This study aims to investigate the key drivers of supply chain complexity in the footwear industry business sector. After conducting extensive literature review and consultation with experts, complexity drivers in the context of the footwear business sector were identified. The content validity of the identified drivers was checked by 13 experts using content validity ratio (CVR), which were used as the basis to select 20 key Supply Chain complexity drivers. Using a multi-criteria decision-making DEMATEL approach the cause and effect drivers were investigated. The findings of the study investigated 12 cause and 8 effect drivers in the footwear sector. Among the cause drivers, four linkage drivers that have strong driving power and dependency were identified. This study is the first in the developing county footwear business sector using DEMATEL approach to identify the key supply chain complexity drivers and their interrelationship. The study identified complexity drivers in the context of the footwear business sector that were not explored before in the existing studies. The outcome of this study will help SC complexity decision-makers in that case sector to control and manage the cause and effect drivers and thus improve the efficiency and effectiveness of their SC performance.

LM26 is a cast aluminum-silicon alloy that exhibits superior castability, moderate strength, and high corrosion resistance. Silicon is typically the primary alloying agent in aluminium alloy LM26. The present study investigates the development of hybrid composites and the machining of aluminium alloy LM26 reinforced with varying weight percentages (0.25%, 0.5%, and 0.75%) of multi-wall carbon nanotubes (MWCNTs), with a focus on sustainable machining. The casting was performed by stir casting at 700°C and 650 rpm. In this study, the Central Composite design is used to design the experiment, and Response Surface Methodology (RSM) is employed to develop a quadratic (polynomial) equation using Design-Expert software V13. The milling experiment was conducted on MWCNT-reinforced LM26 material using a milling machine, with spindle speed, feed rate, depth of cut, and MWCNT percentage as parameters, to measure surface roughness (Ra) and temperature (T). Microstructural characterization of the composite was performed. The performance characteristics were analyzed using ANOVA. This result shows that wt.% of MWCNT is an influential factor in minimizing Ra, while spindle speed affects Ra, and feed rate affects temperature. Based on the results, it has been concluded that adding 0.25% wt. of MWCNTs has improved machinability; however, increasing the MWCNT content increases Ra and temperature. To achieve better machining performance that meets sustainability criteria, a Multi-Objective Genetic Algorithm was employed to optimize the objectives. The MOGA was adopted to solve the optimization problem, yielding 21 non-dominated Pareto-optimal solutions. This study has identified several alternatives to help academics and industry develop environmentally friendly, sustainable machining techniques.

Friction Stir Welding (FSW) is a process of welding materials that generates heat through friction. Plastic deformation, nonlinear material movement, tool-to-structural evolution friction, and heat production from friction and plastic deformation all have an impact on FSW operation. In this paper, thermo-mechanical characteristics of aluminum alloy AA6061-T6 during the FSW process were simulated based on COMSOL® software using a finite element approach. A conceptual model was created to interpret the thermal and structural analyses. According to the obtained results, the temperature rises on the top and bottom surfaces as the axial force increases but decreases along the line perpendicular to the weld direction. The overall temperature decreases as the forward welding speed rises within the acceptable induced temperature range of the workpiece, while the axial force and rotational speeds stay stable.