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Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability)

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A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (15 June 2020) | Viewed by 56298

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Prof. Dr. Faiz Ahmad

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Guest Editor

Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Malaysia
Interests: nanocomposite; intumescent fire-retardant coating; medical devices; metal injection molding
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Othman B Mamat

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Co-Guest Editor

Universiti Teknologi PETRONAS, Malaysia
Interests: natural and advanced composite materials (metal-, polymer-, and ceramic-based); materials characterization and failure analysis

Assoc. Prof. Dr. Puteri Sri Melor

E-Mail Website
Co-Guest Editor

Universiti Teknologi PETRONAS, Malaysia
Interests: advanced materials; polymer and polymer composites; intumescent coatings

Special Issue Information

Dear Colleagues,

The Special Issue on “Selected Papers from ICPER-2020 (7th International Conference on Production, Energy and Reliability)” is being coordinated with the 7th International Conference on Production, Energy and Reliability (ICPER 2020), which will be held at the prestigious Borneo Convention Center Kuching, Sarawak on 14–16 July 2020. This conference has been organized under the umbrella of World Engineering, Science and Technology Congress (ESTCON), Universiti Teknologi PETRONAS since 2010.

The ICPER 2020 aims to gather researchers and industry practitioners to share new ideas, research results, and development experiences towards a sustainable Industrial Revolution 4.0 (IR 4.0).

Topics of interest for submission include but are not limited to: (Scope of Special Edition)

smart and advanced materials and their integrity; biomaterials; corrosion control and monitoring; industrial engineering and quality control; artificial intelligence in reliability and asset integrity; intelligent monitoring; advanced manufacturing processes in automotive applications; energy management; acoustics and signal processing; system integration; and big data analytics.

Prof. Dr. Faiz Ahmad
Prof. Dr. Othman B Mamat
Assoc. Prof. Dr. Puteri Sri Melor
Guest Editors

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

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Published Papers (10 papers)

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Research

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13 pages, 3944 KiB

Open AccessArticle

Structure Property Investigation of Glass-Carbon Prepreg Waste-Polymer Hybrid Composites Degradation in Water Condition

by Norlin Nosbi, Haslan Fadli Ahmad Marzuki, Muhammad Razlan Zakaria, Wan Fahmin Faiz Wan Ali, Fatima Javed and Muhammad Ibrar

Processes 2020, 8(11), 1434; https://doi.org/10.3390/pr8111434 - 10 Nov 2020

Cited by 3 | Viewed by 2171

Abstract

The limited shelf life of carbon prepreg waste (CPW) from component manufacturing restricts its use as a composite reinforcement fibre on its own. However, CPW can be recycled with glass fibre (GF) reinforcement to develop a unique remediate material. Therefore, this study fabricated (1) a glass fibre-carbon prepreg waste reinforced polymer hybrid composite (GF-CPW-PP), (2) a polypropylene composite (PP), (3) a carbon prepreg waste reinforced composite (CPW-PP), and (4) a glass fibre reinforced composite (GF-PP) and reported their degradation and residual tension properties after immersion in water. The polymer hybrid composites were fabricated via extrusion technique with minimum reinforce glass-carbon prepreg waste content of 10 wt%. The immersion test was conducted at room temperature using distilled water. Moisture content and diffusion coefficient (DC) were determined based on water adsorption values recorded at 24-h intervals over a one-week period. The results indicated that GF-PP reinforced composites retained the most moisture post-168 h of immersion. However, hardness and tensile strength were found to decrease with increased water adsorption. Tensile strength was found to be compromised since pores produced during hydrolysis reduced interfacial bonding between glass fibre and prepreg carbon reinforcements and the PP matrix. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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14 pages, 5565 KiB

Open AccessArticle

Mitigation of Chromium Poisoning of Ferritic Interconnect from Annealed Spinel of CuFe₂O₄

