If a database kept track on the peak hours of use of the shared machine, an algorithm could determine time slots with highest and lowest demand and adjust prices per wash load in order to obtain maximum usage.
A machine that can be used my multiple tenants in a house could adapt its pricing mechanism to the washing behavior of the tenants. If 60% of the tenants can only wash their clothes in the evening due to working hours' contraints and 40% are flexible in their washing time allocation the pricing model could offer lower prices for washing during daytime or during the night.
Inversely, if in another house the tenants tend to wash in the morning, the algorithm could adjust to offer better rates in the afternoon, night or evening thereby acting as an incentive.
Tenants using a shared washmachine could "reserve" timeslots in advance for when they want to wash (for example in a mobile app) and free time slots could be discounted in order to motivate tenants.