E3

Efficient Equipment Engineering (E3). The project is within the area of Industry 4.0 closely related to the application and technical solutions proposed by Efficient Equipment Engineering E3.

The project is within the area of Industry 4.0 closely related to the application and technical solutions proposed by Efficient Equipment Engineering E3.

Due to the long lifetime of general machinery, pre-installation technical and economic assessments are necessary in order to obtain the return-on-investment (ROI) by end-users in a manageable timeframe. Life cycle cost (LCC) and RAMS (Reliability, Availability, Maintainability, and Safety) techniques are two acknowledged methods for assisting the optimization process. The combined use of RAMS and LCC analyses will describe the most relevant factors of the Economic and Technical performance in relation to the Operation & Maintenance options that would arise for the machinery systems for different controller situations. Machine Reliability, Availability, Maintainability and Safety are the most significant factors that are directly linked with operation and maintenance efficiency which leads to profitability.

In this context, Efficient Equipment Engineering (E3) seeks to introduce a qualitative jump in the quality, adaptability and robustness of control strategies that will operate the machine during its useful life, where production conditions and machine status cannot be considered as invariant. The project will introduce novel approach by combining the RAMS with CBM and health monitoring to assess the life cycle costing of the systems. The usage of present cost-efficient monitoring solutions will improve downtimes reduction, electric consumption minimization and waste reduction and operation and maintenance services improved, thanks to a lifecycle costing estimation on real-time and predictive analytics capabilities.

 

Project leader

The project in brief

Full name of the project:
Efficient Equipment Engineering 

Project duration:
2016-07-01 – 2018-06-30

Funded by:
The Knowledge Foundation
Volvo Cars Corporation
Autokaross I Floby AB
Eurofins

Researchers related to the current project

Amos Ng, Professor (University of Skövde)

Kanika Gandhi, Ph.D (University of Skövde)

Bernard Schmidt , Msc (University of Skövde)