A profound study of damage behavior for Al 2024-T3 alloy worksheet produced by constrained groove pressing in the superior practical condition.

Constrained groove pressing (CGP) process is one of the most efficient and novel methods of severe plastic deformation to manufacture ultra-fine sheet metal. The present research work is related to the study of CGP process of 2024-T3 Aluminum alloy sheet. The empirical and numerical simulation of CGPed- specimens have been examined at both room and elevated temperatures. In order to simulate the constrained groove pressing process in Abaqus software, the Johnson-Cook material model has been employed. The geometrical variables of the CGP process include the teeth number, teeth angle, and sheet thickness, and the criterion for the superiority of the numerical test is the maximum reduction of two equivalent strain and equivalent force factors, simultaneously. To determine the weight's coefficients of the target factors and select the superior test, the Shannon's Entropy and Simple Additive Weighting (SAW) methods have been used, respectively. After validating the numerical findings, the variation of damage parameter, stress triaxiality and the equivalent plastic strain distribution in the superior practical condition have been evaluated in detail. Based on the Entropy-SAW hybrid technique, the weight's coefficients of equivalent strain and equivalent force target factors were computed to, in turn, 0.38 and 0.62. Also, the results revealed that the CGP process could not be performed at room temperature based on high damage evolution. But, at elevated temperature, the damage parameter (D) doesn't exceed 0.26. Also, the maximum stress triaxiality and equivalent plastic strain (PEEQ) at this process temperature reached to 0.5 and 0.1, respectively.

Empirical analysis of dust and noise pollutants produced in the wood-CNC machining process.

In the manufacturing processes, consideration of sustainability is of particular importance. The current study is concerned with the influences of changing the process variables on the reduction of pollutions in the wood-CNC machining operation. Noise and dust are the studied pollutants in the present research work. Process variables include feed rate, spindle speed, step-over, and depth of cut, and the aim is to predict the behavior of aforementioned pollutants variations in the current process. The amounts of these harmful factors are measured based on existing standards. In order to analyze the findings, adaptive neuro-fuzzy inference system (ANFIS) and regression analysis methods have been employed, separately. The effects of process parameters on response variables have been comprehensively studied. The research findings demonstrated that for the present problem, ANFIS outcomes are more accurate. According to the mean absolute error (MAE) criterion, the prediction errors of ANFIS for noise and dust factors were computed to, in turn, 0.50 and 14.89. Meanwhile, the error values for prediction of noise and dust responses using regression analysis were calculated as 1.54 and 34.62, respectively.

Multi-objective optimization of wire electrical discharge machining process using multi-attribute decision making techniques and regression analysis.

Wire electrical discharge machining (WEDM) is one of the most important non-traditional machining methods that is widely used in various industries. The present research work is concerned with the influences of process variables on quality of machined specimen obtained from WEDM process. The process parameters to manufacture mold structure included wire feed speed, wire tension and generator power, and in the current research, the effects of these variables on the aim factors, namely dimensional accuracy, hardness and roughness of product surface have been investigated, simultaneously. In order to obtain the optimal experiment, the multi-objective optimization with discrete solution area has been employed. Method based on the removal effects of criteria (MEREC) and weighted aggregates sum product assessment (WASPAS) techniques have been used with the aim of weighting the objective functions and discovering the best practical experiment. In the following, the regression analysis has been employed to study the effects of variables on response factors. A good correlation between the results gained from two analysis methods was observed. Based on MEREC-WASPAS hybrid technique, the weights of roughness, hardness and dimensional accuracy of machined part were calculated to about 89%, 9% and 2%, respectively. In the selected optimal experiment, the amount of wire feed speed, wire tension and generator power variables were considered to, in turn, 2 cm/s, 2.5 kg, and 10%.

Effects of COVID-19 outbreak in pricing and collaboration of a health-social dual-channel supply chain.

The coronavirus pandemic has affected most aspects of product supply and consumer behaviors and led to transformations in the supply chain. The COVID-19 pandemic and the requirements to reduce its prevalence have led many people to shop online and encouraged many manufacturers to sell their products online. In this study, a manufacturer, who intends to possess an online sales channel, and a retailer, who has an in-person sales channel, are considered. Then, pricing strategies and collaboration mechanisms between them in the health-social dual-channel supply chain are investigated. This study is developed in three models, including centralized, decentralized, and collaborated under Stackelberg game, whereas the optimal price of products in each channel, level of implementation of health and safety protocols in retailers, advertising level, and status of online shopping performance are obtained for improving customer trust. Moreover, the demand is represented as a function of selling prices of products in online and in-person shops, compliance level of health protocols, level of online shopping performance, and advertising in health during the COVID-19 pandemic. Although the centralized model provides more profit for the manufacturer, the collaborated model provides the highest profit for the retailer. Thus, since the supply chain profit of centralized and collaborated models is close, the collaboration model is the best option for members in this situation. Sensitivity analysis is finally performed to evaluate the impact of key parameters, and then according to obtained results, some management insights are suggested for the dual-channel supply chain during the COVID-19 pandemic.

Optimization of food-energy-water-waste nexus in a sustainable food supply chain under the COVID-19 pandemic: a case study in Iran.