by Muhammad Aqib Hassan and Othman Bin Mamat

Processes 2020, 8(9), 1113; https://doi.org/10.3390/pr8091113 - 8 Sep 2020

Cited by 7 | Viewed by 3026

Abstract

Low-temperature solid oxide fuel cells permit the possibility of metallic interconnects over conventional ceramic interconnects. Among various metallic interconnects, the ferritic interconnects are the most promising. However, chromium poisoning in them adversely affects their performance. To resolve this issue, various coatings and pretreatment methods have been studied. Herein, this article encloses the coating of CuFe₂O₄ spinel over two prominent ferritic interconnects (Crofer 22 APU and SUS 430). The CuFe₂O₄ spinel layer coating has been developed by the dip-coating of both samples in CuFe₂O₄ slurry, followed by heat treatment at 800 °C in a reducing environment (5% hydrogen and 95% nitrogen). Additionally, both samples were annealed to further enhance their spinel coating structure. The morphological and crystallinity analysis confirmed that the spinel coating formed multiple layers of protection while annealing further reduced the thickness and improved the densities. Moreover, the area-specific resistance (ASR) and weight gain rate (WGR) of both samples before and after annealing was calculated using mathematical modeling, which matches with the experimental data. It has been noted that CuFe₂O₄ spinel coating improved the ASR and WGR of both samples which were further improved after annealing. This research reveals that the CuFe₂O₄ spinel is the promising protective layer for ferritic interconnects and annealing is the better processing technique for achieving the preferred properties. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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9 pages, 2163 KiB

Open AccessArticle

Diffusion Bonding of Al–Fe Enhanced by Gallium

by Asmawi Ismail, Warda Bahanan, Patthi Bin Hussain, Asmalina Mohamed Saat and Nagoor Basha Shaik

Processes 2020, 8(7), 824; https://doi.org/10.3390/pr8070824 - 12 Jul 2020

Cited by 11 | Viewed by 3090

Abstract

In this research, diffusion bonding was carried out to produce transition joints between mild steel A36 (Fe A36) and aluminium Al 5083 (AA5083) with the presence of gallium (Ga) as an interlayer between the two faying surfaces. The microstructural development and interfacial growth of intermetallic compounds at the interface layer between Fe A36 and AA5083 after the diffusion bonding process were investigated. The joining was performed by clamping the two materials with a Ga interlayer and then heated in a furnace. The interlayer developed from this diffusion heating in air condition provides an average thickness of 30 μm. Characterization of intermetallic compounds was conducted using SEM-EDX and XRD. The results showed that SEM-EDX confirmed the occurrence of interdiffusion of elements from Fe A36 and AA5083 present at interlayer. XRD analysis reveals the formation of Fe₃Al at the diffusion layer. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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19 pages, 3737 KiB

Open AccessArticle

Statistical Optimization by the Response Surface Methodology of Direct Recycled Aluminum-Alumina Metal Matrix Composite (MMC-Al_R) Employing the Metal Forming Process

by Azlan Ahmad, Mohd Amri Lajis, Nur Kamilah Yusuf and Syaiful Nizam Ab Rahim

Processes 2020, 8(7), 805; https://doi.org/10.3390/pr8070805 - 9 Jul 2020

Cited by 21 | Viewed by 3718

Abstract

In this study, the response surface methodology (RSM) and desirability function (DF) were utilized to optimize the recycling conditions of aluminum (AA6061) chips, in the presence of particulate alumina (Al₂O₃), to obtain a metal matrix composite of recycled aluminum (MMC-Al_R) using hot press forging processes. The effects of temperature (430–530 °C) and holding time (60–120 min) were investigated. The introduction of 2.0 wt. % of Al₂O₃ to the aluminum matrix was based on preliminary research and some pilot tests. This study employed the 2^k factorial design of experiments that should satisfy the operating temperatures (T) of 430 °C and 530 °C with holding times (t) of 60 min and 120 min. The central composite design (CCD) was utilized for RSM with the axial and center point to evaluate the responses to the ultimate tensile strength (UTS), elongation to failure (ETF), and microhardness (MH). Based on RSM, with the desirability of 97.6%, the significant parameters T = 530 °C and t = 120 min were suggested to yield an optimized composite performance with UTS = 317.99 MPa, ETF = 20.45%, and MH = 86.656 HV. Three confirmation runs were performed based on the suggested optimum parameters, and the error revealed was less than 25%. The mathematical models suggested by RSM could adequately describe the MMC-Al_R responses of the factors being investigated. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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12 pages, 2511 KiB

Open AccessArticle

Elastic Constants Prediction of 3D Fiber-Reinforced Composites Using Multiscale Homogenization

by S. Z. H. Shah, Puteri S. M. Megat Yusoff, Saravanan Karuppanan and Zubair Sajid

Processes 2020, 8(6), 722; https://doi.org/10.3390/pr8060722 - 22 Jun 2020

Cited by 13 | Viewed by 4400

Abstract

This paper presents a multi-scale-homogenization based on a two-step methodology (micro-meso and meso-macro homogenization) to predict the elastic constants of 3D fiber-reinforced composites (FRC). At each level, the elastic constants were predicted through both analytical and numerical methods to ascertain the accuracy of [...] Read more.

