Multiple Process Routes Research Articles

Multiple criteria clustering algorithm for solving the group technology problem with multiple process routings

This paper considers the machine-part clustering problem in group technology manufacturing in which for a part multiple process routings can be planned. Existing approaches using similarity coefficient to solve the problem suffer from computational burden which arises since they use the similarity coefficients defined between routings of parts, not machines. Furthermore, existing methods do not deal effectively with the ill-structured problems in which mutually separable cells do not exist. In this paper, we define the generalized machine similarity coefficient. This approach saves considerable computer memory required to store the similarity coefficient information in comparison with the methods using the similarity coefficients defined between parts. Furthermore, the new definition includes existing machine similarity coefficient as a special case. Unlike the existing algorithms using single clustering criterion, a new algorithm using multiple clustering criteria is developed. The algorithm using the generalized machine similarity coefficient effectively solves large-sized and ill-structured problems.

AN ASSIGNMENT METHOD FOR THE PART-MACHINE CELL FORMATION PROBLEM IN THE PRESENCE OF MULTIPLE PROCESS ROUTES

Abstract This paper considers the part-machine cell formation decision of the generalized Group Technology (GT) problem in which multiple process routes can be generated for each part. The existing p-median model and similarity coefficient algorithm can solve only small-sized or well-structured cases. An assignment method for the cell formation problem is suggested. This method uses an assignment model which is a simple linear programming. Numerical examples show that the assignment method provides good separable cell formation even for large-sized and ill-structured problems.

Optimal periodic scheduling of multipurpose batch plants

A rigorous mathematical programming framework for the scheduling of multipurpose batch plants operated in a cyclic mode is presented. The proposed formulation can deal with batch operations described by complex processing networks, involving shared intermediates, material recycles, and multiple processing routes to the same end-product or intermediate. Batch aggregation and splitting are also allowed. The formulation permits considerable flexibility in the utilisation of processing equipment and storage capacity, and accommodates problems with limited availability of utilities. The scheduling problem is formulated as a large mixed integer linear program (MILP). For a given cycle time, it is shown that it is sufficient for the formulation to characterize a single cycle of the periodic schedule despite the existence of tasks that span two successive cycles. The optimal cycle time is determined by solving a sequence of fixed cycle time problems. The MILP is solved by a branch-and-bound algorithm modified so as to avoid exploring branches that are cyclic permutations of others already fathomed. The resulting implementation permits the solution of problems of realistic size within reasonable computational effort. Several examples are used to illustrate the applicability of the algorithm.

A simulator for batch and semi-conductors processes

The design of BOSS, a dynamic simulator for batch oriented processes, is presented. The key features of the simulator are: a modular structure which allows incorporation of dynamic models of individual processing steps, a methodology for processing discontinuities in the time history of the system, provisions for accommodating multiple product processing routes, and logic for allowing dynamic route/equipment assignment. The simulator employs an equation oriented approach and uses the LSODAR integrator and the Harwell sparse equation solving routines.

Prolactin: Multiple intracellular processing routes plus several potential mechanisms for regulation

Prolactin: Multiple intracellular processing routes plus several potential mechanisms for regulation

Relationships between calcium and cyclic nucleotides in cell activation.

Relationships between calcium and cyclic nucleotides in cell activation.