Structure and Performance Attributes Optimization and Ranking of Gamma Irradiated Polymer Hybrids for Industrial Application

Serbaya, Suhail H.; Abualsauod, Emad H.; Basingab, Mohammed; Bukhari, Hatim; Rizwan, Ali; Mehmood, Malik Sajjad

doi:10.3390/polym14010047

Cited by 6 publications

(6 citation statements)

References 34 publications

(50 reference statements)

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“…Numerous investigations have been conducted, and the results of those studies have uncovered a variety of elements that lead to the weaker weld lines of homopolymers [ 20 , 21 , 22 ]. Quantifying the contents of each bin allowed for the calculation of this size distribution.…”

Section: Methodsmentioning

confidence: 99%

“…To create test specimens with and without weld lines, a semi-automatic plunger-type injection molding machine was used. The weld line coefficient (WLC) is the value that is derived by comparing the characteristics of the sample that contains the weld line to those of the sample that does not include the weld line [ 22 ]. This occurs when two samples are prepared under identical conditions.…”

Section: Methodsmentioning

confidence: 99%

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Optimization of Polyolefin-Bonded Hydroxyapatite Graphite for Sustainable Industrial Applications

Bakhsh

2023

Polymers

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As a means of introducing environmental responsibility to industrial applications, the usage of biobased composite materials has been encouraged in recent years. Polymer nanocomposites utilize polyolefins increasingly as a matrix, owing to the diversity in their features and prospective applications, even though typical polyester blend materials, such as glass and composite materials, have garnered greater attention from researchers. The mineral hydroxy-apatite, or Ca10(PO4)6(OH)2, is the primary structural component of bone and tooth enamel. Increased bone density and strength result from this procedure. As a result, nanohms are fabricated from eggshells into rods with very tiny particle sizes. Although there have been many papers written on the benefits of HA-loaded polyolefins, the reinforcing effect of HA at low loadings has not yet been taken into account. The purpose of this work was to examine the mechanical and thermal characteristics of polyolefin-HA nanocomposites. These nanocomposites were built out of HDPE and LDPE (LDPE). As an extension of this work, we investigated what would happen when HA is added to LDPE composites at concentrations as high as 40% by weight. Carbonaceous fillers, including graphene, carbon nanotubes, carbon fibers, and exfoliated graphite, all play significant roles in nanotechnology owing to the extraordinary enhancements in their thermal, electrical, mechanical, and chemical properties. The purpose of this study was to examine the effects of adding a layered filler, such as exfoliated graphite (EG), to microwave zones that might have real-world applications for their mechanical, thermal, and electrical characteristics. Mechanical and thermal properties were significantly enhanced by the incorporation of HA, notwithstanding a minor decrease in these attributes at a loading of 40% HA by weight. A higher load-bearing capability of LLDPE matrices suggests their potential usage in biological contexts.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Optimization of Polyolefin-Bonded Hydroxyapatite Graphite for Sustainable Industrial Applications

Bakhsh

2023

Polymers

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“…is creates an intriguing gap that need to be addressed in further study and is something that has been done. In addition, our findings indicate that a number of AI techniques, such as NLP (machine-human interactions), TS (optimization, robot dynamics, and programming that focuses on creating intelligent robots), and MDP, require additional research and the adoption of these techniques in the industrial sector (a framework for modelling the decision-making process) [21][22][23][24][25].…”

Section: Limitations and Findingsmentioning

confidence: 97%

Performance Optimization of Industrial Supply Chain Using Artificial Intelligence

