先進規劃排程(Advanced Planning and Scheduling)就是考量滿足客戶訂單與企業有限資源條件下，如何找出可行的生產排程。目前以符合限制理論(TOC, Theory of Constraint)中之限制驅導式排程(DBR, Drum Buffer Rope)來實作之先進規劃排程系統，大部分均主要著墨在流線式生產(Flow-shop)，也就是在整個製造的流程裡如何達到最大的產出，讓整個系統達到最大的產能，產能愈大，代表整個系統的效能愈好，期限制主要是在設備的產能。但是對於接單式生產(Job-shop)，除了要有足夠的產能來滿足訂單的需求外，還必須在客戶指定的時間交貨，提早交貨或遲交都是客戶不樂見的。所以在接單式生產除了要讓設備發揮最大產能之外，還必須考慮在正確的時間點完成。
Do the right thing right with right people.
這句話，在接單式生產製造業來說應該是
Do the right order right with right device on right time.
任何系統總是會有瓶頸與限制，而限制驅導式排程(DBR)針對單一瓶頸作生產計劃，追求該瓶頸的最大化產出，在一些系統的實作上確實也有不錯的表現，但是對於台灣的中小企業接單式生產︰少量、多樣、零件製造、成品組裝的複雜生產型態，本論文提出了更好的多重限制驅導式排程(Multi-DBR)模式，在產能與時間的限制下能達到較佳的有效產出。多重限制驅導式排程(Multi-DBR)是針對多個瓶頸內之每個瓶頸來追求其最大化產出，以利整個系統的有效產出達到較佳的狀態。因此在效能的計算及交期差異上，多重限制驅導式排程(Multi-DBR)均優於限制驅導式排程(DBR)。

Advanced Planning and Scheduling System (APS) is usually used to find the most feasible and suitable production scheduling under the constraints of customer orders and enterprise resources. Most APS systems, based-on the Drum Buffer Rope (DBR) of Theory of Constraint (TOC), focus on the flow-shop to produce the maximum amount of products within the whole manufacture flows. When a manufacturer can produce maximum quantity of output, the flow-shop system is efficiency. While, the job-shop has to not only fulfill the customer orders' requests but also pay attention to the requested delivered time, not too early and not too late but right at the delivery dates. A job-shop needs not only to produce the maximum amount of products but also to deliver the products at the right time.
The quote:
“Do the right thing right with right people.”,
should be interpreted for manufacturers of job-shop as:
“Do the right order right with right device on right time.”　
A lot of systems have bottlenecks and limitations at some point. DBR builds production plans based on a single bottleneck and the plans produce the maximum throughput of the bottleneck. While DBR is very efficient on large scale productions, it is not good at planning for small-to-medium job-shop productions with small quantity, diversity products, timely orders and multiple combinatorial parts. This study proposes a Multi-DBR model that focus on multiple bottlenecks of a production system in order to get the best throughput for every bottleneck and therefore is very suitable for small-to-medium scale productions. With proper fitting functions, Multi-DBR has been proved performing better than DBR in production efficiency and in fitting the right delivery dates when used in a real job-shop.

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