E_{x}

” and “

E_{y}

” with good accuracy; however, the analytical method under predicts the shear modulus “

G_{x y}

”. The elastic constants predicted through a multiscale homogenization approach can be used to predict the behavior of 3D-FRC under different loading conditions at the macro-level. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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17 pages, 2841 KiB

Open AccessArticle

An Artificial Intelligence Approach to Predict the Thermophysical Properties of MWCNT Nanofluids

by Balaji Bakthavatchalam, Nagoor Basha Shaik and Patthi Bin Hussain

Processes 2020, 8(6), 693; https://doi.org/10.3390/pr8060693 - 14 Jun 2020

Cited by 13 | Viewed by 2895

Abstract

Experimental data of thermal conductivity, thermal stability, specific heat capacity, viscosity, UV–vis (light transmittance) and FTIR (light absorption) of Multiwalled Carbon Nanotubes (MWCNTs) dispersed in glycols, alcohols and water with the addition of sodium dodecylbenzene sulfonate (SDBS) surfactant for 0.5 wt % concentration along a temperature range of 25 °C to 200 °C were verified using Artificial Neural Networks (ANNs). In this research, an ANN approach was proposed using experimental datasets to predict the relative thermophysical properties of the tested nanofluids in the available literature. Throughout the designed network, 65% and 25% of data points were comprehended in the training and testing set while the other 10% was utilized as a validation set. The parameters such as temperature, concentration, size and time were considered as inputs while the thermophysical properties were considered as outputs to develop ANN models of further predictions with unseen datasets. The results found to be satisfactory as the (coefficient of determination) R² values are close to 1.0. The predicted results of the nanofluids’ thermophysical properties were then validated with experimental dataset values. The validation plots of all individual samples for all properties were graphically generated. A comparison study was conducted for the robustness of the proposed approach. This work may help to reduce the experimental time and cost in the future. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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29 pages, 7303 KiB

Open AccessArticle

Investigating Vapour Cloud Explosion Dynamic Fatality Risk on Offshore Platforms by Using a Grid-Based Framework

by Usama Muhammad Niazi, Mohammad Shakir Nasif, Masdi Muhammad and Faisal Khan

Processes 2020, 8(6), 685; https://doi.org/10.3390/pr8060685 - 11 Jun 2020

Cited by 5 | Viewed by 4545

Abstract

The reliability of petroleum offshore platform systems affects human safety and well-being; hence, it should be considered in plant design and operation in order to determine its effect on human fatality risk. Methane Vapour Cloud Explosions (VCE) in offshore platforms are known to be one of the fatal potential accidents that can be attributed to failure in plant safety systems. Traditional Quantitative Risk Analysis (QRA) lacks in providing microlevel risk assessment studies and are unable to update risk with the passage of time. This study proposes a grid-based dynamic risk analysis framework for analysing the effect of VCEs on the risk of human fatality in an offshore platform. Flame Acceleration Simulator (FLACS), which is a Computational Fluid Dynamics (CFD) software, is used to model VCEs, taking into account different wind and leakage conditions. To estimate the dynamic risk, Bayesian Inference (BI) is utilised using Accident Sequence Precursor (ASP) data. The proposed framework offers the advantage of facilitating microlevel risk analysis by utilising a grid-based approach and providing grid-by-grid risk mapping. Increasing the wind speed (from 3 to 7 m/s) resulted in maximum increase of 21% in risk values. Furthermore, the integration of BI with FLACS in the grid-based framework effectively estimates risk as a function of time and space; the dynamic risk analysis revealed up to 68% increase in human fatality risk recorded from year one to year five. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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15 pages, 4752 KiB

Open AccessArticle

A Feed-Forward Back Propagation Neural Network Approach to Predict the Life Condition of Crude Oil Pipeline

by Nagoor Basha Shaik, Srinivasa Rao Pedapati, Syed Ali Ammar Taqvi, A. R. Othman and Faizul Azly Abd Dzubir

