ORE addresses various kinds of losses associated with manufacturing system which can be targeted for initiating improvements. Evaluating ORE will is helpful to the decision maker(s) for further analysis and continually improves the performance of the resources. Overall Resource Effectiveness (ORE) encompasses seven factors are; performance, quality rate, readiness, changeover efficiency, availability of material and availability of manpower. In this research Job shop production of General Company for hydraulic industries, with focus on Damper and Tasks Factory (DTF)is tested as a case study for two of the most customer demand rear dampers (Samaned and Nissan). Data are collected and analyzed for years 2016-2017 to evaluate of ORE values. Results show that process performance factor among other seven factors have the less value causing the highest loss in ORE decrease. Where the highest ORE value is (58.6%) for Nissan and (69.3) for Samaned rare production. Also, time loss due to set up time is detected where it ranges from 3% to about 13% per month for the above mentioned two tested dampers. Results are generated employing Minitab Version 17, Quality Companion Version 3 soft wares. It is recommended to introduce SMED (Single Minute Exchange of Dies) concept that could decrease losses in set up time .Also improvements in maintenance programs are vital, and above all improving process performance values is essential by employing lean manufacturing that result in fast outcomes ,and TQM process improvement strategy for long term outcomes these two process performance strategies may enhance ORE values therefore, decrease losses, and consequently increase quality and productivity.
Cosmetic surgery is more prevalent in the world in recent years. A beautiful and flawless face is everyone's dream. Aging, environmental factors, disease, or poor diet are among the factors that influence body wrinkles. Various methods are used to reduce these lines. It can be said that the simplest and most effective solution is to inject cosmetic fluids into these areas. But, due to the increase in facial injections using cosmetic fluids, which are considered toxins, the risk of injury to the surrounding facial nerves and injury to one of the main facial nerves is increasing, creating a catastrophe or deformation in the face irreversibly. Deep learning algorithms have been used to determine whether cosmetic fluids are injected or not. Deep Convolutional Neural Networks (CNNs), VGG16, ResNet....etc deep learning algorithms have demonstrated excellent performance in terms of object detection, picture classification, and semantic segmentation. all the suggested approach consists of three stages: feature extraction, training, and testing/validation. Deep learning technology is used to train and test the system with before and after photographs. Numerous investigations have been carried out using various deep learning algorithms and databases the main goal is to attain maximum accuracy to ensure that injected cosmetic fluids by specialists have been injected in safe areas in addition to facial recognition and determining whether or not the person received an injection. The most used databases are IIITD plastic surgery and HDA_Plastic surgery.
The porous Titanium is characterized by high permeability which can assure the ingrowth of bone tissues, and consequently results in a good bonding between the metallic implant and the bone. In this work, Silicon element was added to the Commercially Pure Titanium at different weight percent of (2, 4, 6, 8 and 10) to investigate its effect on the porosity percentage, mechanical properties of the resulted samples. XRD analysis stated that at (Si) content lower than (2 wt%) the alloy is single phase (α- Ti alloy), as the Silicon content increased, in addition to (αphase), (Ti5Si3) intermetallic compound developed in the alloy. Porosity measurement results showed that the porosity percentage increases with the increase in Silicon content. Wear results stated that the wear rate increases with the increase in silicon content due to the increase in porosity percentage while the hardness results stated that there is no significant effect for Ti5Si3 intermetallic compound on improving the hardness of the samples. This is attributed to its low percent and the major effect of porosity on hardness which declined the effect of Ti5Si3 by reducing the hardness of the alloy compared with the master sample. The obtained results of the (yield strength, ultimate compressive strength and Young’s modulus) were within the values that match bone’s properties. This means these materials are suitable for biomedical application
In the current article, an experimental investigation has been implemented of flow and heat transfer characteristics in a parabolic trough solar collector (PTSC) using both nano-fluids and artificial neural networks modeling. Water was used as a standard working fluid in order to compare with two different types of nano-fluid namely, nano-CuO /H2O and nano-TiO2/ H2O, both with a volume concentration of 0.02. The performance of the PTSC system was eval-uated using three main indicators: outlet water temperature, useful energy and thermal efficiency under the influence of mass flowrate ranging from 30 to 80 Lt/hr. In parallel, an artificial neural network (ANN) has been proposed to predict the thermal efficiency of PTSC depending on the experimental re-sults. An Artificial Neural Network (ANN) model consists of four inputs, one output parameter and two hidden layers, two neural network models (4-2-2-1) and (4-9-9-1) were built. The experimental results show that CuO/ H2O and TiO2/H2O have higher thermal performance than water. Overall, it was veri-fied that the maximum increase in thermal efficiency of TiO2/H2O and CuO/H2O compared to water was 7.12% and 19.2%, respectively. On the oth-er hand, the results of the model 4-9-9-1 of ANN provide a higher reliability and accuracy for predicting the Thermal efficiency than the model 4-2-2-1. The results revealed that the agreement in the thermal efficiency between the ANN analysis and the experimental results about of 91% and RMSE 3.951 for 4-9-9-1 and 86% and RMSE 5.278 for 4-2-21.
