Multi-Tenant Manufacturing Cloud Customization With AI Scheduling
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Solution Overview
Problem
Existing cloud-based industrial solutions face challenges in easily customizing services to meet the specific needs of each industrial customer and have limitations in data integration and tool capabilities.
Innovation Solution
A multi-tenant Software-as-a-Service (SaaS) manufacturing platform that leverages generative artificial intelligence to collect, analyze, and customize industrial data, allowing for dynamic scheduling and production modifications based on business strategies optimized for similar manufacturing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If cloud-based industrial solutions are implemented to enable multi-tenant data collection and analytics, then data integration scope and analytical capabilities are improved, but the ability to easily customize services to specific customer needs deteriorates
Solution Approach 1:
The system segments the multi-tenant data collection and analytics service into customizable modules that can be independently configured for different customer entities. Each tenant receives a tailored instance of the service through configurable parameters and selectable analytics components, allowing customization without compromising the integrated multi-tenant architecture.
Solution Approach 2:
The cloud-based industrial solution implements dynamic configuration capabilities that allow service parameters, data collection scopes, and analytics methods to be adjusted in real-time based on specific customer needs. This dynamic adaptability enables the system to serve multiple tenants with customized services while maintaining a unified platform.
2Area of stationary object
If cloud-based industrial computing systems are used to coordinate operations across multiple facilities, then operational coordination scope is improved, but system complexity and difficulty of implementation increase
Solution Approach 1:
The system implements a universal multi-tenant platform that performs multiple functions including data collection, analytics, scheduling, and coordination across different facilities. This unified system reduces implementation complexity compared to deploying separate systems for each function, while maintaining broad operational coordination capabilities.
Solution Approach 2:
The cloud-based platform acts as an intermediary that coordinates operations between multiple facilities and supply chain entities. By centralizing coordination functions in the cloud, the system simplifies implementation at individual facilities while maintaining comprehensive cross-facility coordination.
3Measurement precision
If data is collected and analyzed from multiple industrial customer entities to determine business strategies, then analytical accuracy and optimization capability are improved, but data processing time and computational resources increase
Solution Approach 1:
The system applies partial action by selectively analyzing subsets of multi-tenant data that are most relevant to specific manufacturing processes and business questions. Rather than processing all available data uniformly, the system identifies and analyzes only the necessary subsets, maintaining analytical accuracy while reducing processing time and computational resources.
Solution Approach 2:
The system performs preliminary actions by pre-processing and organizing multi-tenant data into structured formats before detailed analytics are conducted. Data is预先 grouped by manufacturing process types and customer entities, enabling faster retrieval and analysis when business strategies are being determined, thus reducing overall processing time.
Data Source
AI summary
A multi-tenant, cloud-based Software-as-a-Service (SaaS) manufacturing cloud system offers a variety of industrial applications to end customers, including but not limited to MES, ERP, quality management, supply chain management, and customer relationship management (CRM). The system includes extensibility tools that allows industrial customers to customize databases, data collection templates, reporting fields, and other features of their consumed services, eliminating the need for these features to be customized by an administrator of the cloud system. Some embodiments of the manufacturing cloud system can also leverage generative artificial intelligence (AI) in connection with executing its supported services.