Performance Analysis of a Flexible Manufacturing System under Planning and Control Strategies

A typical Flexible Manufacturing System (FMS) has been studied under Planning, Design and Control (PDC) strategies. The chief objective is to test the impact of design strategy (routing flexibility) on system performance under given planning strategy (alternate system load condition) and control strategies (sequencing and dispatching rules). A computer simulation model is developed to evaluate the effects of aforementioned strategies on the make-span time, which is taken as the system performance measure. Shortest Processing Time (SPT), Maximum Balance Processing Time (MBPT) are the sequencing rules for selecting the part from the input buffer whereas for machine selection the dispatching rules are Minimum Number of parts in the Queue (MINQ), and Minimum queue with Minimum Waiting Time of all parts in the Queue (MQMWT). In this paper, the same manufacturing system is modeled under two different system load conditions. These load conditions are Full Balanced Load (FBL) and Unbalanced Load (UBL) with respect to machine load and processing time. The result of the simulation shows that there is continuous reduction in make-span with increase in routing flexibility when both machine load and processing times are unbalanced i.e., under UBL system condition. Modeling of FMS shows that each strategy causes a flow process for each part inside the system. The co-ordination and integration of flexible resources to guide these processes in a desirable direction (lesser conflicts) is important. An FMS can then become a platform for studying interoperability between the various potentially conflicting processes where flexibility helps to reduce these conflicts. The improved performance can then become a measure of this phenomenon. Owing to the globalization of the market, increasing demands of the customized products and rapidly changing needs of customers, the manufacturers are facing a problem of customer satisfaction and survival in the market among the various competitors. Therefore, they are searching such a manufacturing system, which fulfill the demand of the market within due dates and it should be available on lower cost. Thus, they can continue to exist in the global market. Among all the existing manufacturing system, they require a manufacturing system, which is having the flexibility to make the customized product with medium volume. Therefore, they are allured to the flexible manufacturing system (FMS), which is a compromise between job shop manufacturing system and batch manufacturing system. Flexible manufacturing system is the system, which is equipped with the several computer-controlled machines, having the facility of automatic changing of tools and parts. The machines are interconnected by Automatic Guided Vehicles (AGVs), pallets and several storage buffers. These components are connected and governed by computer using the local area network. The exquisiteness of this system is that it gleaned the ideas both from the flow shop and batch shop manufacturing system. The prominent literature has the several definitions of the flexible manufacturing system which is given by the many a researchers like Upton (1994), Wadhwa et al. (2005) etc. Wadhwa and Rao (2000) have defined the flexibility as the ability to deal with change by judiciously providing and exploiting controllable options dynamically. Due to this flexibility, some decision-making problems have occurred in the system. Therefore to run the system efficiently, the judicious combination of flexibility and information based integration and automation. Thus, most real FMS have various planning, designs and control strategies to harness this flexibility when required. In the planning strategy, the load condition of the system should be defined clearly. From the past researches, it can be easily concluded that the system should be fully balanced. The balancing of the system can be viewed as the same distribution of task among all the machines.