Since concrete is one of the most popularly utilized building mixtures in construction, a high demand of natural resources is significantly emerged. Therefore, a skyrocketed attention has been paid to create new opportunities for the use of recycle materials to develop a new construc-tion substance with more satisfactory properties. The use of waste products in concrete is not only economical, but it helps in solid waste management as well. Among various properties of concrete, thermal conductivity is a crucial factor that plays an important role in in building insu-lation by evaluating a material's capacity to transfer heat. This paper aims to review the potential application of waste materials in concrete as additive ingredients and investigate the effect of this waste material on thermal conductivity of concrete. The review of literature revealed that the application of most of the waste materials exhibited an obvious potential as thermal insulator. However, further investigated work is needed to highlight the advantages of utilizing waste mate-rials in concrete containing various type of waste materials
The extensive global competition between companies and the development of new industrial technologies have greatly contributed to the current competitive conditions Like industrial companies, customers demand high quality products, low prices and better performance. This fierce competition has led to concerns about improved product design. This development is based on GQFD. Model of this developed Water pump is employed by CAD solid model (version 7). In order to achieve competition and high quality and high performance in the Iraqi market. GQFD demonstrates the balance between product development and environmental protection. Used a water pump for a home air cooler as a case study. Data is collected and distributed using personal interview methods and questionnaire forms to indicate customer requirements. The data is then analyzed using Pareto chart and AHP to prioritize customer needs. These priorities are then placed in house of quality and matrix of relationships between customer requirements and technical characteristics is established. The product has been developed from electrical to mechanical, in addition to using accumulated, stored and recycled materials; it also saves 20% of energy, thereby combining energy reduction with the use of damaged materials and their re-entry into work. As a result, the cost of pump manufacturing will decrease
Utilizing of subsurface water retention technology is a modern technique to retain and save the application water for sustainability of agricultural production through scheduling and management the irrigation processes. The goal of this paper is to evaluate the effect of the supplementary irrigation and rainfed water on improvement of economic water productivity for winter wheat. The experiment was conducted in open field, within Joeybeh Township, located in east of the Ramadi City, in Anbar Province, for the growing season 2018-2019. Two plots were used for comparison process, the first plot where membrane trough below the root depth was installed and supplementary irrigation system was conducted beside the rainfed water and according to scheduling the irrigation process as checkbook method. While in second plot, the membrane trough was installed and only rainfed water was depend on. Cultivated date of winter wheat was December, 20th, 2018, and the harvest date was May, 10th, 2019. The obtained result was showed that the crop yield and economic water productivity from the first plot and the second plot were equaled to 0.52 kg/m2 and 0.35 kg/m2, and 930 ID/m3 and 800 ID/m3, respectively. The increasing value of crop yield and economic water productivity in the first plot was more than that in the second plot by 49 % and 16 %, respectively. The benefits of applying supplementary irrigation system with installing the new techniques of retaining the applied water were sufficient in improvement the crop yield and accordingly improved value of the economic water productivity.
Lean is a powerful process improvement strategy that is widely used to improve different processes. In this Paper, lean manufacturing as process improvement strategy is employed throughout relative tools and techniques as VSM, 5S, and standard work. These tools and techniques are employed to identify measure and evaluate processes. Job shop production of General Company for hydraulic industries, with focus on Damper and Tasks Factory (DTF) is tested as a case study for the two most customer demanded rear dampers of Samaned and Nissan. Data analysis shows different issues Work-In-Process (WIP) issues causing under/ over and production discrepancy. Improvements are introduced throughout WIP developments and 5S techniques. Results show that these developments may result in reduction of 65% WIP waiting time for Nissan and 58% of Samaned rear dampers. An increase in Overall Work Efficiency (OWE) could result in by 10% for Nissan, and 2% for Samaned dampers While 5S may result in improvements by 50% production processes and 43% assembly processes for Set in order , and by 33% in both production and assembly processes for standardize. Data where analyzed and further results are generated using software's are; Minitab Version 17, Quality Companion Version 3, and Edraw-Max Version 7.
This study assessed the temporal and spatial water quality variability to reveal the characteristics of the Shatt Al-Arab River, Basrah, Iraq. A total of 14 water quality parameters (water temperature (T), pH, electrical conductivity (EC), Alkanets (Alk), total dissolved solids (TDS), turbidity (Tur), total hardness (TH), calcium (Ca), magnesium (Mg), chloride (Cl), sulphate (SO4), total suspended solids (TSS), sodium (Na), and potassium (k)) were analyzed Use of multivariate statistical methods in a total of three stations for the period 2016-2017. In this study was use a statistical approach to determine the water quality using the Pearson Correlation Index (PCI), Principal component analysis (PCA), and Factor Analysis (FA) were used to analyze the data. Main water pollutant sources were wastewater from agricultural drainage and industrial wastewater. Significant relationships recorded between the investigated parameters based on the results of PCI, at the 0.01 and 0.05 significance levels. Per the FA results, 77.1 % of the total variance explained by two factors.