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Print Goes Digital and Predictive with the Internet of Things
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - API Integration & Management
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Connectivity Platforms
Applicable Industries
- Electronics
Applicable Functions
- Discrete Manufacturing
- Maintenance
Use Cases
- Predictive Maintenance
- Real-Time Location System (RTLS)
- Supply Chain Visibility
Services
- Software Design & Engineering Services
- System Integration
The Challenge
The company, a global leader in imaging technology solutions and managed print services, was facing increased competition and service level agreement (SLA) compliance issues. There was a push for IoT-enablement and new device location tracking requirements. The company was also dealing with inefficient field maintenance and rising costs, and lacked real-time visibility into partner supply chains. In the case of on-site printer fleet repair and maintenance, the old way simply couldn’t cut it. Reactive failure reporting, multiple technician visits and manual parts ordering dragged down profits and aggravated customers. With tens of thousands of printers moved per week, and third-party supply chains to contend with, manual repair and maintenance led to SLA violations, billing headaches and logistical nightmares.
About The Customer
The customer is a manufacturer recognized as a global leader in imaging technology solutions and managed print services. The company has thousands of employees who are responsible for billions in revenue from sales in almost every country in the world. The company has led the imaging solutions industry since its founding, but by the mid-2010s, it was facing increasing competition, mounting inefficiencies from manual processes, and the commoditization of previously lucrative contracts. The company's industry-leading innovation and expertise have earned it a world-class customer loyalty rate that most companies only dream of.
The Solution
The company partnered with Software AG to develop the location-based Operational Intelligence Platform (OIP) that could track live device movements, provide visibility into service and component supply-chain processes, and scale for continuous and batch data from millions of devices and their reference data input. The flexibility of webMethods BPMS enabled real-time, automated interaction with service partners. And the combined streaming and predictive analytics of Apama monitored sensor data to determine equipment condition, analyze and act on high-volume IoT streams, and ultimately leverage advanced predictive modeling to anticipate failures. The team’s OIP for streaming analytics was put in place, creating actionable intelligence on more than 1 million device status updates and real-time sensor data alerts per day. Working together, Software AG and partner Wipro implemented the solution in less than three months.
Operational Impact
Quantitative Benefit
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