Alomar

2022

Computational Intelligence and Neuroscience

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Nowadays, organized retailing has witnessed a newer trend in the upcoming generations. Globally, these changes are attributed to growing family income, increased female participation, the transformation from joint to nuclear family structure, and technological advancements. Moreover, other variables such as lower supply chain costs, growing sales, rising consumer demands, changing market structure, and increasing competition also influenced supply chain networks. It is observed that the organizational nonlivestock supply chain performance is affected by strategic, operational, and environmental aspects. AI is helping to deliver powerful optimization capabilities, which are required for more accurate capacity planning, improved productivity, high quality, lower costs, and greater output, all while fostering safer working conditions. These benefits are all made possible thanks to the introduction of AI in supply chains. By conducting a comprehensive analysis of the relevant previous research, the purpose of this work is to determine the specific contributions that artificial intelligence (AI) has made to supply chain management. This research attempted to discover the present as well as possible AI strategies that may increase both the study of Supply Chain Management as well as the practice of it. This was done in order to solve the current scientific gap of AI in Supply Chain Management. It was also found that there are holes in the existing study that need to be filled by more scientific investigation. To be more exact, the following four facets were discussed: (1) the AI approaches that are most often used in Supply Chain Management; (2) the AI techniques that have the potential to be used in Supply Chain Management; (3) the Supply Chain Management subfields that have benefited from the application of AI so far; and (4) the subfields that have a high potential to be improved by AI. Identifying and evaluating articles from the four supply chain management domains of logistics, marketing, supply chain management, and manufacturing require the use of a predetermined set of inclusion and exclusion criteria. In this study, insights are provided via the use of methodical analysis and synthesis. A better understanding of these parameters not only improves the nonlivestock supply chain processes but also ensures competitive advantage. The present research aims to test the following elements that including supply chain speed, customer retention, supply chain management integration, and various management. The proposed work categorizes the performance of the supply chain using the Improved Feed Forward Network with Particle Swarm Optimization technique. Results indicate that inventory management, customer happiness, profitability, and client base identification are listed as competitive advantage elements. On the other hand, stakeholder satisfaction, innovation and learning, market performance, customer satisfaction, and financial success are the six recognized organizational performance criteria. Resultantly, the overall performance metrics of the proposed work is 94.12%, while accuracy rate, specificity, and sensitivity rate are found to be 94.12%, 92.15%, and 89.14%, respectively. The research can be helpful for industrial managers to optimize the performance of supply chain systems using artificial intelligence.

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“…Ultra-high molecular weight PE (UHMWPE) is the gold standard material for orthopedic industrial applications from last ten decades owing to its various properties including biocompatibility, high wear resistance, low friction coefficient, suitable stiffness, and fatigue resistance [ 1 , 2 , 3 , 4 ]. However, the osteolysis and aseptic loosening are the critical disadvantages which limit the service life of prosthesis.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Attribute Decision-Making Model for the Selection of Polymer-Based Biomaterial for Orthopedic Industrial Applications

et al. 2022

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The potential of quantifying the variations in IR active bands was explored while using the chemometric analysis of FTIR spectra for selecting orthopedic biomaterial of industrial scale i.e., ultra-high molecular weight PE (UHMWPE). The nano composites UHMWPE with multi-walled carbon nano-tubes (MWCNTs) and Mg-silicate were prepared and irradiated with 25 kGy and 50 kGy of gamma dose. Principal component analysis (PCA) revealed that first three principal components (PCs) are responsible for explaining the >99% of variance in FTIR data of UHMWPE on addition of fillers and/or irradiation. The factor loadings plots revealed that PC-1 was responsible for explaining the variance in polyethylene characteristics bands and the IR active region induced by fillers i.e., 440 cm−1, 456 cm−1, from 900–1200 cm−1, 1210 cm−1, 1596 cm−1, PC-2 was responsible for explaining the variance in spectra due to radiation-induced oxidation and cross linking, while the PC-3 is responsible for explaining the variance induced because of IR active bands of MWCNTs. Hierarchy cluster analysis (HCA) was employed to classify the samples into four clusters with respect to similarity in their IR active bands which is further confirmed by PCA. According to multi attribute analysis with PCA and HCA, 65 kGy irradiated sample is optimum choice from the existing alternatives in the group of irradiated pristine UHMWPE, UHMWPE/Mg-silicate irradiated with 25 kGy of gamma dose was the optimum choice for UHWMPE/Mg-silicate nano composites, and UHMWPE/γMWCNTs composites containing 1.0% dof γ MWCNTs for UHMWPE/MWCNTs nanocomposites, respectively. The results show the effectiveness of quantifying the variance for decision as far as optimization of biomaterials in orthopedic industrial applications is concerned.

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Structure and Performance Attributes Optimization and Ranking of Gamma Irradiated Polymer Hybrids for Industrial Application

Cited by 6 publications

References 34 publications

Optimization of Polyolefin-Bonded Hydroxyapatite Graphite for Sustainable Industrial Applications

Optimization of Polyolefin-Bonded Hydroxyapatite Graphite for Sustainable Industrial Applications

Performance Optimization of Industrial Supply Chain Using Artificial Intelligence

A Multi-Attribute Decision-Making Model for the Selection of Polymer-Based Biomaterial for Orthopedic Industrial Applications

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