شبیه سازی مدل سازی و تجزیه و تحلیل به اشتراک گذاری ابزار و تصمیم گیری در بخش برنامه ریزی در یک مرحله از سیستم های تولید انعطاف پذیر multimachine
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|16066||2007||10 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Robotics and Computer-Integrated Manufacturing, Volume 23, Issue 4, August 2007, Pages 361–370
This paper focuses on a simulation-based study of tool sharing problem in single-stage multimachine Flexible Manufacturing Systems. Three different scenarios are considered for investigation. A simulation model has been developed for each of these scenarios. A number of scheduling rules are incorporated in the simulation models for the decisions such as tool request selection and part launching in the context of tool sharing environment. The performance measures evaluated are mean tardiness, conditional mean tardiness and mean flow time. Based on the analysis of the simulation results, the best possible scheduling rule combinations for part launching and tool request selection have been identified for the three scenarios.
Flexible Manufacturing System (FMS) is an integrated production system consisting of multifunctional numerically controlled machines connected with an automated material handling system, all controlled by a central computer system. FMS is an evolving technology particularly suitable for mid-volume, mid-variety production. Stecke  identifies four hierarchical levels in which the decision problems in FMS are partitioned: design, planning, scheduling and control problems. Tool management that involves the allocation and scheduling of tools is an important problem in 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 found that tool costs correspond to about 25–30% of the variable and fixed costs involved in FMS applications . Hence, proper tool management is very much essential. In most FMSs, operations are allocated to machines and the corresponding tools are loaded into tool magazines of the machines  and . In these systems, parts are transferred from one machine to another according to the routing determined by the operational allocation decisions. The operational policy for systems of this type is called the part movement policy. On the other hand, in some FMSs, each part visits only one of the machines for the entire processing. Such systems belong to the category of Single-Stage Multimachine Systems (SSMS). Fig. 1 shows the relationship between FMS and SSMS, as presented by Koo and Tanchoco .
نتیجه گیری انگلیسی
In this paper, an attempt has been made to present the details of a simulation study conducted to investigate the effect of tool request selection rules in combination with part launching rules under three different scenarios of operation of a typical single-stage multimachine FMS in a tool sharing environment. The simulation models have been passed through multilevel verification and validation checks. The results on analysis revealed a number of interesting facts about the performance of the FMS considered in the present study. The operating policies for part launching and tool request selection influence the system performance characterized by various measures differently. A clear understanding of the dynamics in the system indicated by the simulation analysis helps to determine the best operational policies. These facts have been established in a restricted sense in the present study using the limited number of situations considered. However, the results of this study have provided considerable encouragement to study the system in detail. Tool life is an important parameter with respect to cutting tools in manufacturing systems. The present study can be enhanced by considering the tool life data for the various tools using appropriate distributions for tool life in the simulation model. The tool life is monitored at the end of each operation. A tool whose life is expired is moved to the central tool storage and replaced. Further, systems involving both tool movement and part movement can also be investigated. The effects of breakdowns of machines, part transporter and tool transporter can also be studied. The authors are presently pursuing further research in these directions.