Journal of Advanced Manufacturing Systems

Inconel 718 is a nickel-based superalloy having high strength and low thermal conductivity. Due to its properties, wire electrical discharge machining has been selected. The paper reports an experimental investigation of Inconel 718 using zinc-coated brass wire electrode. Based on $L_{27}$, Box-Behnken design of response surface methodology has been adopted to estimate the effect of process parameter on the machining responses. Four controllable process parameters (viz., wire tension, wire speed, discharge current and pulse-on time) vary, each at three discrete levels, between parametric domains. The following machining responses, in terms of material removal rate (MRR), surface roughness ($R_a$) and corner deviation ($C_d$), have been investigated. Finally, an evolutionary computation method has been used based on non-dominated sorting genetic algorithm (NSGA-II) in order to find out the optimal set of solutions for rough-cutting. Experimental data have been used to develop regression models to optimize the process. The adequacy of the developed mathematical model has also been tested by the analysis of variance results. Pareto-optimal settings obtained through NSGA-II have been ranked by gray relation analysis to identify the best optimal set of solutions to avoid lengthiness and impreciseness in the judgment. Confirmation tests have been conducted for optimum machining parameter from the set of Pareto-optimal solutions for proving betterment.

In the present study, response surface methodology (RSM) has been used to optimize roller burnishing process for aluminum alloy 63400 grade. Single roller burnishing tool (carbide) is used to burnish round aluminum alloy. Experiments were performed with Box and Wilson Central Composite Design (CCD). The machining factors controlled during experimentation are speed, feed, force and number of tool passes. The response parameters are surface roughness and microhardness. The most significant control factors on the surface roughness and microhardness were determined by analysis of variance (ANOVA). A controllable process parameter is correlated with surface roughness and microhardness by mathematical model. A quadratic regression analysis is performed to compute the correlation coefficient between the experimental and predicted values. The optimum surface roughness and microhardness foreseen by the model is found to agree well with the results of the experiment. To find the optimum value of both the response, desirability approach was used. The input parameters with most desirability value are selected as the optimum solution. Hence, the most desirable burnished condition desirability value 0.872 is speed 37.9m/min, feed 0.5mm/rev, force 35.49N and number of tool passes four. Surface roughness obtained is 0.524$\mu$ m and microhardness is 125.02HV. This is the optimum condition for minimum surface roughness and maximum microhardness. The optimum surface finish and microhardness predicted by the model are found to agree well with the results of the experiment.

The research investigation reported on the effect of machining parameters on surface roughness (Ra) in electric discharge drilling of Inconel 718. Machining was done by using a copper tool electrode. Machining was conducted by considering different process parameters viz. tool diameter, discharge current, pulse on time, pulse off time, tool rotation and depth of hole. Optical surface profiler was used to measure surface roughness of drilled hole in work-piece. Design of experiment was created by Taguchi method based L18 orthogonal array. For minimum surface roughness, optimum parameters were found using Analysis of variance (ANOVA). Based on analysis, it is found that pulse off time, pulse on time and tool rotation are the most significant parameters that affect the surface roughness. Tool diameter is the less significant parameter that affects the surface roughness. Regression analysis was used to predict a value for minimum surface roughness. The scanning electron microscope (SEM) images were used to identify the microstructure of the drilled hole in Inconel 718 work-piece. Interaction plots and residual plot have been plotted for surface roughness to identify the interaction between parameters and residual errors, respectively.

During machining processes, cutting temperature directly affects cutting performances, such as surface quality, dimensional precision, tool life, etc. Thus, evaluation of cutting temperature rise in the tool–chip interface by reliable techniques can lead to improved cutting performances. In this paper, we present the modeling of cutting temperature during facing process by using time series approach. The experimental data were collected by conducting facing experiments on a Computer Numerical Control lathe and by measuring the cutting temperature by an infrared camera. The collected data were used to test several Autoregressive Integrated Moving Average (ARIMA) models by using Box–Jenkins time series procedure. Then, the adequate model was selected according to four performance criteria: Akaike criterion, Schwarz Bayesian criterion, maximum likelihood, and standard error. The selected model corresponded to the ARIMA (1, 1, 1) and it was tested by conducting a new facing operation under the same cutting conditions (spindle speed, feed rate, depth of cut, and nose radius). It was clearly seen that there is a good agreement between experimental and simulated temperatures, which reveals that this approach simulates the evolution of cutting temperature in facing process with high accuracy (average percentage error $=$ 0.57%).

