphasizing the need for careful management and proactive solutions. This paper introduces a real-world time series dataset for Baghdad city, including historical outages, weather conditions (such as temperature), and power overloads, and analyzes the correlation among these parameters in different seasons. The research uses this dataset to train one-dimensional Convolutional Neural Networks (1D CNN) to find patterns and relationships that can accurately predict when power outages can happen in the long term and short term to improve the management of the Baghdad electricity grid through data-driven networks. This model was evaluated using performance metrics, and the results show that CNN is accurate in predicting outages in the short term with a Mean Absolute Error (MAE) of (0.0077), whereas, in the long term, it has achieved an MAE of (0.0775). These predictive models have the potential to facilitate the development of proactive measures aimed at reducing the impact of power outages by anticipating potential outages in advance. This research focuses on enhancing the reliability and efficiency of Baghdad's electricity supply, ultimately contributing to economic growth and stability.
The hydraulic characteristics of dams can be predicted with high precision and reliability of physical and numerical models depending on accurate hydraulic data. The model is operated and simulated to get a more efficient, optimized utilization of the dam. This research included a comprehensive overview and literature examination of the Makhool Dam which is considered one of the most important dams under construction in Iraq. Previous studies of the dam focused on different topics in the operation of the dam and analyses of its properties, part of which focused on the dam ability to manage flood and how it works best with other dams in critical times, and another part studied the properties of the stilling basin, velocity in the dam reservoir, pressure, seepage and other characteristics that affect the operating the dam. Despite this research and the variety of topics discussed, there is no well-established research on the operation of the bottom and emergency spillway of the dam by using computational fluid dynamics (CFD) simulation software. CFD is considered an essential tech because it has an important influence in determining the hydraulic properties of a spillway and studying its effectiveness under different operating conditions. Because the spillway is an important element in the dam body, the research highlighted the necessity of performing a simulation using appropriate CFD software for this part. This research has also reviewed previous research on CFD software and their ability to simulate previously constructed or under-construction dams to analysis of its hydraulic properties.
Platinum, copper, and nickel were founded the best metals used in resistance temperature detectors RTDs. They commonly used in laboratory and industrial applications because they provide accurate and reliable measurements in a wide temperature range from (- 200 to 850 °C). They have high conductivity, sensitivity, and hardness to resist strain shock, pressure, and vibration. The accuracy level of them depends on reliability, stability, repeatability, linearity, and response to time. This study aims to determine and compare the accuracy of these three metals in regarding to their features which include stability, repeatability, and response time. The study has gathered and analyzed the data of these suitable and precise metals and compared with each other. The results showed that platinum is widely needed for RTDs due to its precision, stability, higher accuracy, and linearity output, while copper and nickel are not stable or repeatable as platinum. It was indicated that temperature coefficient of resistance TCR for nickel is bigger and for copper is medium, but for platinum is lower.
This study concerns utilization of nonlinear finite element method for to evaluate the role of longitudinal soffit-bonded CFRP strips in elevating the shear behavior of RC beams without stirrups. All beams cross-sections were of 150 mm breadth and 200 mm depth, the overall length was 1500 mm with clear span 1300 mm. One beam was provided by minimum web reinforcement according to the ACI 318M-14, while the other five were without web reinforcement but externally strengthened by a variety of CFRP-strip combinations consisting of longitudinal soffit-bonded strips. The predictions of a proposed ANSYS (version 14.5) model for six of the test beams including modeling of concrete, steel rebars, CFRP strips and supports and loading steel plates, by SOLID65, LINK180, SHELL41 and SOLID185 elements, respectively, show high agreements with experimental evidence, which stands as a definite witness to the efficiency and reliability of the present numerical model.
As a result of the tremendous development taking place in modern systems and technologies in the field of electronic monitoring. Intelligent monitoring, decision making, and automated response systems have become common subjects at this time, especially after the development of machines responsible for these processes. Traffic surveillance is a trend goal nowadays using different techniques and equipment. In this article, real-time Object detection and tracking techniques were proposed for traffic surveillance using image processing techniques. A state was specifically examined for its ability to detect and count passing motorcycles on a highway in a specific area. The results showed good reliability, with a frame processing time of approximately about (30 ms) and the achievement of real-time performance. The main contribution of this article is reaching the best result implemented by the performance the real-time process using image process technique and tracking the object by depending on the sequencing of frames and can stands with rationally not so powerful machines. Several tools have been used for different types of necessary tasks that will be part of the required application such as Python 3.7; which was used to build the basic algorithms,Visual studio code (VSC) as an Integrated Development Environment (IDE), and Anaconda navigator for downloading many useful libraries. The specifications of the used device were Intel(R) Core (TM) i7- 10750H CPU @ 2.60GHz 2.59 GHz, RAM 16.0 GB, NVIDIA GeForce GTX 1650 GPU, 64-bit operating system, x64-based processor.