In the literature, there exist many variations of machining economics problem in terms of modelling approaches and solution methodologies. However most of the existing studies focus on the single machining operation which is seldom in practice. On the other hand, tool management approaches at the system level fail to relate the tooling issues to the machining conditions, and ignore the tool availability and tool wear restrictions. A new solution methodology is developed to determine the optimum machining conditions and tool allocation simultaneously to minimize the production cost of a multiple operation case where there can be alternative tools for each operation. As a result, we can both improve the solution by exploiting the interaction between these two decisions, and also prevent any infeasibility that might occur for the tool allocation problem due to tool contention among the operations for a limited number of tool types by considering the tool availability and tool life limitations.

Scope and Purlmse---An effective tool management is a major requirement for the implementation of a flexible manufacturing system (FMS), hence the computer numerical control (CNC) machine tools. A new solution methodology to the tool management problem is proposed in connection with the tool magazine arrangement and operations sequencing decisions, where there can be alternative tools for each operation. The proposed approach not only improves the overall solution in terms of the total manufacturing cost, but also prevents any infeasibility that might occur at the system level due to tool management constraints through a feedback mechanism.Abstract--A two-phase approach is developed to solve the tool magazine arrangement and operations sequencing problems. The overall aim is to minimize the total manufacturing cost by utilizing the benefits of tool sharing concept and loading duplicate tools due to a possible decrease in tooling and tool operating costs while maintaining the feasibility in terms of precedence, tool magazine capacity, tool life covering and tool availability constraints due to tool contention among the operations for a limited number of tool types, because the absence of such crucial constraints may lead to infeasible results. Furthermore, the proposed approach can provide an effective decision making tool for the short term operational decisions of FMS.

We propose a problem space genetic algorithm to solve single machine total weighted tardiness scheduling problems. The proposed algorithm utilizes global and time-dependent local dominance rules to improve the neighborhood structure of the search space. They are also a powerful exploitation (intensifying) tool since the global optimum is one of the local optimum solutions. Furthermore, the problem space search method significantly enhances the exploration (diversification) capability of the genetic algorithm. In summary, we can improve both solution quality and robustness over the other local search algorithms reported in the literature

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