A product manufacturer like a semiconductor company has usually contracts with customers to supply them with a certain quantity of a product by some upfront-agreed lead time and some flexibility in the rolling horizon updated planning. Often, customers request to have a product delivered earlier than the standard time, and could be willing to pay a higher price to make that happen. This is a well-known Revenue Management (RM) situation in the service industry, which in other industries such as process industry is just coming up. This paper focuses on lead time based pricing in the context of RM in the semiconductor industry.
In general, based on the manufacturer’s information about the system load and inventory availability, lead time based pricing (LTBP) can help the manufacturer to balance capacity utilization rate while increasing the revenue by fulfilling customer orders earlier. This is specifically important for the semiconductor industry as it is characterized by long production lead times, high demand volatility and short delivery lead time requests. Earlier supply dates are valuable for customers due to the potential of lower inventory costs or for responding poor demand forecasts. Furthermore, their customers (the customer of the semiconductor industry e.g. Tier 1 in the automotive industry) tend to sign “Just in Time” agreements with their customers (e.g. OEMs in the automotive industry), leading to a penalization of Tier 1 for delivering products later than agreed and a non-legal but existing pressure on the semiconductor industry to deliver earlier than the contractually agreed lead time. As a result, the semiconductor industry current state is that the manufacturers provide flexibility beyond the contractual agreed date without any price adder.
In this work, we model the main production stage with typically long cycle times, the semi-finished good inventory as well as the final assembly processes with shorter but non-negligible cycle times. We divide customers in to two types: Price sensitive (PS) and lead time sensitive (LS), and apply the strategy that fits to their primary interests (MTO and ATO respectively). In such a system, we analyze the problem of order selection via price and lead time quotes. In this regard, we model and evaluate two decision-making strategies. The sequential decision-making approach considers lead time quotation, considering production capabilities, followed by price quotation of marketing under the given lead time quote. The second strategy makes these decisions jointly, in other words, the firm optimizes order lead time and price decisions at the same time.
