Fuzzy Gilmore and Gomory Algorithm: Application in Robotic Flow Shops with the Effects of Job-dependent Transportation and Set-ups

This paper addresses the scheduling of robotic cells with job-dependent transportation and set-up effects with fuzzy methodology. Since transportation and set-up times are a large portion of the production time in a flexible manufacturing cell, ignoring these parameters may cause significant errors in determining the optimal makespan. Furthermore, determining the exact values of these time parameters is a challenging task. To overcome this problem, we represent these parameters using fuzzy L-R numbers. Using the capability of fuzzy numbers to model approximate values, we can represent these parameters without losing valuable information. For generating the optimal part sequencing in the cells, the Gilmore and Gomory algorithm is modified, and instead, a fuzzy Gilmore and Gomory algorithm is developed. We compare the results of the proposed fuzzy method with those of crisp ones. The results indicate the superiority of the proposed algorithm in terms of robustness, flexibility, and reduction of makespan.

Effect of routing flexibility on the performance of manufacturing system

This work presented in this paper is based on the simulation of the routing flexibility enabled manufacturing system. In this study four levels of each factor (i.e. routing flexibility, system load conditions, system capacity and four part sequencing rules) are considered for the investigation. The performance of the routing flexibility enabled manufacturing system (RFEMS) is evaluated using three performance measures like make-span time, resource utilization and work-in-process. The analysis of results shows that the performance of the manufacturing system may be improved by adding in routing flexibility at the initial level along with other factors. However, the benefit of this flexibility diminishes at higher levels of routing flexibilities.

Genetic and Phenotypic Characterization of Cryphonectria hypovirus 1 from Eurasian Georgia

Cryphonectria hypovirus 1 (CHV-1) infects the chestnut blight fungus Cryphonectria parasitica and acts as a biological control agent against this harmful tree disease. In this study, we screened the recently characterized C. parasitica population in Eurasian Georgia for the presence of CHV-1. We found 62 CHV-1 infected C. parasitica isolates (9.3%) among a total of 664 isolates sampled in 14 locations across Georgia. The prevalence of CHV-1 at the different locations ranged from 0% in the eastern part of the country to 29% in the western part. Sequencing of two specific regions of the viral genome one each in ORFA and ORFB revealed a unique CHV-1 subtype in Georgia. This subtype has a recombinant pattern combining the ORFA region from the subtype F2 and the ORFB region from subtype D. All 62 viral strains belonged to this Georgian CHV-1 subtype (subtype G). The CHV-1 subtype G strongly reduced the parasitic growth of C. parasitica isolates from Georgia, with a more severe effect on the European genepool compared to the Georgian genepool. The CHV-1 subtype detected in Georgia provides a valuable candidate for biological control applications in the Caucasus region.

Modeling and Analysis for Minimization of Mean Flow Time in FMS Simulation

The aim of this paper is to deal with a simulation study on effect of part launching, part sequencing at central buffer and tool selection rules on a flexible manufacturing system (FMS) involving tool movement along with part movement policy. A typical FMS is selected for a study of discrete event simulation model. Simulation experiments are conducted on various combinations of decision rules and it is found to be good in evaluated performance measures.