Tool Magazine Capacity Research Articles

A BRANCH AND BOUND PROCEDURE FOR SETUP PROBLEMS IN FLEXIBLE MANUFACTURING SYSTEMS

We address a medium‐ to short‐term production planning problem in a flexible manufacturing environment. First we present a single‐machine, mixed integer programming model for part type selection and lot‐sizing problems over a T‐period planning horizon. Demand for part types changes dynamically through the periods. The objective is to meet the demand for part types during the periods they are demanded. Available machine time and tool magazine capacities are the system constraints in our models. We next extend on the single‐ machine model to include multiple machines. In addition to part type selection and lotsizing decisions, the extended model also addresses the machine‐loading decision. We present exact branch and bound procedures based on linear programming relaxations for the two models. We also report the results of our computational experiments.

SOLVING A COMBINED PART‐SELECTION, MACHINE‐LOADING, AND TOOL‐CONFIGURATION PROBLEM IN FLEXIBLE MANUFACTURING SYSTEMS*

Loading too many or too few copies of tools may result in waste of tool magazine slots and unnecessary machine shutdowns. This is a consequence of not integrating the tool‐configuration problem with other flexible manufacturing system (FMS) planning problems. Solving part‐selection, machine‐loading and tool‐configuration problems independently may cause entire solutions to be infeasible. We propose both an approach to the explicit formulation of tool configuration problems and the simultaneous solution of part‐selection, machine‐loading and tool‐configuration problems. We developed and solved sequentially some associated bicriteria models sequentially. We also discussed the effects of considering some secondary objectives on system performance and described the concepts of critical magazine size and critical machining time using an example problem. Unnecessary allocation and under‐use of tool magazine capacity and machining time could be reduced by considering the critical magazine size and machining time. Finally, we suggest using a method based on Lagrangian relaxation for solving large size problems.

Decomposition for Scheduling Flexible Manufacturing Systems

In some flexible manufacturing systems, tool magazine capacity naturally divides parts into families so that substantial setups occur only when switching production between families. For this situation (positive setup times and costs only between families), we show that the production planning problem decomposes into two simpler problems: an aggregate scheduling problem, and a disaggregation. First, we derive a disaggregation that determines the optimal intrafamily product schedules corresponding to a given family schedule in polynomial time. Second, we show how to aggregate so that the decomposition maintains optimality for family schedules satisfying the property that production does not begin until inventory is zero (the Zero-Switch rule).

Block Angular Structures and the Loading Problem in Flexible Manufacturing Systems

Loading problems of Flexible Manufacturing Systems (FMSs) have usually been formulated as an integer program with nonlinear constraints for tool magazine capacities. The nonlinearity and integer nature of the problem results in the loading problem being difficult to solve. Conventional branch-and-bound methods have been proposed, but again the solution time can easily be excessive for moderate sized problems. In this paper, we present an alternative formulation of the FMS loading problem. Such a formulation defines more decision variables, but is able to avoid nonlinearity of the constraints. It also includes the time availabilities of the machines as additional constraints. The main feature of the formulation is that it exhibits a block angular structure. By exploiting this special structure, an efficient branch-and-bound algorithm can be developed. This algorithm has the attractive feature that the bounds of the branches can be computed through simple procedures based on the solution of linear knapsack problems. Some computational results of the algorithm are also presented.

A tool cluster based strategy for the management of cutting tools in flexible manufacturing systems

