Journal of Advanced Manufacturing Systems

This paper deals with the effect of machining parameters on tool wear, surface roughness and cutting forces in dry turning of low carbon steel with deep cryo-treated AISI D3 tool steel. AISI D3 tool steel was used for preparation of cutting tools as per International Standard Organization (ISO: 3685-1993). Deep cryogenic treatment ($-196^{\circ }$C) of D3 tool steel was carried out at different holding time (12h, 24h and 36h) followed by tempering at $150^{\circ }$C for 2h. Taguchi’s L27 orthogonal array is used for optimizing the process parameters during machining process. Analysis of variance (ANOVA) was carried out to study the significance of the input parameters. Mathematical models were developed using linear regression analysis for validating results. The tool worn surface shows the abrasion wear and oxidation wear were the main wear mechanisms observed under higher speed and feed rate cutting conditions.

The (010) and (100) planes of a $\beta$-Ga₂O₃ crystal were subjected to precision grinding tests with a resin bond diamond grinding wheel on a precision surface grinding machine. The grinding characteristics and surface grinding quality of the planes of the $\beta$-Ga₂O₃ crystal were analyzed on the basis of grinding force, grinding force ratio, specific energy, and surface morphology. The (010) plane shows a larger grinding force and specific energy but a smaller grinding force ratio compared with the (100) plane. Under experimental conditions, the normal and tangential grinding forces of the (010) plane are 1.4–2.2 and 2.6–7.8 times that of the (100) plane, respectively. The specific energy of the (010) plane is 2.8–6.1 times that of the (100) plane, and the grinding force ratio of the (100) plane is 1.4–3.7 times that of the (010) plane. Under the same grinding conditions, the material removal methods for the two planes are evidently different. The (010) plane is mainly removed by brittle fracture and accompanied by a minimal broken area, whereas the (100) plane is mainly removed by cleavage layering and exhibits numerous block cleavage. The (100) plane is the strong cleavage surface, and the (100) plane demonstrates a higher surface roughness than the (010) plane under the same grinding conditions.

Electrochemical honing (ECH) is a nontraditional machining process hybridizing the conjoint benefits of electrochemical machining (ECM) and mechanical honing actions. In this process, maximum amount of material is removed through anodic dissolution, followed by mechanical abrasion. In present day manufacturing industries, it has found wide ranging applications, mainly in finishing of varieties of gears, due to its various advantages, like increased material removal rate, long tool life, burr-free operation, achievement of higher surface finish and dimensional accuracy, generation of no residual stress, reduced noise, less material damage, etc. In order to achieve maximum machining capability from this process, it is always recommended to set its various input parameters at their optimal operating levels. In this paper, four powerful metaheuristic algorithms, i.e. firefly algorithm, differential evolution (DE) algorithm, cuckoo search (CS) algorithm and teaching–learning-based optimization (TLBO) algorithm are applied for single as well as multi-objective optimization of pulsed-ECH (PECH) and ECH processes. It is observed that TLBO algorithm supersedes other techniques in optimizing the two ECH processes with respect to the value of the derived optimal solution, consistency of the solutions and computational speed.

Protection of environment from industrialization and urbanization waste is the prime duty of engineers and researchers. Elimination of industrial waste completely is not possible because it is generally a byproduct of the process. It can be minimized by recycling or reusing. In this research, waste slag generated by steel plant is recycled as a useful flux for submerged arc welding. It is found that recycled slag is capable of producing acceptable weld bead geometry. The penetration achieved using recycled slag is 7.897mm, which is more than the penetration obtained using fresh flux, i.e. 6.027mm. The reinforcement produced by recycled slag is 2.632mm, which is close to the reinforcement obtained using fresh flux. It is further observed that chemistry of weld metal deposited using recycled slag is also at par with that of weld metal produced using fresh original flux. The amount of carbon present in weld metal produced by recycled slag is 0.15%, which is comparable to the percentage of carbon present in weld metal produced using fresh flux. The microstructure and microhardness obtained using recycled slag are also comparable with the microstructure and microhardness obtained using fresh flux. This research established the feasibility of recycling slag as a flux required for submerged arc welding process.

