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Material cost reduction using cutting optimization Pro5 and enhanced N-BEATS deep learning forecasting: a case study
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Manufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L and 120 L electric water heaters. That is, Cutting Optimization Pro5 was used to specify optimal sheet sizes and cutting plans, minimizing waste and reducing production costs. At the same time, the Enhanced N-BEATS deep learning model was implemented to forecast future production quantities. The optimization results showed a significant reduction in wasted materials and production costs, allowing lower product prices. Thus, the forecasting results proved that the performance of the Enhanced N-BEATS model was much better than that of SARIMAX and Simple Linear Regression since the model showed the lowest prediction errors (pMAPE value for the 120 L product is equal to 0.040 and nMSE is equal to 0.016, while pMAPE for the 80 L product equals 0.091, and nMSE equals 0.007). The results show that combining cutting optimization and deep learning can create an efficient decision-support framework to improve production efficiency, lower production costs, and enhance production planning in industrial environments.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
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Publication Date
Wed Jan 01 2025
Journal Name
Opennano
Development and characterization of bilastine nanosuspension for enhanced dissolution in orodispersible films
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Abstract Bilastine, a second-generation antihistamine, is commonly prescribed for managing allergic rhinoconjunctivitis and urticaria due to its prolonged action. However, its therapeutic potential is constrained by poor water solubility and low oral bioavailability. This study aimed to enhance bilastine dissolution and patient compliance by formulating a nanosuspension-based orodispersible film (ODF). An anti-solvent precipitation method was employed to produce nanosuspension using different hydrophilic stabilizers (Soluplus®, Poloxamer 188, and PEG 6000). The influence of formulation parameters, such as the stabilizer ratio, the anti-solvent ratio, stirring speed, and the stabilizer type, on particle size and polydispersity index (PDI)

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Publication Date
Wed Jan 01 2020
Journal Name
Advanced Composites Letters
Enhanced thermal and electrical properties of epoxy/carbon fiber–silicon carbide composites
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The silicon carbide/carbon fiber (SiC/CF) hybrid fillers were introduced to improve the electrical and thermal conductivities of the epoxy resin composites. Results of Fourier transform infrared spectroscopy revealed that the peaks at 3532 and 2850 cm−1 relate to carboxylic acid O–H stretching and aldehyde C–H stretching appearing deeper with an increased volume fraction of SiC. Scanning electron microscopic image shows a better interface bonding between the fiber and the matrix when the volume fraction of SiC particles are increased. As frequency increases from 102 Hz to 106 Hz, dielectric constants decrease slightly. Dissipation factor (tan δ) values keep low a

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Optimization of Inventory Inflation Budget Based on Spare-parts and Miscellaneous Costs of a Typical Automobile Industry
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Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's

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Publication Date
Sun Apr 03 2022
Journal Name
Iraqi Journal Of Laser
On the use of Aluminium as a plasmonic material in polarization rotators based on a hybrid plasmonic waveguide
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: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The role of sports marketing in achieving the competitive superiority of the organization: a case study in a sample of the Iraqi Premier League clubs
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The organization of sporting activities at the local and international levels requires a lot of money, which has increased interest in marketing in the sports field, as it is one of the modern topics that represent the basic knowledge needed by the sports marketer and which represents one of the basic concepts to enhance the benefits and returns of sports clubs. The research problem was the weak awareness of the members of the administrative body of Iraqi sports clubs of the role of sports marketing in the dimensions of competitive superiority and not exploiting them in the optimal way that enables clubs to achieve competitive superiority. The research aims to know the role of sports marketing in competitive superi

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Application of the Holonic Manufacturing System using the Genetic Algorithm : Case Study in Lab 7 of the General Company for the Leather Industry
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The study aims to achieve several objectives, including follow-up scientific developments and transformations in the modern concepts of the Holistic Manufacturing System for the purpose of identifying the methods of switching to the entrances of artificial intelligence, and clarifying the mechanism of operation of the genetic algorithm under the Holonic Manufacturing System, to benefit from the advantages of systems and to achieve the maximum savings in time and cost of machines Using the Holistic Manufacturing System method and the Genetic algorithm, which allows for optimal maintenance time and minimizing the total cost, which in turn enables the workers of these machines to control the vacations in th

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Publication Date
Wed Mar 19 2025
Journal Name
Chemical Papers
Natural deep eutectic solvents as a green inhibitor of carbon steel corrosion in sulphuric acid
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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Cyber-security And Digital Forensics (ijcsdf)
Genetic Algorithm Approach for Risk Reduction of Information Security
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Nowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef

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