Analyzing Production Schedules

More powerful, low cost computing systems and software development tools that allow creation of fast, easy-to-maintain software have driven the cost of sophisticated software down with no compromise in performance. For manufacturing, the most visible example of enhanced price/performance software is finite capacity scheduling (FCS) systems. As with any tool, the real value in understanding what the results have to say.

So What is FCS Exactly?

Finite capacity scheduling emerged as a response to the limitations of infinite capacity scheduling that is common to all MRPII systems. The basic problem in MRPII is that the production plans lack realism since they are produced under the assumption that all resources have an infinite capacity to perform work. As any production manager knows, the real world does not work this way, and many of the problems of resource underutilization, excessive inventories and work-in-progress, and job lateness relate back to the inaccuracy of the production plan.

FCS itself is not a new idea, and for many years versions of FCS emerged to enhance the accuracy of the production plan to better manage inventory, resources, and customer satisfaction. The first systems were simple, involving the measure of the primary resource to do work, and either scheduling forward from the current date for new orders (single constraint finite forward scheduling - FFS). Multiple constraints were later added to provide more accurate modeling of the production resources. About the same time backwards and bi-directional scheduling began to appear in some packages.

Then the explosion of different production philosophies appeared to challenge the American ideas of MRP and mass manufacturing, notably just-in-time and theory of constraints. Variations of FCS systems emerged, some committed to supporting one of the three competing philosophies. This forced the innovative FCS companies to face the reality that to remain flexible, the new FCS systems would need two basic improvements:

1. Model any production philosophy and
2. Extend the model with rules that capture the nuances of the competitive model of the client as it related to scheduling. To achieve these goals, the new FCS systems had to support job-based, resource-based, and event-based modeling. By applying any one or a combination of these three views of the production floor, a FCS model can produce the accuracy that adds value to the business goals of the enterprise.

The Value of FCS

The value of FCS comes from the accuracy not obtainable in tradition infinite capacity planning. With this accuracy, raw material levels can be in sync with demand from the production floor, customer service levels improve since throughput is predictable and due dates are more reliable, work-in-progress reduced, and better resource utilization means hidden capacity is uncovered. These are strategic goals, but there is also a very important operational improvement as well.

Figure 1: Time-Cost Plot for Manufacturing

Figure 1 shows that for a given need to produce goods (or provide a service), there is an optimal point in time and cost where goals are met. In manufacturing there are two means to advance the delivery time: Expedite the order, or create WIP to have excess products to deliver against. One obvious drawback with WIP is that the value-added is not recovered quickly; therefore the manufacturer has lost the time-value of the money. What is not obvious is that expediting costs much more than WIP, because of the ripple through impact of moving other orders around (which is to say pushing orders later in delivery) and otherwise disrupting the optimal point for all the other orders, accumulating a much greater financial impact than creating excessive WIP.

It is difficult in the real world, where the product-quantity mix can change daily, to determine these optimal points, which is precisely where the FCS has the greatest value. A good FCS can compute scheduling solutions that set these points for all orders, within the context of the production philosophy and the business goals to be achieved. However, the scheduling solution cannot exist in a vacuum, and the output of a scheduling system needs to provide useful data in order to fulfill its other role as a decision support tool.

Analyzing Schedules

One of the primary advantages of a FCS system is that it offers the user a 'what if' tool to try different methods of scheduling or different dispatching rules, routings, or constraints that are in use. This is because a truly interactive FCS system is not a 'black box' that just gives the 'result' of a scheduling run. It provides in addition a mechanism by which, with the aid of analytical tools (which in its very simplest form is to put the data in front of an experience scheduler), alternative schedules can be generated and compared. There are a number of ways by which scheduling systems offer tools to display and analyze the results of scheduling runs. These include:

• Gantt Charts and Schedule Performance metrics
• Order Trace Charts
• Due date Compliance
• Bottleneck Identification
• Job Analysis
• Material Allocation