Kanban control systems have been around for decades and have been used to control workin-process of manufacturing systems. Lately many variations of the basic control system have been developed; however much of the work in the development and comparision of control systems has focused on a single stage manufacturing system producing a single product type.In this research we present optimization procedures for multiple product kanban control systems, such as Base Stock, Traditional Kanban Control System and Extended Kanban Control System (both dedicated and shared type). We then conduct a detailed simulation study to compare the performance of the systems using a common total cost measure.Numerical results show that the dedicated and shared extended kanban control systems outperform the other two systems. The study also shows that, inspite of their different schematics and contrary to conventional wisdom, the performance of dedicated and shared extended kanban control systems doesn't differ much.

A Kanban Control System (KCS) is a manufacturing/production control system that uses Production Authorization Cards (PAC or also known as Kanbans) to control the Work-In-Process (WIP) of every stage of the Manufacturing Process (MP). It is attached to every finished product, such that once a customer request is received, it is detached and relayed upstream to re-initiate the production process. Thereafter, the finished product is handed over to the customer. In this thesis, different types of KCS were described and categorized according to their operating behaviours. Three significant pull systems, namely Base Stock (BS), Traditional Kanban Control System (TKCS) and Extended Kanban Control System (EKCS) were investigated. The make-up of the EKCS is a hybrid of both the BS and TKCS combined. It was initially proposed to leverage on the strengths of these two systems. However, thus far, all relevant studies only reported on the qualitative aspect of these systems, but none on their quantitative impact. Thus, the purpose of this research was to study the quantitative performance difference of these systems. Specifically, this thesis's objective was to draw insights from the differences in performance of the EKCS against the BS and TKCS. This study was conducted in two main phases: first, the analyses of Single Product KCS (SP/KCS) was carried out, followed by Multiple Products KCS (MP/KCS). Both studies assumed only a Single Stage/Server (SS). Matlab was used to optimize the systems, and Arena version 12 used to simulate different parameter settings. The performance comparison was benchmarked with KPIs such as Fill Rate, Average Inventory Level and Average Customer Cycle Time. The results showed that EKCS outperforms its predecessors, TKCS and BS in all scenarios. There were four key contributions to this research. Firstly, a method was proposed to determine the optimal size of Base Stock, S*, and Number of Kanbans, K*, in a SS/SP/EKCS, which was never done before. Secondly, this report confirmed that EKCS outperforms TKCS and BS in both single and multiple product scenarios. This performance comparison was ensured through simulations. Third, methods to optimize both Multiple-Product Dedicated (MP/De) and Shared (Sh) EKCS systems were proposed. This also had never been done before. Fourth, this research showed iii that both De and Sh/EKCS are equivalent. They operate the same way even though their schematics look different. Despite constant praise for EKCS' performance in the kanban literature, this thesis shows that it outperforms its predecessor, TKCS, only slightly, and only in certain niche scenarios. The worst-performing system turns out to be BS, as it holds a lot of stock in almost all scenarios. Hence, this research has confirmed again that lean or pull production is more effective than push. Current factory floor managers using BS as their production control strategy should consider switching over to the TKCS,

This paper presents a simulation experiment comparing the Single Stage, Single Product Base Stock (BS), Traditional Kanban Control System (TKCS) and Extended Kanban Control System (EKCS). The results showed that BS incurs the highest cost in all scenarios; while EKCS is found to be effective only in a very niche scenario. TKCS is still a very powerful factory management system to date; and EKCS did not perform exceptionally well. The only time EKCS did outperform TKCS was during low demand arrival rates and low Backorder (C b ) and Shortage costs (C s ). That is because during then, it holds no stock. The most important discovery made here is that EKCS becomes TKCS once it has base stock (or dispatched kanbans). The results have also evinced the strength of the pure kanban system, the TKCS over BS. Hence managers using BS should consider upgrading to TKCS to save cost.

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