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.

Green supply chain management has emerged as a critical strategic approach for improving environmental sustainability and organizational performance in manufacturing firms. However, existing literature remains limited and missed the mechanisms and contextual conditions that shape these relationships. This study examines the relationship between green supply chain management and organizational performance through green operational capability as mediating mechanism, while considering perceived governmental environmental signaling intensity as moderated mediator. The study employed a quantitative research approach with explanatory research design. The data were collected from 327 respondents who are working in manufacturing factories. Data were analyzed using Smart PLS to test both the measurement and structural models. The findings show that green supply chain management has significant effect on organizational performance and green operational capability. Green operational capability also significantly enhances organizational performance and mediated the relationship between green supply chain management and organizational performance. Furthermore, perceived governmental environmental signaling intensity significantly strengthen the relationship between green supply chain management and green operational capability then influence the organizational performance which confirm moderated mediation effect. This study suggests that manufacturing firms institutionalize green supply chain management as a strategic capability. Policymakers should strengthen clear and consistent environmental signaling to enhance firm responsiveness. Managers should develop green operational capabilities to effectively translate sustainability practices into improved organizational performance and long-term competitive advantage.

The escalating demand for items and their consumption has exerted immense pressure on industrial production and supply chain systems, leading to adverse environmental and societal consequences. The rise in pollution rates and ecological disasters resulting from industrial production has prompted numerous scholars and industry specialists to focus on Sustainable Production and Consumption matters within the framework of Sustainable Supply Chain Management (SSCM). The interest in sustainable supply chain management has significantly increased in recent years, spanning both business and academic sectors. This phenomenon is seen in the growing prevalence of papers, conferences, specialized periodicals, and websites exclusively focused on the subject matter. Nevertheless, the importance of sustainable development in developing economies has only just started to be acknowledged. This literature review aims to assess existing research on sustainable supply chain management (SSCM) in developing nations while considering a worldwide perspective. This paper thoroughly examines the rapid expansion of the subject from an evolutionary perspective; aimed at comprehending the progression of sustainability concerns by examining patterns across different industries, and economies, and employing diverse approaches. An extensive thematic analysis was conducted on 56 selected publications published between 2010 and 2023, emphasizing the growth and significance of the knowledge base. The analysis is conducted utilizing a descriptive and content-oriented methodology. Subsequently, the results are presented, demonstrating an increasing interest in Sustainable Supply Chain Management (SSCM). Nevertheless, there is a conspicuous discrepancy in the extent of research carried out on this subject in emerging economies as opposed to industrialized ones. The findings indicate that the context in less developed countries plays a crucial role in carrying out empirical or case study research. Moreover, it is crucial to analyze how the integration of the three dimensions of sustainability impacts the efficiency of the supply chain, especially when considering the perspective of an emerging economy. Hence, the limitations of this investigation are delineated. Ultimately, it is crucial to do further research from multiple angles within the supply chain, encompassing collaboration, sustainable practices, innovation, sourcing, and supplier growth, with a special emphasis on the position and background of rising countries.

Green supply chain management (GSCM) has emerged as a crucial strategy for organizations to address environmental sustainability concerns. This study aims to examine the knowledge domain of GSCM practices by conducting a bibliometric analysis of Scopus data from 2010 to 2023. Using the VOS viewer software, the researchers examined the publication trends, influential authors, institutions, journals, and keywords in the GSCM research landscape. The methodology involves systematically searching and retrieving relevant publications from the Scopus database, then data cleaning and preprocessing. The resulting dataset comprises 530 articles, which are then analyzed using the VOS viewer to create a network visualization map. Various bibliometric indicators, such as co-authorship, co-citation, and keyword co-occurrence, are used to uncover patterns and relationships among the articles. The bibliometric analysis revealed a growing interest in GSCM, with a significant increase in publications over the 14 years. The study identified the most influential authors, institutions, and journals in the field, highlighting the prominent contributors to GSCM research. Also, looking at how often keywords were used together revealed the main theme groups in the GSCM field, such as sustainable supply chain management, sustainable operations, sustainable governance, and sustainable organizational performance. The findings of this study provide valuable insights into the intellectual structure and evolution of GSCM research. Visualizing the knowledge domain using the VOS viewer facilitates a comprehensive understanding of the interconnections between various aspects of GSCM, such as the adoption of green practices, environmental performance, and supply chain sustainability. These insights can inform researchers, practitioners, and policymakers in developing strategic initiatives and future research directions to advance the field of GSCM.

Aluminum 1100 is a commercially pure aluminum alloy with properties suitable for applications requiring ductility and workability. It is soft, weldable, and corrosion-resistant. This study attempts to determine the influence of machining on high-speed turning operations. The experiment is designed using the Design of Experiments of Response Surface Methodology, using input parameters such as cutting speed, feed rate, and cutting depth, to estimate surface roughness, temperature, and machining time of aluminum1100 as the workpiece material, with a carbide tool used for operation. The Analysis of Variance technique has been used to test the material's performance. In contrast, the Design Expert software has been used to study the impact of cutting parameters on the workpiece. A Backpropagation ANN model is developed in MATLAB to optimize cutting parameters and reduce Ra, T, and Tm values. The ANN indicates that the lowest expected value is in this case. The Multi-Objective Genetic Algorithms are employed to forecast turning parameters, and it is observed that, for an input parameter grouping of 16 Pareto-optimal solution sets, the ideal Ra ranges from 1.37 to 1.62 µm, and the temperature ranges from 34.10 to 34.08 °C. The machining time ranges from 1.27 to 1.34 min. Among all, cutting speed has the greatest influence on the parameter. The confirmatory analysis shows that the experimental and predicted values differ by less than ±2% and agree admirably with the experimental values.

