5. Description of the VMI supply chain simulation model
The difference equations required to model our version of the VMI scenario are shown in Appendix A. These difference equations can quickly be turned into a mathematical model of the VMI supply chain by using z-transforms. The formulation and exploitation of such a mathematical model is not presented in this contribution due to space restrictions but can be found in Disney (2001) and Disney and Towill (2002a,b). Disney and Towill (2002a) is a comprehensive analysis of the stability of a VMI supply chain and a single echelon of a traditional supply chain. In Disney and Towill (2002b) the VMI model is studied to determine “good” parameter values for a range of circumstances. Thus, we are able to compare one VMI system to another. What this paper uniquely contributes is to take a selection of these VMI systems and compares them with a traditional two-stage supply chain as a benchmark. Hence we investigate the benefits or otherwise of moving from the traditional supply chain with all its real-world faults to a VMI scenario. We know the VMI system is representative of a real-world application (Disney et al., 2001); however, this comparison is restricted to simulation of these models. Herein, the difference equation representation will be exploited. The difference equations may be quickly realised through “spreadsheet” applications such as Microsoft Excel. Difference equations can also be implemented in standard computer languages with relative ease, as shown in Table 1. The equations in Appendix A describe the VMI supply chain when individual stock holding points and transportation despatches are modelled explicitly, whereas for simplicity the pseudo-code in Table 1 models inventory and transportation as based on virtual consumption. Of course, the two systems are exactly the same when focusing on the production order rate (ORATE). A fixed production lead-time of 4 time units will be used throughout this paper.
5. คำอธิบายของ VMI แบบจำลองโซ่อุปทานThe difference equations required to model our version of the VMI scenario are shown in Appendix A. These difference equations can quickly be turned into a mathematical model of the VMI supply chain by using z-transforms. The formulation and exploitation of such a mathematical model is not presented in this contribution due to space restrictions but can be found in Disney (2001) and Disney and Towill (2002a,b). Disney and Towill (2002a) is a comprehensive analysis of the stability of a VMI supply chain and a single echelon of a traditional supply chain. In Disney and Towill (2002b) the VMI model is studied to determine “good” parameter values for a range of circumstances. Thus, we are able to compare one VMI system to another. What this paper uniquely contributes is to take a selection of these VMI systems and compares them with a traditional two-stage supply chain as a benchmark. Hence we investigate the benefits or otherwise of moving from the traditional supply chain with all its real-world faults to a VMI scenario. We know the VMI system is representative of a real-world application (Disney et al., 2001); however, this comparison is restricted to simulation of these models. Herein, the difference equation representation will be exploited. The difference equations may be quickly realised through “spreadsheet” applications such as Microsoft Excel. Difference equations can also be implemented in standard computer languages with relative ease, as shown in Table 1. The equations in Appendix A describe the VMI supply chain when individual stock holding points and transportation despatches are modelled explicitly, whereas for simplicity the pseudo-code in Table 1 models inventory and transportation as based on virtual consumption. Of course, the two systems are exactly the same when focusing on the production order rate (ORATE). A fixed production lead-time of 4 time units will be used throughout this paper.
การแปล กรุณารอสักครู่..