Abstract: During the coronavirus epidemic, food supply chains have been affected by disruptions of this epidemic. Having an overview and considering food-related factors such as energy, waste, and water make the design of the supply chain more effective. In this study, a multi-objective model for a sustainable food supply chain is presented based on the prevalence of coronavirus by considering the food-energy-water-waste nexus. There are dual-channel sales including online and in-person channels, which their demand functions depend on products price in every channel, as well as the prevalence of coronavirus in high-risk or low-risk areas. Distribution centers, located in high-risk regions, require the disinfection of products to minimize coronavirus spread. Indeed, the proposed mathematical model has three objective functions that the first objective maximizes the profit of the food supply under COVID-19 conditions. The other two objectives minimize not only the environmental impact of transportation, but also the delivery time. In order to solve this multi-objective model, the epsilon constraint method, as an efficient technique, is employed. To validate the proposed model, the model is finally implemented in a two-channel supply chain in Iran. The results show that the food supply chain has a close relationship with the energy-water-waste nexus COVID-19 and can also affect customers' behavior. Moreover, the model shows when the prevalence of COVID-19 increases, people tend to buy from online shops, affecting product prices that can change by nearly 50%.

Comparing supply-side and demand-side policies in the solar cell supply chain under competitive circumstances: a case study.

Due to the destructive effects of fossil fuels on the environment, using renewable energies has nowadays been suggested. In addition, because of the increased use of solar energy and the prevention the solar cell supply chain (SCSC), this chain is mainly supported by government funding. In this study, we mathematically model both supply-side and demand-side policies for a two-echelon SCSC, considering the competition between domestic and foreign suppliers as well as government intervention under the supply-side subsidy policies to support SCSC members and finance the customers through demand-side subsidy policies. The aim of this paper is to investigate the effects of government intervention under the supply-side and demand-side policies on supporting the members of SCSC and encouraging customers to increase the use of solar panels. In addition, this study explores the best policy for improving and promoting SCSC. In the real world, both supply-side and demand-side policies will help industrial factories, power plants, and households to enhance the use of solar energy for producing electricity. This study has been investigated using one real example, whose results show that the efficiency under the supply-side policy is about 7% more than the efficiency under the demand-side policy. The price under the supply-side policy is roughly 10% less than the price under the demand-side policy. The members' profit under the supply-side policy is approximately 5% bigger than the one under the demand-side policy. According to real examples, the government's utility under the demand-side policy is nearly 1% smaller than the government's utility under the supply-side policy. Finally, key findings are considered for the proposed model.

Organic level vs. sales effort in coordination of green food supply chain for deteriorating items.

Current research concentrates primarily on the effect of the organic level on the deterioration rate of products over a two-echelon food supply chain with two manufacturers and a retailer. One of the manufacturers produces organic products (OP), which is called the organic manufacturer (OM), and the other one produces non-organic products (NOP) with sales effort, which is called the non-organic manufacturer (NOM). Indeed, the NOM compensates for the organic advantage of OM by sales effort. The deterioration rate is assumed to be an ascending function of the organic level, and the products start to deteriorate at a specific rate that depends on the type of that product. In this study, the green supply chain based on the organic level is firstly examined in decentralized and centralized conditions, and then coordination between the retailer and the OM with the contract mechanisms is investigated. To demonstrate the performance of mathematical models, a real-world example and sensitivity analysis of crucial factors are presented. Thus, the chain profit increases, but one of the member's profits will decrease.

Impact of government policies on photovoltaic supply chain considering quality in the power distribution system: a case study.

Nowadays, due to the lack of energy and the harmful effects of fossil fuels on the environment, many countries seek to use renewable sources such as solar energy, a clean and free energy source. Direct conversion of solar energy into electricity is the reason for using solar cells. This paper proposes a three-echelon photovoltaic supply chain with two suppliers (domestic and foreign), two power plants (big and small), and a power distribution system with government intervention. We consider three approaches, including (1) the decentralized model, (2) the centralized model, and (3) the government's role in the photovoltaic supply chain. In the first model, the power distribution system is a leader, and other members are followers. In the second model, we explore the whole supply chain as a centralized model, and in the third model, the government has the leading role, and the rest of the members follow. Indeed, in the last model, the role of the government as a supporter that gives subsidies and tax exemptions to keep members in a competitive market is investigated, and the decision variables of the government (tariffs) are obtained. Finally, based on real example from the power industry of Iran, sensitivity analysis and managerial insights are proposed.

A hierarchical revenue-sharing contract in electronic waste closed-loop supply chain.

Due to the growing concerns about the increasing release of consumer products to the environment, especially for defective electronic products, the management of the closed-loop supply chain (CLSC) is emerging. To do this, a chain consisting of a manufacturer, a retailer, and a collector is offered in a manufacturer-led Stackelberg game. Due to the presenting of some concepts in the model, which are provided by considering two categories of customers for primary and secondary goods, it is suitable for electronics supply chains. In order to coordinate between the members of the chain, a hierarchical revenue sharing (HRS) contract is introduced, which is suitable for some members of the chain where operate as a holding company. In the following, some numerical examples are applied to examine the applicability of the proposed models. The results of the sensitivity analysis on the main parameters of the problem indicate an increase in the profitability of all members in the coordination contract compared to the decentralized mode. Furthermore, customer sensitivity to price and quality has also inverse and direct impact to members' profitability, respectively. Each of the analyzes provides some in-depth managerial implications that can be considered for future research. Finally, another research result will explain the increase in the amount of return defective goods by the customer in the contract mode.