The Impact of Learning on the Selection of Cost-Effective Machining and Production Process

Informed production decision-making requires a structured understanding of the production process and costs associated. This research proposes a decision support system incorporating the learning effects on selecting cost-effective machining production process. The approach is applied to the case on manufacturing wind turbine blades. The machining industry has experienced a surge in demand for complex machining applications and an availability of a wide range of new machining technologies. Producing complex structures requires experienced CNC programmers that perform extensive strategy planning, design and optimization. The system developed considers the production processes, cost items, power learning curve and experience of the programmers. This enables managers to evaluate between various production processes and select the most cost-efficient process. An analytical approach to evaluate cost efficiency between 3-axis CNC and 5-axis CNC machines. The result is a user-friendly planning and selection tool aiding in answering critical managerial questions related to cost-effectiveness.