مدلسازی و شبیه سازی و تجزیه و تحلیل بخشی و ابزار کنترل جریان در یک سیستم تولید انعطاف پذیر

This paper presents the details of a simulation study carried out for analyzing the impact of scheduling rules that control part launching and tool request selection decisions of a flexible manufacturing system (FMS) operating under tool movement along with part movement policy. Two different scenarios have been investigated with respect to the operation of FMS. In scenario 1, the facilities such as machines, tool transporter and part transporter are assumed to be continuously available without breakdowns, whereas in scenario 2, these facilities are prone to failures. For each of these scenarios, a discrete-event simulation model is developed for the purpose of experimentation. A number of scheduling rules are incorporated in the simulation models for the part launching and tool request selection decisions. The performance measures evaluated are mean flow time, mean tardiness, mean waiting time for tool and percentage of tardy parts. The results obtained through the simulation have been statistically analyzed. The best possible scheduling rule combinations for part launching and tool request selection have been identified for the chosen FMS.

A flexible manufacturing system (FMS) is a production system in which groups of numerically controlled (NC) or computer numerically controlled (CNC) machines and an automated material handling system (MHS) work together under computer control. The system can simultaneously process medium-sized volumes of a variety of part types. FMS attempts to achieve both production flexibility and high productivity in order to meet the demands of today's competitive markets. A series of decision problems has to be addressed for the successful implementation of an FMS. These decision problems are classified as design, planning, scheduling and control [1]. Managing the flow of parts and tools is recognized as a critical issue in the operation of FMS. The versatile machines in FMS can perform a variety of operations when it is provided with the required tools. Increase in part variety means increase in number of cutting tool types. This requires a large tool mix and proper methods to plan, monitor and control tools, thus adding to the system cost. It is observed that tool-related costs constitute about 25–30% of the total costs associated with FMS applications [2]. Hence, proper planning and control procedures for tool management are needed for the efficient operation of FMS.

This paper presents the salient aspects of a simulation study conducted for the analysis of part and tool flow control decisions in an FMS, operating in a tool-sharing environment. Two different scenarios have been investigated with respect to the operation of FMS. Scenario 1 corresponds to the failure free FMS. Scenario 2 considers the failure prone FMS wherein the machines, tool transporter and part transporter are subject to failures. For each of these scenarios, a discrete-event simulation model is developed. A number of scheduling rules are incorporated in the simulation model for the part launching and tool request selection decisions. The simulation model has been passed through a multi-level verification exercise. The simulation output has been suitably subjected to steady state analysis to ensure that further investigations are free from initial bias. The results indicate that for the FMS considered, scheduling rules for the part launching decision has a significant effect on the system performance. SPT and EMDD rules for the part launching decision provide better performance for most of the measures. There is not much variation in the mean waiting time for tool when various combinations of scheduling rules for part launching and tool request selection decisions are considered. This is because in the FMS considered in the present study, tool sharing occurs between the two machines in a group only. Tool request selection decision becomes a critical issue in FMSs, involving tool sharing among all the machines in the system. The authors are currently working on the investigation of the impact of tool flow control policies in such systems.