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Research projects

SAPPA - Service Architecture for Product and Production Availability

About this project

Project information

Project status



Magnus Löfstrand

Research subject

The aim of the SAPPA project is to develop, test and demonstrate an innovative cloud-based predictive and preventive maintenance system, improving availability of products and production systems, with a focus on heavy industry applications. The approach is to proactively detect deviations in behavior of products, compared to a simulation model continuously updated with real-time data captured from products in operation, using telematic services and cloud-based analytics. The concept enables the supplier to climb the value chain, compared to traditional hardware-only product offerings, taking greater responsibility for the customers’ productivity. This alters the business roles between suppliers and customers through risk and profit sharing schemes, promoting sustainability through economic incentives. A demonstrator prototype system will be developed for an availability-critical pilot application, consisting of a process industrial production system powered by hydraulic motors. As an additional benefit, the operational data collected from products in use creates a valuable information asset supporting knowledge driven product development, whereby next generation products are improved and the time to market for new products is reduced.

Concept and approach

The concept of the SAPPA project for availability monitoring of complex industrial products and production systems is based on five main components:

An embedded system platform for data capture from sensors connected to products in use,

A telematic service architecture, enabling remote access to captured data using wireless or wired network infrastructures,

A cloud-based analytics framework, providing scalable processing of data using Big Data principles, and a high-level API for access to information resources,

Availability modeling, simulation and validation mechanisms forming the basis for the deviation detection and predictive/preventive maintenance functions,

User interface components, for status monitoring, visualizations and alerts.