AbstractThe management of tooling systems in cell‐based flexible manufacturing systems is described. The use of cluster analysis in the management of cutting tools is presented. The role and functioning of a cluster based tool management strategy is described with respect to the management of the cutting tools, scheduling of the work flow and the number of captive tools. The research findings are described and supported by an example. A Rank Order Clustering (ROC) algorithm was used, selected for its simplicity and rapid implementation, to cluster tools. The ROC algorithm is applied to cluster tools. These clusters are scheduled on work stations based on part (the primary priority) and cluster (secondary) priority management rules. This provides the dynamics of managing the change of tool clusters as well as providing for the case where resident tool clusters are desired. A spreadsheet‐based computer assisted tool clustering model, intended for industrial usage, is described. The clustering model reduces the requirement for robust advance schedule generation and encourages the adoption of smaller tool magazine capacities. The cluster based model advances beyond just tool kitting to provide rapid on‐line generation of tooling configurations where part mix and production ratios may be varied almost instantaneously on a spreadsheet and where rigidity in scheduling may be relaxed by allowing a tool cluster to attract any part in the cluster set. The paper concludes with a brief description of on‐going research effort in applying cluster analysis to cell tool management.

A methodical approach to the flexible-manufacturing-system batching, loading and tool configuration problems

SUMMARY A mixed-integer programming (MIP) problem is formulated to address the flexible manufacturing system (FMS) batching, loading, and tool configuration problems concurrently. This model results in a great many variables, making its mathematical solution impractical. We introduce a four-pass approach using submodels of the original MIP problem. The approach assumes that the need for batching is primarily that of tool magazine capacity constraints, with balancing and maximizing flexibility as secondary objectives.

A tool allocation method based on group technology and heuristics.

In this paper, we propose a heuristic tool allocation method for FMS's based on group technology. According to this method, a structured tool-part relation matrix is at first to be obtained by applying quantification theory III. Then the heuristics utilizing the properties of a structured relation matrix is applied to form part families and tool sets, considering the constraints on tool magazine capacity and available running time. By applying this heuristic method, independent machining cells can be formed for each part families, the part movements between the machines can be decreased, tool setup time can be reduced, and also good workload balance between the machines can be achieved. Consequently, the machine efficiency and the productivity of the system can be improved. This heuristic method is also shown to be valid and efficient by an example.

A study of FMS part type selection approaches for short-term production planning

This research compares seven approaches from the literature to the selection of part types for simultaneous production over the next time horizon. A flexible approach to the selection of part types and the simultaneous determination of their mix ratios so as to balance aggregate machine workloads is presented. Constraints on tool magazine capacity are considered. Simulation studies are conducted on realistic, detailed models of flexible flow systems (FFSs) configured as pooled machines of equal sizes. The simulated settings are constructed to evaluate the impact of such factors as blocking, transportation, buffer utilizations, and fixture requirements and limitations of various types.One of the goals of this study is to encourage industry to relax, for those FMS types for which the procedure is appropriate, what is essentially an artificial constraint: that tool changing be isolated in time, to a period between batches. For other types of FMSs, batching may be appropriate.The results indicate that using the flexible approach enables the system to be more highly utilized. It is also observed that the batching approaches tend to require more fixtures of each type than the flexible approach. The system utilizations for the batching approaches seem to be more sensitive to restrictions on the number of fixtures of each type. Further research needs are also discussed.

A Branch and Bound Approach for Machine Load Balancing in Flexible Manufacturing Systems

A flexible manufacturing system (FMS) is an integrated system of computer numerically controlled machine tools connected with automated material handling. A set of production planning problems for FMSs has been defined (Stecke [Stecke, Kathryn E. 1983. Formulation and solution of nonlinear integer production planning problems for flexible manufacturing systems. Management Sci. 29 (3, March) 273–288.]), and this paper considers one called the loading problem. This problem involves assigning to the machine tools, operations and associated cutting tools required for part types that have been selected to be produced simultaneously. The part types will be machined during the upcoming production period (say, of one to three weeks duration on average) and according to a prespecified part mix. This assignment is constrained by the capacity of each machine's tool magazine as well as by the production capacities of both the system, and each machine type. There are several loading objectives that are applicable in a flexible manufacturing situation. This paper considers the most commonly applied one, that of balancing the workload on all machines. This paper first discusses a nonlinear integer mathematical programming formulation of the loading problem. The problem is formulated in all detail. Then an efficient solution procedure is proposed and illustrated with an example. Computational results are provided to demonstrate the efficiency of the suggested special-purpose procedures.