Processes 2020, 8(6), 661; https://doi.org/10.3390/pr8060661 - 2 Jun 2020

Cited by 80 | Viewed by 16292

Abstract

Pipelines are like a lifeline that is vital to a nation’s economic sustainability; as such, pipelines need to be monitored to optimize their performance as well as reduce the product losses incurred in the transportation of petroleum chemicals. A significant number of pipes would be underground; it is of immediate concern to identify and analyse the level of corrosion and assess the quality of a pipe. Therefore, this study intends to present the development of an intelligent model that predicts the condition of crude oil pipeline cantered on specific factors such as metal loss anomalies (over length, width and depth), wall thickness, weld anomalies and pressure flow. The model is developed using Feed-Forward Back Propagation Network (FFBPN) based on historical inspection data from oil and gas fields. The model was trained using the Levenberg-Marquardt algorithm by changing the number of hidden neurons to achieve promising results in terms of maximum Coefficient of determination (R²) value and minimum Mean Squared Error (MSE). It was identified that a strong R² value depends on the number of hidden neurons. The model developed with 16 hidden neurons accurately predicted the Estimated Repair Factor (ERF) value with an R² value of 0.9998. The remaining useful life (RUL) of a pipeline is estimated based on the metal loss growth rate calculations. The deterioration profiles of considered factors are generated to identify the individual impact on pipeline condition. The proposed FFBPN was validated with other published models for its robustness and it was found that FFBPN performed better than the previous approaches. The deterioration curves were generated and it was found that pressure has major negative affect on pipeline condition and weld girth has a minor negative affect on pipeline condition. This study can help petroleum and natural gas industrial operators assess the life condition of existing pipelines and thus enhances their inspection and rehabilitation forecasting. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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Review

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32 pages, 1158 KiB

Open AccessReview

Statistical Review of Microstructure-Property Correlation of Stainless Steel: Implication for Pre- and Post-Weld Treatment

by Musa Muhammed, Mazli Mustapha, Turnad Lenggo Ginta, Abdullah Musa Ali, Faizal Mustapha and Chima Cyril Hampo

Processes 2020, 8(7), 811; https://doi.org/10.3390/pr8070811 - 10 Jul 2020

Cited by 9 | Viewed by 3425

Abstract

For the past three centuries, there has been a very high demand for stainless steel for different applications, due to its corrosion resistance coupled with the good strength and low cost of the metal. Several welding techniques have been adopted in the fabrication of stainless steel, with the choice of welding technique hinged on the desired requirements. Advancement has been made in its dissimilar welding with other metals like aluminum, copper and titanium. While similar welding of stainless steel faces the challenge of weld metal property deterioration, dissimilar welding poses more serious challenges due to the differential in chemical composition and the thermophysical properties of the base metals. A review of the literature reveals that considerable progress has been made in the improvement of the properties of the weld joint by the application of several weld treatment processes. It was discovered that most of the researchers focused on the effect of these weld treatment processes on the properties of the weld joints, with little attempt to establish a relationship between the microstructure and properties. This review paper critically analyzed the effect of weld treatment processes on the properties of stainless steel in light of microstructure-property correlation. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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14 pages, 567 KiB

Open AccessReview

Thermal Performance Enhancement in Flat Plate Solar Collector Solar Water Heater: A Review

by Nurril Ikmal Shamsul Azha, Hilmi Hussin, Mohammad Shakir Nasif and Tanweer Hussain

Processes 2020, 8(7), 756; https://doi.org/10.3390/pr8070756 - 29 Jun 2020

Cited by 43 | Viewed by 11620

Abstract

Various studies to improve the thermal performance of flat plate solar collector (FPSC) solar water heater have been conducted, and more are currently in progress. This study aims to review existing methods on thermal performance enhancement for FPSC and discuss on heat-transfer enhancement using vibration and its potential application for FPSC. Ten methods for improving thermal performance are identified, which include applications of nanofluids, absorber coatings, phase change materials (PCM), thermal performance enhancers, FPSC design modifications, polymer materials, heat loss reduction, mini and micro channel and heat-transfer enhancement using vibration. An examination of heat-transfer enhancement using vibration in low frequency ranges for an evacuated-tube solar collector (ETSC) solar water heater system showed that it can potentially achieve heat-transfer enhancement of up to 78%. Nevertheless, there is still a lack of research on the applications of heat-transfer enhancement using vibration on FPSC to date. Full article

(This article belongs to the Special Issue Selected Paper from ICPER-2020 (7th International Conference on Production, Energy and Reliability))

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