Automatic Door Inquiry Routing With Adaptive Countermeasure Learning
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Solution Overview
Problem
Conventional automatic door systems face challenges in efficiently processing inquiries and addressing defects due to lack of knowledge about the system among customers and the difficulty in deploying operators with specialized knowledge, leading to unnecessary maintenance visits and increased costs.
Innovation Solution
An inquiry processing device and method that records past inquiry information, operation situations, and quality data, uses an extraction algorithm to present recommended countermeasures, receives feedback, and updates the algorithm to improve future inquiries, allowing for efficient troubleshooting and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators with specialized knowledge are deployed at the call center to respond to inquiries, then the quality of inquiry processing improves, but the cost increases
Solution Approach 1:
The patent creates a virtual copy of expert knowledge through the knowledge database and extraction algorithm. Instead of deploying actual experts, the system captures their knowledge in structured formats and uses algorithms to retrieve relevant information, providing expert-level support without the associated costs.
Solution Approach 2:
The knowledge database acts as an intermediary between the operator and the expert knowledge. The extraction algorithm serves as a mediator that translates customer inquiries into relevant knowledge base queries and retrieves appropriate responses, eliminating the need for operators to possess specialized knowledge directly.
2Measurement precision
If workers are dispatched to the site to confirm defect situations, then accurate defect assessment is achieved, but time and cost increase
Solution Approach 1:
The system enables customers to perform self-diagnosis and self-troubleshooting by providing them with relevant knowledge through the inquiry processing system. The extraction algorithm guides customers through appropriate diagnostic steps and potential solutions, eliminating the need for worker dispatch in many cases.
Solution Approach 2:
The knowledge database is prepared in advance with comprehensive defect information, diagnostic procedures, and troubleshooting steps. When an inquiry is received, the system quickly retrieves pre-prepared knowledge rather than requiring on-site assessment, enabling rapid response without losing accuracy.
3Quantity of substance
If a knowledge database is used to support operators, then operational cost is reduced, but the ability to handle complex automatic door-specific inquiries is insufficient
Solution Approach 1:
The system transforms the static knowledge database into a dynamic response system through the extraction algorithm. The algorithm adapts to different inquiry types by automatically extracting relevant parameters, searching appropriate knowledge sections, and generating context-specific responses, enabling the system to handle diverse automatic door inquiries effectively.
Solution Approach 2:
The extraction algorithm changes the parameters of inquiry processing by automatically identifying key parameters from customer inputs, matching them with corresponding parameters in the knowledge database, and retrieving relevant information. This parameter-based approach enables versatile handling of complex technical inquiries without requiring expensive specialized operators.
Data Source
AI summary
An inquiry processing device includes: an automatic door information recorder that records information including past inquiry information from a customer regarding an automatic door, an operation situation, and quality information; a countermeasure presenter that presents recommended countermeasure information corresponding to a new inquiry regarding the automatic door by an extraction algorithm; a feedback information receiver that receives feedback information on whether or not a defect of the automatic door has been removed by taking measures on the basis of the recommended countermeasure information; a learner that updates the extraction algorithm of the countermeasure presenter on the basis of the feedback information; and a countermeasure presentation determiner that causes the countermeasure presenter to present new recommended countermeasure information by the extraction algorithm updated by the learner, when it is determined that the defect of the automatic door has not been removed.