In-House Calculation Engine for Supply Chain Planning

In-House Calculation Engine for Supply Chain Planning

Creating a calculation engine to plan for the unique needs of the semiconductor supply chain often requires factoring for both static and dynamic components. While standard, off-the-shelf, planning tools can save internal resources in developing a calculation engine, it is the dynamic components in many cases which preclude the use of them in favor of a custom in-house engine. Here’s a look at best practices and when to invest in an in-house engine.

As the complexity of supply chain planning increases, standard planning tools face challenges in meeting all its dynamic requirements. It is often in these instances where it is best to use an in-house engine. These dynamic requirements are especially pronounced in industries where business models and products are rapidly evolving:

  • In the semiconductor environment, binning is a general concept to differentiate the grade of a semi-finished product. The multiple-to-multiple relationship between a semi-finished product and final customer order is another challenge that creates flexible variables which traditional planning tools are unable to meet.
  • In the manufacturing process, raising the number of required machines dynamically scales the demand for those machines’ required materials. In this scenario, the unique way of combining different resources to meet the changing manufacturing requirement is rarely supported by a standard planning tool.
  • For the LED industry where economies of scale rapidly change, standard tools are unable to evolve with shifting market forces. For example, the average LED selling price reduction year on year requires better and better inventory control and optimized planning, which raises the bar for planning quality. Balancing this with planning solutions for new products and new flows becomes imperative, and thus requires a custom in-house engine.

At a semiconductor company working with several business units, each unit often requires different products from different industries to share the same manufacturing resources. However, the demand stability, product volume, and mix are quite different, which result in quite different planning strategies from the supply chain point of view. Segmented business unit planners are frequently in charge of a small group of products to enable them to focus on detailed planning activities such as material requirements planning, order confirmations or loading plans. Due to these factors, a centralized planning mechanism/process is essential to achieve global optimization since the resources are shared by different products crossing the business unit.

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