Browsing by Author "Ho, TF"

Now showing 1 - 2 of 2

Heuristic dispatching rule to maximize TDD and IDD performance
(2004-12-15)
Ho, TF
;
Li, RK
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Although mean flow time and tardiness have been used for a long time as indicators in both manufacturing plants and academic research on dispatching rules, according to Theory of Constraints (TOC), neither indicator properly measures deviation from production plans. TOC claims that using throughput dollar-day (TDD) and inventory dollar-day (IDD) can induce the factory to take appropriate actions for the organization as a whole, and that these can be applied to replace various key performance indices used by most factories. However, no one has studied dispatching rules based on TDD and IDD performance indicators. The study addresses two interesting issues. (1) If TDD and IDD are used as performance indicators, do those dispatching rules that yield a better performance in tardiness and mean flow time still yield satisfactory results in terms of TDD and IDD performance? (2) Does a dispatching rule exist to outperform the current dispatching rules in terms of TDD and IDD performance? First, a TDD/IDD-based heuristic dispatching rule is developed to answer these questions. Second, a computational experiment is performed, involving six simulation examples, to compare the proposed TDD/IDD-based heuristic-dispatching rule with the currently used dispatching rules. Five dispatching rules, shortest processing time, earliest due date, total profit, minimum slack and apparent tardiness cost, are adopted herein. The results demonstrate that the developed TDD/IDD-based heuristic dispatching rule is feasible and outperforms the selected dispatching rules in terms of TDD and IDD.
Mixing macro and micro flowtime estimation model: wafer fab example
(1999-07-20)
Tseng, TY
;
Ho, TF
;
Li, RK
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Accurately predicting the order flowtime for a wafer fab is a critical task. Previous investigations involving flowtime estimation of the regression approach have extensively applied the macro flowtime estimation concept. The 'macro' flowtime estimation concept constructs only one aggregate model to estimate the flowtime as a whole. In contrast, the 'micro' flowtime estimation approach constructs an individual regression model for each stage of operation to estimate its individual flowtime. The cumulative order estimated flowtime is then the sum of the individual estimated operation flowtime. Each approach has its own merits and limitations. Therefore, in this study we examine the feasibility of mixing the macro and micro flowtime estimation models. Comparing the proposed model with a variety of macro and micro models reveals that the mixed macro and micro flowtime estimation model can achieve a balance between flowtime estimation error and model complexity.