A measurement method of routing flexibility in manufacturing systems (original) (raw)
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Evaluation of the routing flexibility of a manufacturing system
2015
The current competitive and dynamic economic context, requires to manufacturing companies to be reactive and dynamic. For that, they should get a flexible manufacturing system able to change the production plan easily and economically. A good Flexible Manufacturing System (FMS) must have a transportation system able to support a dynamic scheduling and potential failure of the manufacturing system. In this paper, we present a methodology for the dynamic evaluation of the routing flexibility of a manufacturing system. This methodology is based on the computation of entropy and uses Coloured Petri Net model and simulation. We have two objectives:(1) the development of a simulation model able to forecast the level of flexibility of a FMS before its implementation, (2) the definition of an indicator for measuring flexibility. For illustrating our methodology we take an example of a flexible job shop of four machines and one transport resource.
An operational measure of routing flexibility in a multi-stage multi-product production system
The International Journal of Advanced Manufacturing Technology, 2009
The high degree of variety in customer demands causes mass production to become outdated and flexible production to be favored. Routing flexibility can be found in systems that implement general-purpose machines, alternative or identical machines, redundant machine tools, or the versatility of material handling systems. It is recognized that routing flexibility can be treated as a tool for enhancing system performance, such as lead time and inventory reduction. However, its implementation entails a huge cost of installation of flexible machines, automated tool changers and fixtures, and machine operators possessing multiple skills. Therefore, system managers must determine the appropriate level of routing flexibility for a specific system configuration in order to balance benefits and costs incurred. This paper presents a background to and a rational for a routing flexibility measure for a multi-stage flow shop. Instead of merely counting the number of available routes, this measure takes into account the loading balance between machines. Therefore, a manufacturing system with overloaded machines will have less routing flexibility as compared with one that is not overloaded, when both systems have the same number of available routes. An example for demonstrating the applicability of the proposed measure is also illustrated.
Evaluation of flexibility in manufacturing systems
IEEE International Conference on Systems, Man, and Cybernetics, 1990
Studies devoted to modeling and measuring the flexibility of manufacturing systems are reviewed and discussed. Some flexibility measures are then proposed. One is routing flexibility, i.e. flexibility in the sequence of product processing operations. The other measures the consequences of adding new products or increasing the production volumes. Data necessary for both measures are almost deterministic, easy to obtain, and related to what is happening on the shop floor
The measurement of flexibility in manufacturing systems
International Journal of Flexible Manufacturing Systems, 1996
This aIticle provides a theoretical basis for measuring the flexibility of manufacturing systems. The concept of multiple levels of measures (necessary, capability, actual, inflexibility, and optimality) for each flex-~ility type is introduced. Capability and actual measures are then developed for machine, routing, process, product, and volume flexibilities. For each of these flexibility types, a state defining variable is identified. A measure of flexibility is then derived by computing either, (i) the change effort expended in moving between states, (ii) the drop in system performance in moving between states, Off) a genera/or physical scale of difference between two successive states, or (iv) a meamre combining all three. The use of the developed measures is illustrated via a two-facility example.
Route-Independent Analysis of Available Capacity in Flexible Manufacturing Systems
Production and Operations Management, 2008
I n a job shop, because of large setup times, each operation is assigned to only one machine. There is no alternative routing. In a flexible manufacturing system, each manufacturing operation can often be performed on several machines. Therefore, with automated equipment, the capacity of a machine to perform certain operations is not independent of the capacity of other machines. Often, however, operations managers can use a route-independent answer to production planning questions. For example, how much can be produced of a certain part type and when are important capacity questions in business negotiations, when the detailed routing and scheduling are not yet of interest or cannot be known.
Flexibility of manufacturing systems: Concepts and measurements
European Journal of Operational Research, 1989
The issue of flexibility is assuming increasing importance in manufacturing decision making. Flexibility is important to accommodate changes in the operating environment. Manufacturing systems that are flexible can utilize the flexibility as an adaptive response to unpredictable situations. Many researchers have defined various types of manufacturing flexibility and provided methods for measuring them. In this paper we have classified the literature based on the ways researchers have defined flexibility and the approaches used in measuring it.
Performance analysis of a flexible manufacturing system: A statistical approach
International Journal of Production Economics, 1998
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.
GAZI UNIVERSITY JOURNAL OF SCIENCE
Machine sequence flexibility is defined as the combination of operation and routing flexibilities in this study. Its importance in performance level of a flexible manufacturing cell (FMC) is investigated in this study. Studies related with the effects of various flexibility types such as routing flexibility are available in the literature. For example, studies related with routing flexibility try to measure the effects of routing flexibility on the performance levels in operation of manufacturing systems under their own manufacturing environments. Similarly, this study also aims to present a performance measurement model based on Taguchi parameter design principles for investigating the effects of different levels of machine sequence flexibility on the performance of a flexible manufacturing cell and obtaining an optimum and robust performance level. Two main performance metrics namely, manufacturing lead time (MLT) and surface roughness (SR) are considered for the optimization of t...
2010
In a social network analysis the output provided includes many measures and metrics. For each of these measures and metrics, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes? Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply two procedures to analyze these outputs to find the most influential nodes as a function of the decision makers' inputs. We use data envelopment analysis as a method to optimize efficiency of the nodes over all criteria and use the analytical hierarchy process (AHP) as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature: the kite network and the information flow network. We discuss some basic sensitivity analysis that can be applied to the methods. We find the AHP method as the most flexible method to weight the criterion based upon the decision makers' inputs or the topology of the network.
Measuring manufacturing flexibility a resource-elements based approach
Balanced Automation Systems II, 1996
Flexibility is one of the critical performance measures of manufacturing systems. It describes the system's ability to adapt and be responsive to changing production requirements. This paper deals with some issues relating to manufacturing flexibility and the measures that may be used in its evaluation based upon detailed description of the capabilities of machine tools and machining facilities using generic capability units termed "Resource Elements". Three new measures of manufacturing flexibility are proposed and examples are provided to show how they may be applied.