Value-Based Feature Design for Smart Services in Computerized Numerical Control Machine Tools: A Case Study on Measuring Perceived Value Using a Choice-Based Conjoint Analysis

Artificial intelligence (AI) has emerged as a key technology, transforming the manufacturing industry by enabling new business models and reshaping existing ones through smart services. However, due to a lack of expertise in some companies, there are challenges in understanding how AI can be effectively integrated to create value and how products can be further developed into smart service products. Against this background, this paper contributes to the value-driven design of intelligent machine tools. In an exploratory research study, the self-explicated method was used with 23 industry experts to evaluate different service types and a variety of possible features. The results identify intelligent quality improvement as the smart service with the highest perceived value from the user's perspective. Based on these results, fictional service offerings were created and examined in a choice-based conjoint analysis with a sample of n = 245 industry professionals involved in procurement and retrofitting decisions for machine tools. The evaluation of feature selection is based on the analysis of willingness to pay, and additionally, the paper identifies optimal feature combinations for different target groups to maximize willingness to pay.