Production scheduling software applications, or constraint-based scheduling, gives manufacturers a tool to create the most optimal and feasible production schedules. The best of these applications employ genetic algorithms to arrange production schedules for the best possible outcomes taking into consideration a number of constraints, which are defined by the user. These programs cycle through numerous possibilities, until the best schedule is created which best meets all of the criteria. These scheduling applications need accurate data in order to arrive at the best possible scheduling line up.

The most effective systems demand correct routings which reflect steps in the manufacturing process the proper order, and definition about whether steps can be parallel or sequential. The amount of careful planning that is required for a successful system to be implemented is one of the big stopping points in implementation, but the effort will pay off.

System users must define accurate routings in terms of operation sequence and operation overlap. Resource constraints also need to be accurately documented, as well as run and set-up times. Tools like constraint based production scheduling systems should not be thought of as a magic solution, but rather as a tool which requires accurate data in order to produce executable schedules which are understood by users.

When using constraint based scheduling systems within an enterprise resource planning system, ERP which is well integrated with other aspects of the business will generally also be a more powerful tool in terms of production scheduling. A number of variables which reside in non-manufacturing software system functionality can affect capacity. A well integrated system will be able to update the other business systems of changes in the schedule.

Apart from the immediately apparent capacity management benefits of constraint based scheduling, there are several less obvious analytical capabilities. Scheduling functionality typically allows users to perform predictive analyses (what-if) when changes are made to an optimized schedule. This functionality also provides predictive analyses on the effects of adding capacity in the plant. What this enables manufacturers to see is whether or not equipment purchases will deliver an increase in capacity, or if they will result in some other bottleneck further downstream in their manufacturing process.

This is a good article on production scheduling Tuppas Blog Scheduling. Tuppas offers a nice scheduling capability. They have a lot of different interfaces to choose from.