This article presents an experimental study of a recently developed process, namely, ultrasonic assisted jet electrochemical micro-drilling (UAJet-ECMD) using pulsed DC voltage power supply. The goal of the work was to examine the effect of pulsed DC voltage on the performance of UAJet-ECMD process. In the previous work carried out by the authors, the process has been studied using the continuous DC voltage. The pulse “on” time (pulsed DC voltage), electrolyte pressure and pulse “on” time (ultrasonic vibrations) were selected as the process parameters, whereas material removal rate (MRR) and hole taper were chosen as process responses. It was found that the pulse “on” time (pulsed DC voltage) had crucial effect on the MRR as well as on the hole taper. MRR and hole taper were both found to increase with rise in pulse “on” time (pulsed DC voltage). Optimization of process responses of UAJet-ECMD process was done. The responses obtained for optimized set of process parameters were verified and found in good conformity with the experimental results.

Electrochemical discharge machining (ECDM) is an advanced machining process which uses both chemical action and spark discharge method for removal of materials. Till date, most of the applications of ECDM are in machining nonconductive materials, although some authors have also tried machining conductive materials. This paper attempts to develop a finite element simulation model based on heat generation in the spark region to evaluate material removal rate (MRR) in case of quartz and soda lime glass. The calculation of MRR is based on melting and evaporation of the material due to high temperature generated due to spark discharge. Convection heat transfer is also considered in the analysis. The results obtained from the simulation are compared with available experimental results and previous simulation results. Although this process is not used in the industry till now, it has a lot of scope for research and development.

The pork processing industry resembles a case of disassembly scheduling because a planner needs to decide the pig size and quantity to be supplied to the slaughtering house, as well as the amount of meat and meat size needed to process an order. The meat processing resembles disassembly scheduling for multiple products with parts in commonality. We extend the general disassembly model further to cover product perishability of the meat while allowing demand to occur in other levels of product hierarchy rather than the leaf product (products that are no longer being disassembled). We also allow the model to obtain outsource products to be processed if it achieves a more economical solution. In this study, we developed a mathematical model to determine the quantity and size of pig supplies (root items) and meat cuts (parent/child items) to be processed for an order to minimize the total cost. Computation time and cost of generated test problems are obtained. The application of pork processing plan is demonstrated.

The excessive competition in domestic as well as international market has forced the manufacturing organizations to adopt advance manufacturing systems such as flexible manufacturing system (FMS). Adoption of these systems has resulted into increased productivity and better quality products. In order to continue their presence in cut-throat competitive environment, the manufacturing organizations are exploring the flexibility options of FMS. In order to analyze the flexibility options of FMS, an endeavor has been performed to identify the critical factors (CFs) that are pertinent to the flexibility of FMS. These CFs have a reflective impact in designing of FMS. After ascertaining these CFs, interpretive structural modeling (ISM) and MICMAC approach have been used to establish the structural relationships among these CFs to develop a hierarchical model. The verdicts of this exploration may assist managers to analyze the flexibility options of FMS in their organizations.

Assembly line balancing problem (ALBP) is an allocation of given tasks to the workstations in a way that the number of workstations or the idle times of workstations get minimized. ALBP is a well-known problem in mass-production systems with high production volume and low diversity. In division and grouping allocation problems like ALBP, metaheuristic algorithms based on group structure, i.e. grouping genetic algorithm, are more efficient. The aim of this study is developing a new solution procedure to minimize the number of workstations for a given cycle time based on grouping evolution strategy. A modification of the ranked positional weight method is proposed to construct the initial solution, and a new heuristic method based on a modified version of the COMSOAL method is provided to tighten the solution after performing the mutation operator. Different strategies based on line efficiency and line smoothness indexes are considered to select the best result and transfer it to the next generation. Moreover, to evaluate the performance of proposed algorithms, some well-known standard test problems are utilized. Computational results indicate that the proposed solution algorithm performs efficiently and can obtain the optimal global solution in most of the high dimensional problems.