This research examines the effects of green supply chain (SC) practices including recycling techniques, green logistics (G2), environmental protection trainings and programs, and green manufacturing. A data sample of 339 manufacturing firms was collected from the industrial area of Punjab, Pakistan. By using Structural Equation Modelling (SEM), the findings indicated that except GL, the remaining green practices (GP) have significant and positive association with the organizational performance. In addition, GL have insignificant effect on firms’ performance due to government non seriousness, no financial subsidies on green technologies, heavy import duties, scarcity of green technologies/vehicles in Pakistan and that most firms import green vehicles from European and Western countries which incur huge costs into SC system in terms of long lead time. This study will help the policymakers and SC managers to understand the problems and current situation of GSCM in the manufacturing firms of Pakistan. Further, we also discuss research limitations, areas for future research.

Due to industrialization, increasing solid waste is affecting environmental integrity globally. Reverse logistics (RL) has become a significant tool to deal with environmental degradation issues, and it is being implemented in developed countries. However, RL is at the infancy stage in developing countries especially in Pakistan due to different obstacles. This study aims to identify and analyzes the interrelationship between barriers affecting RL implementation in Pakistani manufacturing industry using an integrated methodology of Interpretive Structural Modeling (ISM) and MICMAC approach. Results of ISM and MICMAC identified organizational, financial, and technological barriers as dependent barriers. However, lack of government policy incentives, lack of responsiveness about RL, lack of enforceable laws on product return, changing in regulations due to political changes, lack of environmental law awareness and lack of corporate social responsibility emerged out as top-ranked barriers driving other barriers that need to be addressed. An inter-relationship based structural model will be helpful for supply chain and RL professional in understanding major obstacles to RL implementation and develop a strategy to promote RL in the manufacturing industry.

In a high-speed cold strip rolling process, it is necessary to optimize the process parameters for improved quality in the product. In this study, two separate multi-objective optimization problems for a cold rolling process are formulated. The objectives in one of the cases are minimum isothermal film thickness and film temperature rise in the inlet zone and in another case it is minimum thermal film thickness and film temperature rise in the inlet zone. Particle swarm optimization algorithm has been used for solving the optimization problem. The key input parameters for the cold rolling process are identified and prioritized through the convergence study and the coefficient of variation analysis. A response analysis is performed on the critical input variables. This study assists the process engineer to understand the lubrication in cold strip rolling at high speed and select an appropriate lubricant for a given combination of strip and rolls.

Laser Shock Peening (LSP) turned out to be the most efficient surface engineering process for advanced materials to induce beneficial deep compressive residual stress which helps in improving mechanical, fatigue properties and surface damage resistance. But, analyzing the nonuniform distribution of residual stresses in the treated sample with X-ray diffraction (XRD) is much time taking and a costly process. This problem can be resolved with LSP finite element numerical simulation model which is feasible with the realistic experimental process. The FE model allows the user to control the laser parameters in order to achieve the optimal level of all controllable parameters. This study is intended to analyze and optimize the influence of laser processing parameters that assists in inducing the residual compressive stress with minimal surface deformation. A Ti6Al4V material model with Johnson–Cook’s visco-elastic–plastic material behavior law is prepared for LSP simulation. Gaussian pressure profile is utilized for uniform loading of the targeted zone for the proposed model. Taguchi Grey Relational Analysis (TGRA) with L27 orthogonal array is applied to LSP simulation, and the results were analyzed with consideration of multiple response measures. It is noted that surface deformation is increased with the rise in a number of laser shots and pressure pulse duration. Maximum compressive residual stresses are falling for higher levels of laser spot diameter, laser spot overlap and laser power density. The correlation is observed between the FE simulation and the published results. The optimal set of process parameters are obtained for improving the LSP on Ti alloys.

There are several critical factors which have adverse effects on the workpiece surface finish, dimensional accuracy, tool life, etc. Eccentricity is one of them which can be manipulated when the spindle, tool holder and milling cutter revolve around the line parallel to their cutting axes and crop up due to clamping deviation and geometric imperfections. This work was driven by the observation that there should an approach through which final eccentric error can be reduced as other researchers only displayed the effects of eccentricity on cutting forces, etc. This task was carried out through performing numerous experiments on the CNC milling center and measuring geometric imperfections from the whole body of machining elements at different orientations with dial gauge to find out whether different orientations of elements have effects on the eccentricity. If they have noticeable effects then such orientations of elements exhibiting the minimum eccentricity can be selected which in turn may improve the accuracy and precision of workpieces and reduce the final cutting edge error. Our observation showed that orientations have remarkable effects on the eccentricity pretending lowest final eccentric error which is unable to be ignored.