Capacity Planning - Constrained or not?
Manufacturing companies plan how much material and capacity they need to produce a product. After securing the material and capacity, they execute and monitor the production. Business applications provide them the functionality to calculate the material and capacity requirements. In order to generate a realistic production plan, most companies consider material availability as a key constraint. The key question is whether to constrain the capacity or not given that your business application may allow you to do so.
Applications use resources and calendars to model capacity. Resources can be either human or machinery. Calendars dictate when and how much of the capacity is available. Some products consume more capacity than others. The more complex the product is, the more capacity it consumes. Thus, capacity cannot be tracked in terms of the number of pieces produced. The consumption must be normalized. Most applications convert units to hours. The capacity is stated in terms of time. The consumption is declared in terms of how much time is needed to produce a single product.
During production planning, the capacity consumption can be calculated after taking into account material availability. The capacity requirement can then be compared against the available capacity. When the required capacity is below the available capacity, the production can be scheduled without any issues. When the required capacity is above the available capacity, we hit a key decision point. If we constrain the capacity, we must tell the system what to do. Let's consider our options.
Capacity search is more complex than most people think. It is at least two-dimensional across time and resources. When capacity is constrained, you have a few options: manufacture it early, manufacture it late, jump to an alternate resource, or even increase your capacity (by putting extra resources). This search can get even more complex when you have multiple alternate resources. What happens if your primary alternate is available a little later than your secondary alternate which is available on time. Let's take this one step further. In a constrained capacity situation, you may have several production orders to move across time or resources. Which ones should you pick to move and which ones you would chose to keep?
I have tried multiple times modeling these complex decision trees for large companies with multiple options. The planning engines can give you an answer but it would be very hard to explain why. In most cases, the business users override the planning suggestions anyhow. I humbly realized that t is very hard to replace human intuition and know-how with a constrained engine. Production people can find very creative ways of making the product on time rather than delaying the order.
I believe it is more important to provide visibility to the business user and let them decide what to do rather than providing an answer that neither you can explain nor they don't trust. You should focus on showing the capacity load against the available capacity. You should empower the user to make good choices when they move the production across time and resources. This would go a much further in making a better production decision.
If you are interested in learning more, please connect with me on LinkedIn, follow me on Twitter, or watch me on YouTube.
My name is Cem and this has been another gem.
