Laundry Appliance Usage Balancing Through Dynamic Pricing Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Washing and drying appliances in locations like laundromats experience uneven utilization, leading to uneven wear and deterioration, requiring irregular maintenance and potential re-arrangement, which is cumbersome and costly.
Innovation Solution
A system and method for generating utilization signals from appliances, determining activity and demand statuses, and generating control signals to balance usage across multiple appliances and locations, using controllers and network communication to adjust operation schedules and pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If appliances are positioned at various locations, then accessibility and visibility are improved, but utilization becomes uneven across appliances
Solution Approach 1:
The system continuously monitors utilization rates of appliances at different locations and uses this feedback to dynamically adjust pricing signals. The controller receives utilization data from multiple appliances and locations, compares it against target utilization rates, and adjusts pricing accordingly to guide users toward under-utilized appliances, thereby balancing utilization distribution across the appliance fleet.
Solution Approach 2:
The system changes the pricing parameter dynamically based on utilization rates. When an appliance is under-utilized, the system lowers its pricing to attract more users; when over-utilized, it increases pricing to discourage use. This parameter adjustment mechanism effectively balances utilization distribution while maintaining accessibility at multiple locations.
2Reliability
If appliances are re-arranged to achieve even utilization, then utilization distribution is improved, but operational complexity and cost increase
Solution Approach 1:
The system replaces the mechanical approach of physically re-arranging appliances with an electronic/information-based approach. Instead of moving appliances to balance utilization, the system uses electronic pricing signals transmitted to user devices to guide users toward under-utilized appliances. This substitution eliminates the complexity and cost of physical re-arrangement while achieving the same utilization balancing objective.
3Device complexity
If appliances operate independently, then system simplicity is maintained, but utilization optimization across multiple locations is reduced
Solution Approach 1:
The system merges multiple independent appliances into a coordinated network managed by a central controller. The controller aggregates utilization data from appliances across multiple locations and coordinates pricing signals to optimize overall utilization. This merging maintains reasonable system complexity while significantly improving utilization optimization compared to independent operation.
Solution Approach 2:
The controller performs multiple functions: it monitors utilization rates, determines pricing signals, transmits pricing information to user devices, and receives feedback on user responses. This multi-functional approach allows the system to achieve utilization optimization across multiple locations without proportionally increasing complexity, as a single controller handles all coordination tasks.
Data Source
AI summary
An appliance, system, and method for operating laundry appliances are provided. The method includes generating a plurality of utilization signals including a utilization rate corresponding to a first plurality of appliances at a first location; determining an activity status based on the plurality of utilization signals of the first plurality of appliances at the first location; determining a demand status based on comparing the activity status to a quantity of user interface devices within range of a network; and generating a user control signal based on the demand status. The user control signal corresponds to a second plurality of appliances at a second location.