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Many years ago I attended my first APICS conference. I was excited about the opportunity to meet the leading experts of the trade and learn from them. During one of the breaks I talked to one of the "pillars of knowledge" about MRP, and asked him for his opinion on enhance­ments to MRP. "Oh, no!" he said. "The last thing we need is better software. We don't even know how to use the software we have now." 1 was deeply disappointed. By that time I was already frustrated by my lack of ability to answer my management's very basic questions, such as, "When will I get my parts? When will we deliver our product to the customer? How should I staff the production line? What can we do to improve our performance?" These were all very basic questions that MRP, as it existed, could not answer. All I had from MRP was the plan that I was directed to execute and a very thick report telling me why I could not do it. Being in the electronics assembly industry and work­ing mostly on government contracts compounded our problem. Some­how no matter how good our on-time delivery was, we always had parts waiting for other parts to come in. I felt these "parts in waiting" could be used somewhere else, but MRP provided no help in telling me where or when.


Years passed. I had an opportunity to experiment and get better insight to the limitations of MRP. I learned about the theory of con­straints (TOC), which gave me a direction for a solution, but I still couldn't find tools to help me. In recent years I came across the term "advanced planning and scheduling" (APS), sometimes referred to as "advanced planning and optimization" (APO). I checked into it and all of a sudden felt vindicated. Here were top-notch vendors, openly pro­claiming (or admitting, depending on whether they were ERP vendors or a competitor "best of breed") the limitations of MRP, and offering standard tools that provided answers to my questions!


I continue to attend APICS conferences and talk to colleagues and practitioners. When I share my excitement about these developments, I often receive blank stares or puzzled looks, when people wonder what I am talking about. Literature about the topic is not readily available. Most of it is buried in vendors' advertisements, which tends to have lengthy praises of their product, but are short on explanations about the issues. This is where I come in to provide the novice practitioner an insight into what this is all about.


APS is one the most important advances in business applications. It is more of a revolutionary rather than an evolutionary tool or an incre­mental improvement process. It was enabled only in recent years by the advances in computer technology, enabling the desktop PC to per­form an amazing volume of processing at an incredible speed, thus providing the user with a responsive decision support tool, rather than drowning him/her in a flood of exception messages. It is based on three main features:

      constrained-based planning



Let's explain each one of them.


We all know MRP is a powerful planning tool. We tell the computer what we want to do and the desired end result, and the computer draws a detailed plan for execution. There is nothing wrong with that, and this is the way it should be, since at that time we may not know what are our constraints, as well as the variability of these constraints. Only when we have the plan and commit resources to execute it we can identify our constraints and limitations. MRP is doing that part also: these are all the exception messages we get on material unavailability and capacity over­loads. However, the problem is that MRP makes a basic assumption that we have full control over these resources, so just by telling us what is wrong, we can change and make it right. Of course, this is easier said than done. The reality of manufacturing is that in most cases we cannot change 100 percent of the exceptions and conflicts. In theory, then, we should change the plan. But change the plan to what? Here is where our handicap lies: MRP does not tell us, assuming our constraints are real, what will happen, but only the plan that will not happen! Here comes a new process called "available to promise" (ATP) or my preferred term, "available to deliver" (ATD), which tells us what we can do. The differ­ence between ATP and ATD is the focus: ATP is mostly a one-time snap­shot activity of knowing when we can promise delivery to the customer at the time it is ordered. ATD is an ongoing, repetitive process, taking into account changes in resource availability between time of order and time of delivery (which may be quite a long period, providing ample opportunity for changes to occur). Let's compare MRP to ATD. MRP is characterized by

      top-down process (set-back scheduling)

      total critical schedule. All activities are planned for the latest possible date. Every miss impacts delivery (which causes us to add "invisible" safety margins to our lead times and buffer the master schedule from the customer orders schedule).

      assumes no constraints

      no need for a full-level pegging of the requirements, so they are usually consolidated at each indenture

      show us what we want to happen.


      is a bottom-up process (forward schedule). It starts from the material availability schedule, the suppliers' promised dates, accounts for capacity constraints of labor and equipment, and goes up the BOM structure and process flow to finished product delivery.

      is a noncritical schedule. All activities are identified at the earliest time they are possible. This provides the planner visibility of the constraints (critical path and critical parts) and a choice between the latest date before impacting delivery and the earliest possible date to start. This enables other requirements to be handled like level loading the production line to capacity.

      assumes all constraints are real, prioritizes them by criticality, pointing out which one to address first, and which one should be ignored, once we cannot change the critical ones

      requires full-level pegging and single-level pegging, linking con­
straints to their impact on the end results

      shows us what will happen based on the realities of what we cannot or will not change.

To Be Continued

For balance of this article, click on the below link:

Lean Manufacturing Articles and click on Series 11

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