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Taking the Uncertainty Out of Planning and Scheduling


By Rob Kranz, Director/GM
Published: October 3, 2017

Categories: Articles, Manufacturing, Project Management, Supply Chain/Logistics

An Old Danish proverb says,

It is difficult to make predictions, especially about the future. 

Yet, businesses rely upon predictions and forecasts to make decisions each and every day; for better or for worse.

One of the problems with predictions is that they often rely upon simplified assumptions or incomplete data.  In the face of uncertainty or complexity, idealized assumptions are made in hopes that they adequately describe real-world performance or ensure that the prediction is “close enough.”  On average, the prediction might be close enough.  However, there will always be times when circumstances combine to destroy the accuracy of the prediction, leaving businesses wondering what went wrong.

One area that seems particularly prone to these sorts of simplified assumptions is planning and scheduling.  For most large organizations, planning and scheduling algorithms have become part of the ERP system.  These algorithms tend to be pretty complicated.  However, our experience has shown that many of them rely upon relatively simple assumptions related to process performance and simplified heuristics that help define what makes an acceptable schedule or plan.  The end result is a plan that doesn’t fit the reality of what the process is capable of delivering.  Ultimately, this can lead to failure to meet customer requirements and the business implications that come with it.

But, what if it were possible to validate the accuracy of these schedules before finalizing them in operations?  What if it were possible to use current process information, including actual process variability to test these schedules?

With Arena, this sort of testing/validation of plans and schedules is easily accomplished.  The result of this simulation is a clearer view of the risk profile associated with the current schedule.  In other words, what is the risk that each order in this schedule is going to be completed within the timeframe required by the customer?

The basic methodology is straightforward:

  1. Develop and validate a model of your process in Arena.

  2. Read in current state information (including variabilities, breakdown frequencies, resource levels, etc…) from your process.

  3. Take the recommended schedule or operating plan and run this through the Arena simulation model.  In fact, you need to run multiple replications of this schedule in order to better understand the statistics and risk profile.

  4. The simulation can provide statistics on likelihood of completing orders on time, the utilization of equipment and associated resources as well as identifying potential bottle necks in the system via queue statistics. 

  5. If the results of this schedule show unacceptable risk in order delivery, you can adjust the schedule or other parameters you do have control over (Labor, Equipment Availability) and re-run to see if the situation improves.

A number of Arena clients have been putting this to use for many years to improve their business forecasts, drive higher throughput in their operations and improve customer satisfaction.

Here are a couple of examples from actual Arena customers:

In this example, a manufacturing organization is using Arena to evaluate how their current customer orders impact line loading based upon the normal production allocation rules employed in their business.

From these charts, it is clear that the current customer order mix and scheduling rules were going to overload Plant 1 while other plants had spare capacity to take on additional orders.  This enabled the organization to re-balance orders to different lines for more efficient operations and higher on-time delivery of orders.

In this 2nd example, an aerospace company is using Arena to evaluate the production schedules for certain parts.  The Arena simulation model enables them to better understand the interdependencies of various part manufacturing schedules.  Based upon this resulting chart, they can easily identify potential schedule delays and risks before they occur.

Predictions are always fraught with uncertainty.  However, simulation gives you the ability to test and validate the impact of that uncertainty on your business performance so that you can take corrective actions in advance.

If you would like to learn more about how Arena could enable your business to optimize scheduling and planning, please feel free to contact us.


The Author

Rob Kranz

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