Cloud Risk Assessment System for Industrial Enterprises
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Solution Overview
Problem
Conventional risk assessment techniques for industrial systems are laborious and fail to consider hidden or non-obvious interdependencies, leading to missed opportunities for mitigating risks in large, distributed industrial enterprises with complex supply chains and automation processes.
Innovation Solution
A cloud-based risk assessment system that collects and analyzes big data from industrial devices, assets, and supply chain entities to identify potential risks, generate reports, and provide real-time alerts, using techniques such as big data analysis, device and configuration-specific risk factor identification, and equipment compatibility matrices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional risk assessment techniques are used, then labor requirements are reduced, but risk identification completeness deteriorates due to inability to detect hidden interdependencies
Solution Approach 1:
The patent replaces manual, mechanical risk assessment processes with automated computational systems that use algorithms to analyze interdependencies among industrial assets. This substitution enables comprehensive analysis of hidden relationships that would be impractical to detect through conventional manual evaluation, thereby improving reliability without proportionally increasing time investment.
Solution Approach 2:
The patent introduces an intermediary computational layer that processes data from multiple industrial assets and identifies hidden interdependencies. This intermediary system acts as a mediator between raw asset data and risk assessment outcomes, enabling the detection of non-obvious relationships that connect otherwise unrelated assets across the industrial enterprise.
2Measurement precision
If comprehensive data collection from all industrial assets is performed, then risk identification accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex task of enterprise-wide risk assessment into manageable components by analyzing interdependencies among individual assets and asset groups. This segmentation allows the system to process comprehensive data from multiple sources while breaking down the overall complexity into discrete analytical units that can be evaluated systematically.
Solution Approach 2:
The patent implements a universal analytical framework that can process diverse data types from various industrial assets using common methodologies. This multi-functional approach enables the system to handle different asset categories and data formats through unified analysis processes, reducing overall system complexity despite the comprehensive scope of data collection.
Data Source
AI summary
A cloud-based risk assessment service collects industrial data from multiple relevant and connected sources for storage and analysis on a cloud platform. The service analyzes gathered data from internal and external sources and customers across different industries to identify operational trends as a function of industry type, application type, equipment in use, device configurations, and other such variables. Based on the analysis, the risk assessment service identifies risk factors inherent in a customer's particular industrial enterprise. The cloud-based system generates a risk profile for the customer that identifies the determined risks and recommends risk aversion strategies based on the customer's specific profile, compared to industry standards, product information, internal business expectations, external regulatory bodies, and/or past performance. Risk profiles are tailored for both plant-level users and business-level users to provide intelligent strategies to improve performance and prevent avoidable losses.