International Journal of Research in Industrial Engineering
Volume:11 Issue: 4, Autumn 2022

In managing a supply chain, the green approach has become pivotal for the sake of environmental, economic, and social sustainability. In this paper, we consider the environmental performance prediction in managing sourcing of a textile industry supply chain. Specifically, this research focuses on the dying sector of an emerging economy. We identify eleven green supply chain performance indicators and four performance measures and perform both qualitative and quantitative analyses. The performance is predicted using a probabilistic model based on a Bayesian belief network (BBN). The robustness of the findings is validated through a sensitivity analysis. The outcomes suggest that ‘total suspended solids’ (TSS) and ‘volatile organic compounds’ (VOC) are the most important indicators for the case company in this study with the highest entropy reduction. Also, ‘air emission’ was found to be the most impactful performance measure for entropy reduction. This research work will help improve the decision-making capability of the managers and practitioners considering the total environmental performance of the green supply chain. The improved decision-making will also improve overall organizational performance of a green supply chain.

In any country's economy, the distribution is one of the most important industries and infrastructure. The industry's 8% portion of national income, explains the wide range of this industry and consequently the key role of this industry in the supply chain of many industries in the country. Not using all the capabilities of the distribution network and ignorance about distribution enablers will lead to chain costs failure and increase supply. In today's condition, maintenance and continuity of activities in the distribution network are considered as important subjects in a supply chain, and the reliability of the distribution network in a supply chain is grounded in recognition of the enablers. Identifying and prioritizing the distribution network enablers precede the development and proper implementation of the strategies and plans of a distribution network. The fuzzy logic has become a convenient tool for prioritizing due to the necessity of the comprehensive view to the supply chain, the uncertain space of it, and inconsistency in the views of decision-makers. This research tries to identify and prioritize the empowerment in order to direct and supply resources and thus to increase the productivity and effectiveness of the country's industrial distribution network.The theoretical framework of the study is based on the extracted enablers from the literature and selecting a final set of them by using the Lawshe method. The group of experts is comprised of 11 experts in the welding and cutting industry. The enablers are prioritized using the fuzzy BWM method and Lingo software. The results indicate that the most influencing factor on the distribution network is "on-time delivery" and the "logistic infrastructures" factor is the least important among the factors. The resulted prioritization could be used as a guideline for a better perception of the activities related to the distribution network.

In this paper, the performance characteristics of a fabricated horizontal axis wind turbine with and without flanged diffusers were studied using wind tunnel experiment. Measurements of global parameters (power, torque, rotational speed efficiency, etc.) were carried out at wind speed regime between 3-7 m/s. Flanged diffusers of five different inlet-outlet diameter ratios were employed. The results showed minimum mean increments in tip-speed ratios (TSR) of about 45 % with the smallest diffuser and a maximum of 80 % with the largest diffuser. Increments in the torque even at modest wind speed of 4 m/s were as much as 65, 70 and 76 % for the largest three diffusers and about 33 % for the smaller diffuser. The power output (with and without diffuser) gradually increased from 3-7 m/s wind speed, while the power coefficient (Cp) increased from 3-5.5 m/s, and thereafter began to fluctuate as the wind speed approached 7 m/s. Comparatively, maximum Cp of the turbine without diffuser was 0.22 for λ=0.534 at a wind speed of 7 m/s, while the maximum average value of Cp for turbine with flanged diffuser 3 was 0.34 for λ=0.706 at the same wind speed. As a result of the flanged diffuser attachment, the maximum Cp increased by 36 %. The results showed mean incremental values of 52 and 57 % with the greater value obtained from the second largest diffuser (Di/Do = 0.70) and the least value from the largest diffuser (Di/Do = 0.80), while the first three diffusers achieved near identical increments of 55 %. This consequently implies that increments in the extracted power (i.e., Cp) above 5 m/s wind speed declined with indications of separation and turbulence in the flows beyond the rotor.

Productivity improvement is important for the sustainability of the business. However, before improvement it is important to measure the existing system productivity level. In this sense, the productivity of the case company has been measured by using the PO-P approach. Using this approach, the overall productivity of the case company has become 0.652. By having the ergonomic sub system and strategic goal of the case company, goal programing has been formulated to show by how much percent does the ergonomics subsystem alone will improve the overall productivity level. For this, it is required to have optimal solution of performance value of the performance objectives of the ergonomics sub-system. The optimal solution of the excel solver has given the suggested performance values of x3=1.035, x4= 0.82, x5=0.7, x6=0.8, x7=2.76, x8=0.75, x9=0.8, x10=0.5, and x11=0.4. Having these values, the productivity of the ergonomics subsystem became 1.492, in effect increased the overall productivity from 0.652 to 0.776.

The most desired strength value in any welding process is an excellent Ultimate Tensile Strength (UTS) of the weld in respect to the parent metal. Welding process parameters should be monitored and reviewed on a continuous basis due to the increased demand for structural and industrial materials with higher strength weld joints. The goal of this study is to look into the limitations of the investigated industrial firm's existing GMAW welding process parameters used in the welding procedure, and to propose alternative, uniquely designed, and improved process parameters to replace its existing procedure welding protocol, thereby improving weld results by achieving higher Ultimate tensile strength. The proposed process parameters were then compared to available literature, and optimization was performed using the Response Surface Method.Tensile strength was determined on GMAW welding plates of 200mm by 20mm. The RSM Analysis was used to examine the data acquired from the experimental findings, and the results show that the current, voltage, and travel speed had the most significant effect on the ultimate weld strength. Furthermore, the findings show a high link between the actual and predicted ultimate tensile strength. Maximum ultimate tensile strengths of 425, 450, and 475Mpa were attained at welding voltages of 28 v, currents of 240 A, and travel speeds of 0.012 m/s .

Curve fitting is a computational problem in which we look for a base objective function with a set of data points. Recently, nonparametric regression has received a lot of attention from researchers. Usually, spline functions are used due to the difficulty of the curve fitting. In this regard, the choice of the number and location of knots for regression is a major issue. Therefore, in this study, a Genetic algorithm simultaneously determines the number and location of the knots based on two criteria comprise of least square error and capability process index. The proposed algorithm performance has been evaluated by some numerical examples. Simulation results and comparisons reveal that the proposed approach in curve fitting has satisfactory performance. Also, a sensitivity analysis on the number of knots has been illustrated by an example. Finally, simulation results from a real case in statistical process control show that the proposed Genetic algorithm works well in practice.

Improving supply chain management performance is one of the key issues for companies to gain competitive advantage. In this regard, one of the solutions is a pure approach. A lean approach helps eliminate supply chain waste. On the other hand, based on the conditions of Iran and the existence of abundant auto parts industry, the implementation of a lean approach in the supply chain of organizations operating in this field, is extremely important in order to conduct this study in one of the largest companies Activities in the automotive parts industry have been implemented. At first, by reviewing the literature, eight key factors that cause the supply chain to be clean were identified, and 40 supply chain experts were assisted using a questionnaire. The normality of the data distribution was examined using the Kolmogorov-Smirnov test. The main result of this study was the pattern of factors affecting the purity of the supply chain in the automotive parts industry. This model includes the leveling of factors affecting the supply chain, which provides managers with a comprehensive view and attitude about the relationships between these variables.