Failure Behavior Assessment for Steel-Based Laminated Panel Using Combination of Hybrid Data Analysis

J Fail. Anal. and Preven. https://doi.org/10.1007/s11668-026-02404-x ORIGINAL RESEARCH ARTICLE Failure Behavior Assessment for Steel-Based Laminated Panel Using Combination of Hybrid Data Analysis M. K. Faidzi . S. Abdullah . S. S. K. Singh . M. F. Abdullah Submitted: 1 December 2025 / in revised form: 26 January 2026 / Accepted: 3 February 2026 Ó The Author(s) 2026 Abstract This study aims for a comprehensive data analysis of failure assessment by integrating the qualitative and quantitative methods. Failure assessment of metal laminate panel is crucial and particularly vulnerable to delamination, core crushing, and buckling under extreme loading conditions, such as cyclic loading. Traditional assessment methods are time-consuming and costly. Hence, simulation-based optimization has become a preferred approach. However, the integration of qualitative multi-criteria decision-making methods with quantitative engineering practices remains unclear and requires further exploration. Metal laminate panels were simulated under a four-point bending setup, and the results were analyzed This article is an invited paper selected from presentations at the 8th International Symposium on Damage Mechanics of Materials and Structures, held September 9–11, 2025, in Bangi, Malaysia, and has been expanded from the original presentation. The issue was organized by Salvinder Singh Karam Singh and Shahrum Abdullah, Universiti Kebangsaan Malaysia. M. K. Faidzi (&)  M. F. Abdullah Department of Mechanical Engineering, Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, Kem Perdana Sg. Besi, 57000 W.P Kuala Lumpur, Malaysia e-mail: S. Abdullah  S. S. K. Singh Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia S. Abdullah e-mail: M. F. Abdullah Center for Tropicalisation, Defence Research Institute, Universiti Pertahanan Nasional Malaysia, Kem Perdana Sg. Besi, 57000 W.P Kuala Lumpur, Malaysia using the Fuzzy AHP-TOPSIS method to identify the best design core configuration. Experimental analysis was performed, together with data survivability, using a 95% confidence interval analysis. The findings indicate that a smaller dimple core improves life cycle by 39% different and exhibits the highest ranking in closeness coefficient. In addition, the statistical analysis provided a strong correlation and high accuracy between experimental and simulated data. It has been highlighted that the potential of integrating qualitative and quantitative methods to determine the best core configuration for metal laminate. Keywords AHP-TOPSIS  Delamination  Hybrid data analysis  Failure assessment  Metal laminate Introduction The failure assessment of metal laminate (ML) panels has become an essential research focus and its rapidly evolving in material engineering and structural analysis. When subjected to extreme loading conditions such as high-cycle fatigue or repetitive cyclic stresses, they are prone to experience an interfacial delamination, localized crushing of the core structure, and global buckling instabilities [1]. Such failure modes are not only inherent to the material system but involving with the interaction between the core geometry, adhesive layers, and external load conditions. The selection of core design and material type plays a significant role in dictating the structural integrity of sandwich panels, with performance strongly influenced by operational environments and load severities [2]. For example, although cores with open or closed cavity designs provide significant weight savings compared to solid-core 123 J Fail. Anal. and Preven. alternatives, they often lack the mechanical robustness required to resist high-velocity impacts or prolonged cyclic fatigue loading [3]. This trade-off highlights the complex interactions between lightweight design objectives and structural durability. Moreover, the wide range of factors contributes to failure, including the geometric configuration, adhesive strength, and load application modes. Hence, rigorous advanced solver and techniques were required to accurately predict failure mechanisms. However, this requirement often imposes substantial challenges for researchers and manufacturers, as it increases both the cost of product validation, and the time required to achieve reliable performance assessments. Consequently, there is a growing demand for more efficient predictive modeling approaches that can minimize experimental procedure while still ensuring high accuracy in capturing real-world damage behaviors [4]. Current practice shown that researchers and industry players tend to optimize their product conceptual and design using the simulation and testing. However, due to time constraint and budget costing, these steps were seen to be ineffective. Using FEA results could be complex when defining the best selection because several alternative core designs must be considered based on the critical failure factors [5]. Designers need the capability to process several important factors alongside a variety of alternatives using an analytical approach if they are to produce firm results indicating the suitable selection [6, 7]. The previous literature reveals a lack of in-depth research on the use of FEA results as an input for the data analytics of Multi-Criteria of Decision-Making (MCDM) approach to determining the best core design [8, 9]. Throughout the years as shown in Fig. 1, the trend of multi-criteria decision-making Fig. 1 The trend analysis until November 2025 for the research related with the hybrid multicriteria decision-making (MCDM) with finite element analysis and experimental work for the past 5 years ago (Source: Science Direct Website) 123 (MCDM) approach associated with FEA and experimental has keep increasing and become an important tool when deals with many factors in analyzing the best option [10]. However, the combination of qualitative (MCDM) and quantitative approach was still new, and it remains to be discovered their potential [11]. Hence, a new comprehensive approach is vital to reduce the repetition process in designing and optimize decision result. In this work, the ML panel was simulated using the specific finite element software under four-point bending scenario. Thus, it leads to an objective of the work, which is to determine the suitable core design configuration for metal laminate by integrating the qualitative of hybrid data analysis with quantitative responds. The simulation results were then used as input in MCDM approach to analyses and determine the best core design for sandwich panel. The qualitative results were validated with quantitative result to define the correlation and the stability of the data. This study contributes to the systematic failure assessment approach in determining the suitability of core design for ML panel to improve the delamination resista (...truncated)