Adaptive Work Instructions from Real-Time Workspace Sensors
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Solution Overview
Problem
Existing systems for providing work instructions to employees are inefficient due to the use of static instructions linked to tags or QR codes, leading to redundancy and management inefficiencies, as they cannot adapt dynamically to changing environments.
Innovation Solution
A network service that dynamically determines instructions in real-time or near real-time based on sensor data from a plurality of sensors deployed in the workspace, utilizing machine learned models to analyze data and generate adaptive instructions tailored to the current environment and employee profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static instructions are provided through tags or QR codes, then employees can access work instructions, but the instructions cannot adapt dynamically to changing environments leading to redundancy and inefficiency
Solution Approach 1:
The patent transforms static work instructions into dynamic, real-time adaptive instructions by implementing a system that continuously receives sensor data from the workspace environment, processes this data through machine learning models, and generates updated work instructions accordingly. This allows instructions to adapt to changing conditions such as environmental parameters, employee location, and incident detection, eliminating redundancy and improving workflow efficiency.
2Productivity
If manual creation and distribution of work instructions is used, then instructions can be provided to employees, but the process is time-consuming and inefficient
Solution Approach 1:
The system implements automated self-service functionality where work instructions are automatically generated, updated, and distributed based on real-time sensor data and machine learning model predictions. The system autonomously manages the entire instruction lifecycle from creation to distribution without requiring manual intervention, significantly reducing time loss and improving delivery efficiency.
Solution Approach 2:
The patent incorporates continuous feedback loops where sensor data from the workspace is constantly monitored, analyzed, and used to update work instructions in real-time. This feedback mechanism ensures that instructions remain current and relevant, automatically adjusting to changing conditions without manual review, thereby eliminating time-consuming manual management processes.
3Ease of operation
If generic work instructions are provided to all employees, then instruction distribution is simplified, but the instructions do not account for individual employee experience or specific incidents
Solution Approach 1:
The patent applies local quality by customizing work instructions for each employee based on their specific characteristics such as experience level, role, and current location in the workspace. The system processes individual employee profiles and combines them with real-time sensor data to generate personalized instructions that account for employee-specific context, preventing information loss while maintaining operational simplicity through automated differentiation.
Data Source
AI summary
Aspects of the present disclosure relate to systems and methods for providing instructions (e.g., work instructions) to employees. Specifically, aspects of the present disclosure relate to a network service that dynamically determines instructions for each employee and provides the determined instructions to the employees while executing their duties. The network service can determine the instructions based on a set of inputs generated from each computing device and sensor data received from a plurality of sensors deployed at the workspace.