Industrial Vehicle Task Scoring for Dynamic Performance Measurement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial vehicle performance assessment in dynamic environments is hindered by the inability to accurately measure and adjust for extrinsic factors, leading to inefficiencies in operations across different facilities and industries.
Innovation Solution
A computer-implemented process that evaluates industrial vehicle performance by receiving task metrics, extracting operational data, and computing task evaluation scores based on target scores, which are dynamically adjusted to account for extrinsic factors, enabling aggregation of performance data across various operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fixed performance metrics are used to assess industrial vehicle performance, then the assessment process is simple and consistent, but it fails to account for extrinsic factors and dynamic operating conditions, leading to inaccurate performance evaluation
Solution Approach 1:
The patent implements dynamic target scores that automatically adjust based on extrinsic factors such as facility characteristics, task complexity, and operating conditions. Instead of fixed performance thresholds, the system calculates adaptive target scores that reflect real-world variations, enabling accurate performance assessment across diverse environments while maintaining a structured evaluation framework
Solution Approach 2:
The system changes the performance assessment parameters by introducing multiple extrinsic factors (facility size, task type, vehicle age, operator experience) that modify the target scores. This allows the measurement system to adapt to different operating conditions without requiring complete redesign of the assessment approach for each scenario
2Measurement precision
If vehicle-specific performance measures are implemented to improve assessment accuracy, then performance evaluation becomes more precise, but comparison across different manufacturers and models becomes difficult
Solution Approach 1:
The patent creates a universal performance assessment framework that can evaluate different vehicle types (forklifts, pallet jacks, reach trucks) using the same extrinsic factor categories and scoring methodology. While target scores are adjusted for vehicle-specific characteristics, the underlying assessment structure remains consistent, enabling comparison across manufacturers and models through standardized performance indicators
3Measurement precision
If dynamic adjustment of target scores based on extrinsic factors is implemented, then performance assessment accuracy improves, but the complexity of data collection and processing increases
Solution Approach 1:
The patent segments the performance assessment into distinct extrinsic factor categories (facility characteristics, task parameters, vehicle attributes, operator factors). Each category is evaluated independently and contributes to the overall target score calculation, making the complex data processing manageable through structured modular assessment components
Data Source
AI summary
A computer-implemented process receives into memory, information designating a task to be performed on an industrial vehicle. The task has a metric associated therewith. The process also extracts vehicle operational data that is generated on the industrial vehicle in response to the industrial vehicle executing the task. The process further receives into memory, information identifying a set of target scores, each target score of the set of target scores defining a different measure of performance associated with the task. The process yet further computes a task evaluation score for each target score in the set of target scores based upon the corresponding measure of performance associated with the task, and creates an adjusted task evaluation indicative of industrial vehicle performance that takes into account an aggregation of the task evaluation score computed for each target score in the set of target scores.