Journal of Advanced Manufacturing Systems

A lot of research has been done to improve electric discharge machining (EDM) process to overcome the difficulties of lower material removal and surface finish. In the current study, magneto rheological (MR) fluid was used in place of conventional dielectric to develop a new variant of EDM process. A comparative study of MR fluid assisted EDM at the stationary and rotary conditions of the tool with M2 grade high-speed steel as workpiece has been presented. Investigations have been done to evaluate the effect of various process parameters such as percentage volume Al₂O₃, pulse on time, duty cycle and discharge current on material removal rate and surface roughness with surface morphology. Higher material removal rate and lower surface finish was obtained in rotary magneto rheological fluid assisted EDM as compared to magneto rheological fluid assisted EDM without rotation under the same processing condition at optimum process parameters.

This research paper presents the laser transformation hardening (LTH) to improve the surface hardness of commercially pure titanium, nearer to ASTM Grade3 chemical composition of 1.6mm thickness sheet using a CW (continuous wave) 2kW, with radiation wavelength $\lambda =1.06$$\mu$m Nd:YAG laser. Full factorial and response surface design approach in Design Expert 9 software have been discussed and evaluated by statistical regression analysis and analysis of variance. The experiment was carried out as the full factorial design (FFD) array of 27 with 3 factors, 3 levels, i.e. 3${}^3=27$ experiments. The selected input parameters are: laser power, scanning speed and focused position, and responses are: Vickers Microhardness on top surface, in fusion zone, and in heat affected zone. FFD and response surface methodology (RSM) were applied to evaluate and optimize the effects of laser process parameters on Vickers microhardness of laser hardened surface. The results show that, the hardness of as-received commercially pure titanium is approximately 153VHN and the hardness after laser transformation hardened bead geometrical surface is in the range of 200–240VHN. The hardness can be increased with the increase in the scanning speed and decrease in the optimum value of laser power i.e. heat input applied. It has been found that the quadratic model is best fitted for prediction of the Vickers microhardness of laser hardened surface. These findings are significant in modern development of hard surface coatings for corrosion and wear resistant applications. Application of experimental results will be considered in the aerospace, marine, chemical, medicine, automobile and the engineering industries.

This paper deals with a mathematical model for reduction of the lack of coverage (LC) involving multiple coverage in presence of partial covering. The model proposes a new structure of assignment of facilities in a facility location system to cover in greater proportion of the demand territory, avoiding assignment of several facilities in the same space of the territory. A comparison between the engendered solution and its representation is carried out through known indicators to measure the improvement of the solution. The results of our proposed model are contrast and better compared to defined referred models in order to evaluate the reduction of LC.

The aim of this study is to present an approach for identifying and prioritizing risk factors of supply chain in the home appliance industry. First, the indexes related to the supply chain risk have been determined by literature review; and then the indexes have been refined by consulting experts; finally, the six main indexes including supplier, manufacturer, customer, environment, distributor and information as well as 32 subsidiary indexes for supply chain risks have been selected. In order to assess the indexes, a fuzzy questionnaire has been developed and distributed to 15 managers and employees of Snowa as one of the Entekhab Industrial Group corporate brands, the main home appliance manufacturing company in Iran. Research population included managers and experts of the company and the analysis approaches included risk-assessment matrix and Shannon fuzzy entropy. Findings indicated that environment, manufacturer and supplier indexes with the weights of 0.105, 0.102 and 0.095, respectively were prioritized as the top three risk factors in product development. Furthermore, the subsidiary indexes of raw material alteration, delay in supply of the demand, work force, after-sale services, competitors and lack of political stability were among the top risk factors of new product development.

Supply chains have been more serious for environmental issues for not only the reduction of CO₂ emission but also for material starvation. To enhance a closed loop supply chain for assembled product, a disassembly system is required. At end-of-life, the assembly products at recycling organization should be disassembled environmentally and economically for not only low carbonization but also of material circulation. This recycling and reusing of product enables to reduce CO₂ release because the virgin materials which release CO₂ volumes caused by production and logistics can be saved by the usage of the recovered materials. Parts with higher recycling and CO₂ saving rates ought to be chosen and physically disassembled, but the manual disassembly brings a higher cost, rather than discarding the parts. Therefore, material recovery value is also to be considered for parts selection during the assembly operation. Parts information like material recovery value, CO₂ release, weight, precedence relationships are required for environmental and economic parts selection. This study proposes a CAD based approach for environmental and economic parts selection for disassembly using solid works sustainability. It considers higher CO₂ saving rate, higher recycling rate and higher material recovery value as environmental and economic criteria for parts selection.

To address the resources optimization problem of AGV-served manufacturing systems driven by multi-varieties and small-batch production orders, a scheduling model integrating machines and automated guided vehicles (AGVs) is proposed. In this model, the makespan of jobs from raw material storage to finished parts storage through multi-stage processes has been used as the objective function, and the utilization ratios of machines and AGVs have been used as the comprehensive evaluation functions. An improved particle swarm optimization algorithm with the characteristics of main particles and nested particles is developed to solve a reasonable scheduling scheme. Compared with the basic particle swarm optimization algorithm and genetic algorithm, the numerical result suggests that the nested particle swarm optimization algorithm has more advantages in convergence and solving efficiency. It is expected that this study can provide a useful reference for the flexible adjustment of AGV-served manufacturing systems.

The implementation of lean manufacturing practices (LMP) means a systematic approach of several management procedures and practices, which may impact content, nature and quality of people’s work. This implementation process is often performed after an accurate assessment to ensure the effectiveness and efficient execution of these practices. However, the necessity and logic of different assessments according to the situation required by assessment objective, the logic requires general rules for designing assessment with effective and reliable results. The aim of this research paper is to develop a logical perception to explain the impact of LMP on the actual and overall performance of the company and explains the computational basics and mathematical equations contributing to the assessment design of these practices to ensure efficiency and accuracy in the results. Moreover, this study also concludes a novel mathematical equations that can be used in the effective assessment to increase the effectiveness of evaluation for improvement processes in different sectors.

In this work, micro-EDM ($\mu$EDM) characteristics of conductive SiC have been evaluated using the knowledge of existing coupled thermo-structural model. A simplified thermo-structural model of $\mu$EDM process on conductive SiC has been used to simulate the $\mu$EDM process on conductive SiC. So far, the studies have used traditional melting and evaporation removal mechanism during EDM simulation which is suitable for metals. In case of ceramics, material removal occurs by various phenomenon such as spalling, melting, evaporation and it depends on $\mu$EDM energy and type of ceramic. Thus, we aim here to evaluate the characteristics of a SiC ceramic using the thermo-structural model. To make the model more realistic, Gaussian heat flux distribution has been used and transient study has been performed. The model uses process parameters (voltage, capacitance and time) and material properties as input to predict the transient temperature distribution, crater dimensions, volume of material removed and thermal residual stresses. To simulate the material removal, element death has been performed. The element death is purely based on attainment of certain temperature suitable for material removal irrespective of material removal mechanism. The transient thermal analysis was carried out in heating phase and the structural analysis was carried out in cooling phase. Observatory experiments were performed to add value to the model predictions.