Simulation-based tool for theory of constraints (TOC) implementation | |
| Author | Chompoonoot Kasemset |
| Call Number | AIT Thesis no.ISE-05-11 |
| Subject(s) | Theory of constraints (Management)--Simulation methods Manufacturing processes |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. ISE-05-11 |
| Abstract | This study presents a simulation-based tool for the implementation of management policies based on Theory of Constraints. A simulation tool is created based on ARENA Software by building separately the physical flow model and the information flow model with interacting points clearly defined. This tool is applied as an evaluated tool for TOC implementation. In addition to the proposed procedure used follows the five steps of TOC Implementation. The physical flow generic model provides utilization statistics of each process for the analysis of current system performance under the push policy. Bottleneck identification starts by selecting bottleneck candidates from both simulation results and the bottleneck rate calculated from the concept of Factory Physics. Experiments are then carried out to confirm the real bottleneck resource. After bottleneck stations are identified, the exploitation step is carried out by applying the concept of transfer lot size. The information flow model is applied via the Drum-Buffer-Rope (DBR) system to improve the system performance in subordination step. The time buffer in DBR is represented as the waiting line in front of the bottleneck and the size of the time buffer is estimated by using queuing formula and critical WIP concept to conduct the buffer size evaluation. Rope is used to control the material releasing and protect the excess work in process by blocking the unneeded part from being processed. The throughput data can be obtained from simulation experiments and compared with the target demand. The concept of mean confident interval comparison is applied when comparing throughput data. The procedure stops when the target demand is met. Numerical examples are shown to illustrate the proposed procedure. In addition, this procedure can be used as the guideline when the simulation is used in TOC implementation. Furthermore, the generic model can be easily modified for other cases. |
| Year | 2005 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ISE-05-11 |
| Type | Thesis |
| School | School of Advanced Technologies (SAT) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Voratas Kachitvichyanukul; |
| Examination Committee(s) | Anulark Techanitisawad ;Huynh Trung Luong; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2005 |