Huabo Wu^1,2, Jialiao Zhou³, Lan Huang^1,2,*, Zi Wang^1,2,*, Liming Tan^1,2, Jin Lv⁴, Feng Liu^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2675-2709, 2025, DOI:10.32604/cmes.2025.064854 - 30 June 2025

Abstract Nickel-based superalloys are indispensable for high-temperature engineering applications, yet their additive manufacturing (AM) is plagued by significant cracking defects. This review investigates crack failure mechanisms in AM nickel-based superalloys, emphasizing methodologies to evaluate crack sensitivity and compositional design strategies to mitigate defects. Key crack types—solidification, liquation, solid-state, stress corrosion, fatigue, and creep-fatigue cracks—are analyzed, with focus on formation mechanisms driven by thermal gradients, solute segregation, and microstructural heterogeneities. Evaluation frameworks such as the Rappaz-Drezet-Gremaud (RDG) criterion, Solidification Cracking Index (SCI), and Strain Age Cracking (SAC) index are reviewed for predicting crack susceptibility through integration of… More >

Saurabh Sanjay Singh^*, Rahul Joshi, Deepak Gupta

Journal on Artificial Intelligence, Vol.7, pp. 177-203, 2025, DOI:10.32604/jai.2025.065078 - 30 June 2025

Abstract This paper addresses the challenge of energy-conscious scheduling in modern manufacturing by formulating and solving the Energy-Conscious Flexible Job Shop Scheduling Problem. In this problem, each job has a fixed sequence of operations to be performed on parallel machines, and each operation can be assigned to any capable machine. The problem statement aims to schedule every job in a way that minimizes the total energy consumption of the job shop. The paper’s primary objective is to develop a reinforcement learning-based scheduling framework using the Advantage Actor-Critic algorithm to generate energy-efficient schedules that are computationally fast… More >

Seungmin Lee¹, Beomseong Kim², Heesung Lee^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1397-1415, 2025, DOI:10.32604/cmc.2025.066152 - 09 June 2025

Abstract This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing their performance to identify the most effective architecture. Input images are preprocessed using a Gaussian Mixture Model (GMM) to remove… More >

Song Gao, Shixin Liu^*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5623-5641, 2025, DOI:10.32604/cmc.2025.058334 - 19 May 2025

Abstract With the development of economic globalization, distributed manufacturing is becoming more and more prevalent. Recently, integrated scheduling of distributed production and assembly has captured much concern. This research studies a distributed flexible job shop scheduling problem with assembly operations. Firstly, a mixed integer programming model is formulated to minimize the maximum completion time. Secondly, a Q-learning-assisted co-evolutionary algorithm is presented to solve the model: (1) Multiple populations are developed to seek required decisions simultaneously; (2) An encoding and decoding method based on problem features is applied to represent individuals; (3) A hybrid approach of heuristic… More >

Ting-Yu Lin¹, Kuo-Chen Hung^2,*, Josef Jablonsky³, Kuo-Ping Lin¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1901-1927, 2025, DOI:10.32604/cmc.2025.063543 - 16 April 2025

Abstract VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) has been developed and applied for over twenty-five years, gaining recognition as a prominent multi-criteria decision-making (MCDM) method. Over this period, numerous studies have explored its applications, conducted comparative analyses, integrated it with other methods, and proposed various modifications to enhance its performance. This paper aims to delve into the fundamental principles and objectives of VIKOR, which aim to maximize group utility and minimize individual regret simultaneously. However, this study identifies a significant limitation in the VIKOR methodology: its process amplifies the weight of individual regret, and the calculated… More >

Ilesanmi Afolabi Daniyan^1,*, Rumbidzai Muvunzi², Festus Fameso³, Julius Ndambuki³, Williams Kupolati³, Jacques Snyman³

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1623-1648, 2025, DOI:10.32604/cmc.2025.062092 - 16 April 2025

Abstract This study evaluates the Fuzzy Analytical Hierarchy Process (FAHP) as a multi-criteria decision (MCD) support tool for selecting appropriate additive manufacturing (AM) techniques that align with cleaner production and environmental sustainability. The FAHP model was validated using an example of the production of aircraft components (specifically fuselage) employing AM technologies such as Wire Arc Additive Manufacturing (WAAM), laser powder bed fusion (L-PBF), Binder Jetting (BJ), Selective Laser Sintering (SLS), and Laser Metal Deposition (LMD). The selection criteria prioritized eco-friendly manufacturing considerations, including the quality and properties of the final product (e.g., surface finish, high strength,… More >

Josef Izák^1,*, Marek Benč², Petr Opěla²

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3115-3133, 2025, DOI:10.32604/cmes.2025.059234 - 03 March 2025

Abstract The paper deals with the FEM (Finite Element Method) simulation of rotary swaging of Dievar alloy produced by additive manufacturing technology Selective Laser Melting and conventional process. Swaging was performed at a temperature of 900°C. True flow stress-strain curves were determined for 600°C–900°C and used to construct a Hensel-Spittel model for FEM simulation. The process parameters, i.e., stress, temperature, imposed strain, and force, were investigation during the rotary swaging process. Firstly, the stresses induced during rotary swaging and the resistance of the material to deformation were investigated. The amount and distribution of imposed strain in… More >

Yuxuan Wu, Sirish Namilae^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2067-2090, 2025, DOI:10.32604/cmes.2024.059091 - 27 January 2025

Abstract Powder bed fusion (PBF) in metallic additive manufacturing offers the ability to produce intricate geometries, high-strength components, and reliable products. However, powder processing before energy-based binding significantly impacts the final product’s integrity. Processing maps guide efficient process design to minimize defects, but creating them through experimentation alone is challenging due to the wide range of parameters, necessitating a comprehensive computational parametric analysis. In this study, we used the discrete element method to parametrically analyze the powder processing design space in PBF of stainless steel 316L powders. Uniform lattice parameter sweeps are often used for parametric… More >

Tajmal Hussain, Jongwon Seok^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 231-250, 2025, DOI:10.32604/cmes.2024.056621 - 17 December 2024

Abstract Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence (AI) and internet of things (IoT) to enhance efficiency, reduce costs, and ensure product quality. In light of the recent advancement of Industry 4.0, identifying defects has become important for ensuring the quality of products during the manufacturing process. In this research, we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network (CNN) architectures: VGG16, VGG19, Xception, and Mobile-Net V2, compensating for their… More >

Prashanth K P^1,*, Rudresh M², Venkatesh N³, Poornima Gubbi Shivarathri⁴, Shwetha Rajappa⁵

Journal of Renewable Materials, Vol.12, No.12, pp. 2115-2134, 2024, DOI:10.32604/jrm.2024.055437 - 20 December 2024

Abstract This study explores the mechanical properties of a novel composite material, blending polylactic acid (PLA) with sea shells, through a comprehensive tensile test analysis. The tensile test results offer valuable insights into the material’s behavior under axial loading, shedding light on its strength, stiffness, and deformation characteristics. The results suggest that the incorporation of sea shells decrease the tensile strength of 14.55% and increase the modulus of 27.44% for 15 wt% SSP (sea shell powder) into PLA, emphasizing the reinforcing potential of the mineral-rich sea shell particles. However, a potential trade-off between decreased strength and… More >