About 75% of the total product cost is determined in the early design phase, which means that the possibilities to affect costs are relatively small when the design phase is completed. For companies, it is therefore vital to conduct reliable cost estimates in the early design phase, when selecting between different design choices. When conducting a cost estimate there are many uncertainties. The aim with this study is therefore to explore how uncertainties regarding product cost can be considered when estimating product cost and how expert’s knowledge can be integrated within cost estimation. A case study has been conducted within the aerospace industry at the company GKN Aerospace Sweden (GAS) in Trollhättan, from which a model to estimate product cost has been developed. The model is developed for space turbines, but can with modifications be used for other products. Space turbines are highly advanced products, produced in small batches with complex manufacturing processes and high costs. Because of the heavy capital investment, long lead times and high risks, cost estimates become very important, which made GAS suitable for the case study.

The new cost estimation model (NCEM) developed is a combination between intuitive, analogical and analytical cost estimation techniques. Product cost at GAS is built up by the following cost elements; raw material, purchased parts, material surcharge, manufacturing cost, manufacturing surcharge, outsourced operations, method support, delivery cost, warranty and scrap, which are studied more in depth. The material cost is estimated based on historical data and a list of previous purchased alloys is created. The manufacturing cost is determined more in detail where the cost for each operation is estimated, based on operation time, amount of removed material or welding speed. The method support cost is estimated based on a study of an internal prognosis where the amount of time from each discipline needed to support the product is determined. Included in the NCEM is also a risk assessment.

The main insights from this study is that transparency is vital when estimating product cost. It is important to state what assumptions that have been made. Breaking down the product cost into smaller units and create awareness about the cost drivers will identify risks and reduce uncertainness. Experts possess a great deal of knowledge about cost drivers and should be integrated when estimating product cost.