248 research outputs found

    Joint cell loading and scheduling approach to cellular manufacturing systems

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    Cataloged from PDF version of article.A hierarchical multi-objective heuristic algorithm and pricing mechanism are developed to first determine the cell loading decisions, and then lot sizes for each item and to obtain a sequence of items comprising the group technology families to be processed at each manufacturing cell that minimise the setup, inventory holding, overtime and tardiness costs simultaneously. The linkage between the different levels is achieved using the proposed pricing mechanism through a set of dual variables associated with the resource and inventory balance constraints, and the feasibility status feedback information is passed between the levels to ensure internally consistent decisions. The computational results indicate that the proposed algorithm is very efficient in finding a compromise solution for a set of randomly generated problems compared with a set of competing algorithms. © 2011 Taylor & Francis

    Tool allocation and machining conditions optimization for CNC machines

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    Cataloged from PDF version of article.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

    Tool magazine arrangement and operation sequencing on CNC machines

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    Cataloged from PDF version of article.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. Copyright © 1996 Elsevier Science Lt

    Dynamic lot sizing and tool management in automated manufacturing systems

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    Cataloged from PDF version of article.The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose "ve alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The "rst algorithm is an exact algorithm which "nds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically signi"cant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters

    Single CNC machine scheduling with controllable processing times to minimize total weighted tardiness

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    Cataloged from PDF version of article.Advanced manufacturing technologies, such as CNC machines, require significant investments, but also offer new capabilities to the manufacturers. One of the important capabilities of a CNC machine is the controllable processing times. By using this capability, the due date requirements of customers can be satisfied much more effectively. Processing times of the jobs on a CNC machine can be easily controlled via machining conditions such that they can be increased or decreased at the expense of tooling cost. Since scheduling decisions are very sensitive to the processing times, we solve the process planning and scheduling problems simultaneously. In this study, we consider the problem of scheduling a set of jobs on a single CNC machine to minimize the sum of total weighted tardiness, tooling and machining costs. We formulated the joint problem, which is NP-hard since the total weighted tardiness problem (with fixed processing times) is strongly NP-hard alone, as a nonlinear mixed integer program. We proposed a DP-based heuristic to solve the problem for a given sequence and designed a local search algorithm that uses it as a base heuristic

    A new lower bounding scheme for the total weighted tardiness problem

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    Cataloged from PDF version of article.We propose a new dominance rule that provides a sufficient condition for local optimality for the 1\\Sigma w(i)T(i) problem. We prove that if any sequence violates the proposed dominance rule, then switching the violating jobs either lowers the total weighted tardiness or leaves it unchanged. Therefore, it can be used in reducing the number of alternatives for finding the optimal solution in any exact approach. We introduce an algorithm based on the dominance rule, which is compared to a number of competing approaches for a set of randomly generated problems. We also test the impact of the dominance rule on different lower bounding schemes. Our computational results over 30,000 problems indicate that the amount of improvement is statistically significant for both upper and lower bounding schemes. (C) 1998 Elsevier Science Ltd. All rights reserved

    An analysis of cyclic scheduling problems in robot centered cells

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    Cataloged from PDF version of article.The focus of this study is a robot centered cell consisting of m computer numerical control (CNC) machines producing identical parts. Two pure cycles are singled out and further investigated as prominent cycles in minimizing the cycle time. It has been shown that these two cycles jointly dominate the rest of the pure cycles for a wide range of processing time values. For the remaining region, the worst case performances of these pure cycles are established. The special case of 3-machines is studied extensively in order to provide further insight for the more general case. The situation where the processing times are controllable is analyzed. The proposed pure cycles also dominate the rest when the cycle time and total manufacturing cost objectives are considered simultaneously from a bicriteria optimization point of view. Moreover, they also dominate all of the pure cycles in in-line robotic cells. Finally, the efficient frontier of the 3-machine case with controllable processing times is depicted as an example

    Lot sizing with piecewise concave production costs

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    Cataloged from PDF version of article.We study the lot-sizing problem with piecewise concave production costs and concave holding costs. This problem is a generalization of the lot-sizing problem with quantity discounts, minimum order quantities, capacities, overloading, subcontracting or a combination of these. We develop a dynamic programming algorithm to solve this problem and answer an open question in the literature: we show that the problem is polynomially solvable when the breakpoints of the production cost function are time invariant and the number of breakpoints is fixed. For the special cases with capacities and subcontracting, the time complexity of our algorithm is as good as the complexity of algorithms available in the literature. We report the results of a computational experiment where the dynamic programming is able to solve instances that are hard for a mixed-integer programming solver. We enhance the mixed-integer programming formulation with valid inequalities based on mixing sets and use a cut-and-branch algorithm to compute better bounds. We propose a state space reduction–based heuristic algorithm for large instances and show that the solutions are of good quality by comparing them with the bounds obtained from the cut-and-branch

    Stochastic lot sizing problem with controllable processing times

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    Cataloged from PDF version of article.In this study, we consider the stochastic capacitated lot sizing problem with controllable processing times where processing times can be reduced in return for extra compression cost. We assume that the compression cost function is a convex function as it may reflect increasing marginal costs of larger reductions and may be more appropriate when the resource life, energy consumption or carbon emission are taken into consideration. We consider this problem under static uncertainty strategy and α service level constraints. We first introduce a nonlinear mixed integer programming formulation of the problem, and use the recent advances in second order cone programming to strengthen it and then solve by a commercial solver. Our computational experiments show that taking the processing times as constant may lead to more costly production plans, and the value of controllable processing times becomes more evident for a stochastic environment with a limited capacity. Moreover, we observe that controllable processing times increase the solution flexibility and provide a better solution in most of the problem instances, although the largest improvements are obtained when setup costs are high and the system has medium sized capacities
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