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Research Article

Optimizing milk-run system and IT-based Kanban with artificial intelligence: an empirical study on multi-lines assembly shop floor

, ORCID Icon &
Article: 2179123 | Received 06 Nov 2022, Accepted 06 Feb 2023, Published online: 23 Feb 2023

Figures & data

Figure 1. Research framework.

Figure 1. Research framework.

Figure 2. Layout of the shop floor.

Figure 2. Layout of the shop floor.

Figure 3. (a) Kanban cards. (b) Kanban rack.

Figure 3. (a) Kanban cards. (b) Kanban rack.

Figure 4. ITK workflow.

Figure 4. ITK workflow.

Figure 5. HIS algorithm.

Figure 5. HIS algorithm.

Table 1. Line-Path Incidence matrix.

Table 2. Case # 1 – Q = 35.

Figure 6. Paths #4; #14.

Figure 6. Paths #4; #14.

Figure 7. MRS paths.

Figure 7. MRS paths.

Table 3. Demand required.

Table 4. Path times.

Table 5. MRS quantity Qmin = 35.

Table 6. MRS quantity Qmin = 40.

Table 7. MRS quantity Qmin = 45.

Table 8. MRS quantity Qmin = 50.

Table 9. MRS quantity Qmin = 55.

Figure 8. LT values.

Figure 8. LT values.

Figure 9. MHT values.

Figure 9. MHT values.

Figure 10. WiP values.

Figure 10. WiP values.

Figure 11. WS values.

Figure 11. WS values.

Figure 12. MS values.

Figure 12. MS values.

Figure 13. A comparison between the mean value of each parameter and the Qmin is shown in , which highlights the dependence of LT, MHT, WIP, WS and MS with the quantity shipped by the MRS.

Figure 13. A comparison between the mean value of each parameter and the Qmin is shown in Figure 13, which highlights the dependence of LT, MHT, WIP, WS and MS with the quantity shipped by the MRS.