Garment sector is one of the industrial sectors in Ethiopia. In this sector the final products are always with defect(s) which reduces attraction from customers and economic benefit from the business. With this intention, quality enhancement of shirt products through defect(s) rejection reduction using SQC tools was a vital task of this research. The study applied Pareto Analysis and Cause-and-effect diagrams for detailed examination of top defects. From the Pareto-analysis six top defect types; cuff assembly seam slip out, sleeve hemming, button slip out, side seam puckering, button missed, and placket seam out have been identified. These defects contributed 81.68% of all defects happening in the case company. Then root-cause analyses for these top defect types have been done and solutions have been suggested to overcome causes to reduce rejected shirts. Finally, the suggested solutions have been practically implemented through the organized implementation team from different departments of the case company including the researcher. This has given remarkable results of almost 67.3%, 2222 shirts, of export rejected shirts have been saved. These saved shirts have been exported additionally to the international market in line with the defect free products of that month and increased the income of the case company by 444,400 ETB to 555,500 ETB per month.

The permanence and durability of mechanical and structural elements with discontinuities such as cracks and voids require the calculation of SIF (stress intensity factors) with reasonable fidelity. SIF is a crucial parameter that predicts crack growth and failure behavior by quantifying the stress field neighboring the crack tip. Therefore, understanding the sophisticated characteristics of the stress fields in the vicinity of discontinuity requires an effective way of calculating SIFs. Currently, there are numerous methods to calculate SIF, such as FVM (Finite Volume Method), FEM (Finite Element Method), BEM (Boundary Element Method), XFEM (Extended Finite Element Method), Phase field method and Meshfree methods. For an extended period, FEM is one of the leading methods in solving fracture mechanics problems. Though FEM is quite robust in dealing with several engineering problems, it has got its inherent drawbacks to deal with singular fields like discontinuities. Hence to reasonably capture moving discontinuities, finer meshes near the discontinuous field are required that demand more computation effort and time. To alleviate the above drawback of FEM, this study employed Extended Isogeometric Analysis (XIGA) to efficiently and effectively determine the SIFs in the case of fissured plates as benchmarking fissure problems. In this study SIFs in relation to crack length were examined for edge and center cracked plates and results were compared with the theoretical values.

A flat Aluminum specimen with a geometric discontinuity, which allows testing of the applicability of 2D and 3D Digital Image Correlation Strain measurements, has been considered for this research since it is prone to high stress concentration via Addis Ababa Institute of Technology research interest. Experimental strain using digital image correlation and geometry measurements should be measured with estimated material properties and compare the results with theoretical model predictions. Aluminum plate with central hole were subjected for far field stress in the Machine shop of School of Mechanical and Industrial Engineering at Addis Ababa University in order to test the agreement between DIC’s strain analysis, strain gauge strain analysis and calculated empirical formulas of strain analysis and for the stress distribution of the plate elastically deformed by using VIC-3D and strain gauge. The aim is to measure vertical strain field, Vertical strain along horizontal line through hole center as function of applied loading and vertical strain using theoretical formula along same line as measurements in a plate with central hole subjected to far field and near field tensile loading using visual image coloration (VIC-3D) software, Destensometere device and solid mechanics equations to compare strain results.

The purpose of this overview is to discover materials commonly used in the automotive industry and provide an overview of optimized composites to reduce weight, cost, fuel consumption and CO2 emissions. The cost of carbon fiber, Al and Mg lightweight composites is much higher than conventional materials. It is therefore important for research and development in the area of reducing costs, increasing recyclability, enabling integration and maximizing the fuel economy benefits of automobiles. In order to meet these characteristics, natural fibers have better properties and, in addition to being environmentally friendly, will become the material of choice for the future automotive industry. Composites can reduce weight by 10-60%. Researchers are already working with bio composites, investigating not only the economic aspects, but also the properties and associated manufacturing processes for environmentally friendly transportation and CO2 reduction.

There is no rationalization for a certainty that harder wheels or rails will result in an increase in wear of the opposite side of the wheel/rail interface. This research investigated how the wear of wheel material changes when the hardness of the opposing pair is varied. Three Rail/wheel material matches; normalized UIC50 kg/m and S1002 wheel profile (Rail/wheel material 1), normalized UIC60 kg/m and whole heat treated S1002 wheel profile (Rail/wheel material 2) and rim heat treated UIC60 kg/m and whole heat treated S1002 wheel profile (Rail/wheel material 3) has been investigated using multi-body simulation software (SIMPACK) and MATLAB programming. For validation, as an experimental advantage, the wear depths measured on the wheel tread wear of the end vehicle of LRT for mileage of 50,000 km are compared to the results of numerical simulation performed. As a result, the estimated total tread wear amount after a mileage of 50,000 km is 4% larger than the experimental one. That is indeed a very good result considering that either component of the wheel wear prediction model used is neither adjustment nor calibration. From the three rail/wheel matches, Rail/wheel material 3 found to be the better material match that could resist wear significantly considering material hardness as important criteria for comparison. The study could remark that, despite the fact both wheel and rail material hardness could affect the wear performance in respected positive ways, most significant improvements are attained by improving the rail material hardness ahead of wheel material.