Companies have made significant investments in their ERP (Enterprise Resource Planning) systems; however these systems typically fall short with production scheduling. Although there are a number of Advanced Planning and Scheduling (APS) products on the market designed to integrate detailed production scheduling into the overall ERP solution, these solutions have some widely recognized shortcomings. For the most part the ERP system and day-to-day production remain disconnected.
A critical problem with the traditional APS approach is that it requires that all the data be fully known and deterministic. For example, all processing times must be fixed and there can be no unexpected events or delays. Hence the resulting schedule with APS is by nature optimistic, and is typically very different from what occurs in the real facility. It is common that what starts off as a feasible schedule turns infeasible over time as variation and unplanned events degrade performance. It is normal to have large discrepancies between predicted schedules and actual performance. To protect against delays the scheduler must buffer with some combination of extra time, inventory, or capacity; all adding cost to the system.
With Simio Scheduling Software, you can build a simulation model that fully captures both the detailed constraints and variations within your system. This allows you to use the model in two different ways. The model you generate gives a detailed schedule and plan that is executed in a perfect environment (APS approach) where machines do not break, process times are always constant, and materials arrive on time. Then you can replicate the same simulation model, but this time with variation turned on and perform a probabilistic analysis to estimate the underlying risks associated with the schedule. With this model, the risk measures generated include the probability of meeting your defined targets, as well as expected, pessimistic and optimistic targets.
Simio Scheduling Software has Entity Gantt Charts integrated into the software. These charts display corresponding risk measures for each of your orders. In the chart shown below, the markers to the right indicate the target due date and the value in each marker indicates the probability of shipping on time. You can see that Order01 should make the target, the high variability of Order03 puts it at risk, and the lack of slack time in Order04 puts it at a high risk of making the target set by you.
With the knowledge gained from Simio Scheduling Software and the Entity Gantt Chart, you can take early action in the operational plan to mitigate the risks and reduce cost. You are provided with a realistic view of expected schedule performance and can plug in specific alternatives such as overtime or expediting external material/components from suppliers and see their impact on both risk of meeting schedule targets, and the cost of mitigating those risk. Thereby providing you with operational strategy at minimum cost.
The model built using Simio Scheduling Software allows for simulation of the flow of a specific set of orders. Using this model, not only do you get detailed logic for planning/scheduling day to day operations, but you can evaluate the long term impact on performance of capital equipment purchases, change in process flows, or new product introductions of your facility design.
Simio Scheduling Software brings finite capacity scheduling and advanced planning and scheduling functionality to Wonderware MES. Our patented approach is the first to automate comparing a deterministic schedule with a variation adjusted schedule to let you effectively deal with uncertainty, such as: breakdowns, unplanned events and material shortages. Using Simio and Wonderware MES together, you can reschedule resources to acceptable levels of risk. Simio also allows you to take advantage of your existing data to quickly and automatically build a scheduling model, and that can be enhanced to accurately capture complexity unique to your system.
To learn more about Simio and Wonderware's interface and to receive a free book, visit here.
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