A flexible cell scheduling problem with automated guided vehicles and robots under energy-conscious policy

Abstract

Abstract. A exible Cell Scheduling Problem (CSP) under Time-Of-Use (TOU)electricity tari s is developed in this study. To apply a kind of energy-conscious policy, overconsumption cost of on-peak period electricity, limitations on total energy consumption by all facilities, setup time available on each cell, part defect (pert) percentage, and the total number of Automated Guided Vehicles (AGV) were considered. Additionally, an Ant Colony Optimization (ACO) algorithm was employed to nd a near-optimum solution to the proposed Mixed Integer Linear Programming (MILP) model with the objective of minimizing the total cost of CSP model. Since no benchmark is available in the literature, a lower bound was implemented as well to validate the result achieved. Moreover, to improve the quality of the results obtained by meta-heuristic algorithms, two hybrid algorithms (HGA and HACO) were proposed to solve the model. For parameter tuning of algorithms, Taguchi experimental design method was applied. Then, numerical examples were presented to prove the application of the proposed methodology. Our results were compared with the lower bound, con rming consequently that HACO is capable of nding better and near-optimum solutions.

Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

“…Electricity suppliers have been adopting time-varying pricing schemes to incentivize users to shift electricity consumption from high-demand periods to lower-demand ones, improving the reliability and efficiency of the electrical power grids, as well as reducing carbon emissions in electricity generation. Therefore, a new trend in the research on EEJSPs, which optimizes energy costs by taking advantage of such incentives, has emerged [35,36,38]. Researchers usually resort to discrete time formulations that divide the scheduling horizon into time slots with equal duration, each having a predefined energy cost.…”

“…Nevertheless, there are a few exceptions. Some authors [37,38,85,[87][88][89][90][91][92] schedule transport and take into account the energy required to load/unload vehicles, and others [93][94][95][96][97][98] consider the energy required to transport the jobs between geographically distributed facilities.…”

“…In recent years, several researchers have addressed energy-efficient scheduling problems, some by imposing energy-related constraints or objectives [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] and others by extending the scope of problem decisions to include equipment status [23][24][25][26][27][28][29], equipment working speed [30][31][32][33][34], and time slot allocation [35][36][37][38]. We review all works on energy-efficient job shop scheduling problems, regardless of how energy consumption is approached (optimized or restricted) and how energy consumption is changed (equipment status or working speed).…”

Sensitivity Analysis and Optimization of the surface Roughness in the Incremental Forming of mild Steel Sheets

“…The S/N ratio is divided into three groups: (1) nominal is the better case, (2) smaller is the better one and (3) larger is the better case [24]. This study aims to minimize the surface roughness; hence, the-smaller-thebetter method is utilized based on equation 2 [25]:…”

Approach to Reduce Throughput Time in Grinding of Gundrills

“…If the plant has a job shop/ functional layout in place, significant reductions in batch size may require conversion to manufacturing cells which reduce move time, processing time, process variability and arrival variability further reducing MTTP [12]. Cellular manufacturing system is another method that helps in reducing throughput time [13]. An approach to reduce throughput time during the product design has been proposed by [14].…”