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Articles by Tian- Syung Lan
Total Records ( 3 ) for Tian- Syung Lan
  Tian- Syung Lan
  This study not only applies Material Removal Rate (MRR) into the objective function mathematically, but also implements calculus of variations to resolve the dynamic machining control problem comprehensively. In addition, the optimal solution of the Machining Project Control (MPC), model is proposed and the decision criteria to determine the optimal solution are also recommended. Moreover, the computerized analyses with a numerical simulation to compare with the traditional machining model are fully prepared. This study definitely contributes the applicable approach to dynamic control of the material removal rate and provides the efficient tool to concretely optimize the cost of a machining project for operation research engineers in today`s machining industry with profound insight.
  Tian- Syung Lan
  A DMC (Dynamic Machining Control) model to achieve the optimal control of Material Removal Rate (MRR) for a cutting tool undergoing the considerations of fixed tool life and maximum machining rate is introduced in this research. This study not only applies material removal rate dynamically into the DMC model, but also implements Calculus of Variations to comprehensively optimize the control of material removal rate. In addition, the optimal solution for the dynamic control of material removal rate is also provided. Moreover, the comparison of DMC model and traditional machining model is fully discussed. Furthermore, the decision criteria for selecting the optimal solution of the machining model are presented. This study definitely generates the adaptive concept to dynamically control the material removal rate and provides the efficient tool to concretely optimize the profit of a cutting tool for operations research engineers in today`s manufacturing with profound insight.
  Tian- Syung Lan , Chih- Yao Lo and Cheng- I Hou
  Through the proposed model in this study, the production control with the consideration of workforce scheduling for advanced manufacturing systems becomes realistically and concretely solvable. This study not only meditates the concept of balancing machine productivity and human ability into the objective, but also implements Calculus of Variations to optimize the profit for a deterministic production quantity. In addition, the optimum solutions of dynamic productivity control and workforce scheduling are comprehensively provided. Moreover, the decision criteria for selecting the optimum solution and the sensitivity analysis of the critical variables are fully discussed. This study definitely contributes the applicable strategy to control the productivity and workforce in manufacturing and provides the valuable tool to conclusively optimize the profit of a machining project for operations research in today`s manufacturing industry with profound insight.
 
 
 
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