Crowdsourced Printer Stock Setting Prediction
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Solution Overview
Problem
Customers face inefficiencies and high costs in setting up printers due to the lack of a system for sharing optimal machine settings and setup routines across a fleet of printers, leading to delayed printer setups and outdated information.
Innovation Solution
A cloud-based stock management system that uses crowdsourced data from multiple printers to predict and recommend device settings and setup routines based on performance data and environmental conditions, allowing for the prediction of suitable stocks and printer settings across a fleet of devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If customers determine optimal machine settings for each stock by trial and error, then they can find suitable settings, but it delays the setting up of the printer and consumes considerable time
Solution Approach 1:
The system pre-determines optimal device settings for different stock types by analyzing performance data from multiple printers. When a customer loads stock, the system automatically retrieves pre-optimized settings based on the stock identifier, eliminating the need for trial-and-error setup at the customer site.
Solution Approach 2:
The system collects performance data from multiple printers using different settings for the same stock, analyzes this feedback to determine optimal settings, and continuously refines these settings based on aggregated results from the printer fleet.
2Ease of operation
If service technicians provide assistance for setting up printers, then customers can obtain help with device settings, but it increases service costs and technicians may not have up-to-date information
Solution Approach 1:
The system enables customers to automatically obtain optimized device settings without technician intervention. The printer communicates with the server, which automatically retrieves and applies appropriate settings based on the loaded stock, making the system self-configuring and eliminating the need for costly service visits.
Solution Approach 2:
A centralized server acts as an intermediary between customers and the optimal settings database. The server automatically processes stock information, retrieves pre-determined settings, and provides them to the printer, replacing the need for human technicians while ensuring up-to-date information is always available.
3Adaptability or versatility
If customers use a wide choice of suppliers and types of print media, then they have more options, but they cannot easily predict whether a new type of stock will work well on their printer
Solution Approach 1:
The system collects performance data from multiple printers using various stock types, analyzes this feedback to determine which settings work best for each stock, and uses this aggregated knowledge to predict and ensure optimal performance for any stock the customer chooses to use.
Solution Approach 2:
The system creates a universal database of optimized settings that can be applied across the entire printer fleet for any stock type. This universal knowledge base allows any customer with any printer model to achieve optimal performance with any stock, eliminating the need for customer-specific trial and error.
Data Source
AI summary
A system for predicting one or more stock-related device settings, includes memory which stores a crowdsourcing component. The crowdsourcing component acquires reports from multiple printers in a fleet of printers. The reports each include performance data and printer attributes used when printing one of a plurality of stocks, the printer attributes including at least one device setting. A learning component learns relationships between printer settings and performance, e.g., in the form of a prediction model, based on the acquired reports. A prediction component uses the learned relationships to predict device settings for the stock for at least one of the printers in the fleet of printers and a processor, in communication with the memory, which implements the components.