Tool speed and polarity effects in micro-EDM drilling of 316L stainless steel

This paper focuses on the issues of Resistor-Capacitor-based Electrical Discharge Micro-Machining process and investigates the effects of tool speed and polarity on the performance measures such as Tool Wear Rate, Material Removal Rate, Overcut and Taper Angle by drilling on 316L Stainless Steel. Taguchi’s L54 mixed orthogonal array design is employed to conduct experiments by varying tool polarity at two levels and voltage, capacitance, spindle speed at three levels. The cause and effect relationship between the experimental factors and responses are analysed and discussed using Factorial Analysis of Variance technique. Optimum combinations of machining parameters are also evaluated using Taguchi-based Grey Relational Analysis, by considering grey relational grade matrix and influence of process parameters on the responses. Further, microscopic analysis is done to identify the micro-voids, globular formation, and cracks present on the surface of the hole produced under various machining conditions

Multi-objective co-operative co-evolutionary algorithm for minimizing carbon footprint and maximizing line efficiency in robotic assembly line systems

Methods for reducing the carbon footprint is receiving increasing attention from industry as they work to create sustainable products. Assembly line systems are widely utilized to assemble different types of products and in recent years, robots have become extensively utilized, replacing manual labor. This paper focuses on minimizing the carbon footprint for robotic assembly line systems, a topic that has received limited attention in academia. This paper is primarily focused on developing a mathematical model to simultaneously minimize the total carbon footprint and maximize the efficiency of robotic assembly line systems. Due to the NP-hard nature of the considered problem, a multi-objective co-operative co-evolutionary (MOCC) algorithm is developed to solve it. Several improvements are applied to enhance the performance of the MOCC for obtaining a strong local search capacity and faster search speed. The performance of the proposed MOCC algorithm is compared with three other high-performing multi-objective methods. Computational and statistical results from the set of benchmark problems show that the proposed model can reduce the carbon footprint effectively. The proposed MOCC outperforms the other three methods by a significant margin as shown by utilizing one graphical and two quantitative Pareto compliant indicators

Differential evolution algorithm for solving RALB problem using cost- and time-based models

Assembly process is one of the important aspects in manufacturing industries. Industries are extensively using advanced technologies in assembly lines recently such as robots instead of human labor. Cost associated with human labor such as wages, training, safety, and employee management are eliminated with the help of robots. Investments on assembly lines are cost intensive, and industries continuously need to maximize their utilization. In this paper, a cost-based robotic assembly line balancing (RALB) problem with an objective of minimizing assembly line cost and cycle time is addressed. Moreover, there is no research reported on concurrently optimizing cycle time and assembly line cost for a robotic assembly line system to date. The objective of this paper is to propose models with dual focus on time and cost to minimize the cycle time and total assembly line cost simultaneously. Time-based model with the primary focus to optimize cycle time and the cost-based model with the primary focus to optimize total assembly line cost are developed. Due to NP-hard nature, differential evolution (DE) is the algorithm used to solve the RALB problem. Straight and U-shaped robotic assembly line problems are solved using the proposed algorithm, and the detailed comparisons of the results obtained are presented. While comparing straight and U-shaped RALB problems, assembly line cost and cycle time obtained by U-shaped RALB problems are better than the straight RALB problems. The proposed models have significant managerial implications, and these have been discussed in detail