Production planning for a ramp-up process in a multi-stage production system with worker learning and growth in demand

In a response to changes in customer requirements and environmental dynamics, product lifecycles have become shorter and shorter over the last decades. As a result, production ramp-ups have become more frequent in many industries, and they now often account for a significant share of the entire product lifecycle. Due to the prominent role production ramp-ups play in the lifecycle of a product, efficient production ramp-ups are now an important determinant of business success. This work proposes a mathematical model for managing production ramp-ups in a serial multi-stage production system. In the scenario considered here, both the productivity of workers and demand increase over time until a steady-state phase is reached at the end of the ramp-up. The model proposed in this paper supports the assignment of workers to the different stages of the production system and the balancing of production and demand to ensure a smooth transition from the production ramp-up to steady-state production. The model is analysed in numerical experiments to illustrate its potential for managing the production ramp-up. Our experiments show that high learning rates can have drawbacks in terms of large inventories if learning is not aligned with demand growth and across production stages.