Multi-Tenant Manufacturing Cloud Customization Across Facilities
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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 utilizes generative artificial intelligence to customize databases, data collection templates, and reporting fields, and integrates a broader scope of data and tools, allowing for dynamic production and supply chain optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud-based industrial solutions are implemented to enable multi-tenant operations and data sharing, then global scalability and coordination capabilities are improved, but the ability to easily customize services to specific customer needs deteriorates
Solution Approach 1:
The system segments customization into modular components including configurable data collection templates, customizable reporting fields, and selectable analytics components. Each tenant can independently configure these segments without affecting other tenants, enabling both global scalability and individual customization through a multi-tenant architecture where the platform is divided into independent configurable units.
Solution Approach 2:
The system implements dynamic configurability where data collection templates, reporting fields, and analytics components can be modified in real-time based on tenant-specific requirements. The platform allows tenants to dynamically adjust their service configuration without requiring system-wide changes, maintaining both scalability and customization flexibility through runtime configurability.
2Adaptability or versatility
If cloud-based industrial computing systems are used to coordinate operations across multiple facilities, then operational coordination capability is improved, but data integration scope and tool capabilities are limited
Solution Approach 1:
The system implements a universal multi-tenant platform that consolidates multiple data integration and analytics tools into a single cloud-based system. The platform provides universal data collection capabilities across diverse industrial facilities, unified analytics processing, and centralized reporting functions, eliminating the need for separate complex integration systems at each facility while enhancing coordination capabilities.
Solution Approach 2:
The system merges data collection, analytics processing, and reporting functions into an integrated cloud-based platform. By combining previously distributed tools and data sources into a unified multi-tenant system, the platform expands data integration scope while simplifying the overall system architecture and reducing individual facility complexity.
3Reliability
If traditional industrial systems are used to maintain operational control, then system stability is improved, but the speed and accuracy of industrial applications deteriorate
Solution Approach 1:
The system introduces a cloud-based intermediary platform that sits between traditional stable industrial systems and modern high-speed applications. This intermediary multi-tenant platform provides stable data collection and processing foundations while enabling faster analytics and reporting capabilities, allowing legacy systems to maintain stability while gaining access to enhanced application performance through the cloud layer.
Solution Approach 2:
The system performs preliminary data collection, processing, and analytics preparation in the cloud before results are delivered to applications. By pre-processing data and preparing analytics in advance through the stable multi-tenant platform, the system enables faster application response times without compromising the stability of underlying industrial systems, as heavy processing occurs beforehand in the cloud.
Data Source
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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.