PROGRAMS | PROGnostics based Reliability Analysis for Maintenance Scheduling

Considering the increasing manufacturing plant size and complexity, unassisted maintenance management is becoming a losing strategy. Intense and global competition forces industries toward the maximal exploitation of their available resources, including equipment. However, the almost uninterrupted use of machine and robots degrades their performances and leads to an increased insurgence of breakages and failures. In turn this leads to higher costs due both to machine unavailability and expensive repair interventions.

The best solution to this problem would be to know at every given moment the real deterioration status of each piece of equipment. This knowledge would allow to select and schedule the best moment for maintenance, right before a component breaks or leads to unacceptable performance for the system/production chain of which it is part of.

Reliable information about the real component remaining lifetime can only be achieved by combining different techniques (trend analysis, components modelling, simulation, …) while the determination of the best maintenance schedule must rely on the correct assessment of the impact that each component has on the whole system as well as the compatibility with company’s production deadlines.

The PROGRAMS main objective is thus the optimal management of a factory maintenance activities, through the maximization of  operating life of production systems and the minimization of maintenance related LCC costs. In order to achieve these results, the proposed approach relies on a Smart Objects Technology (named Smart Control System) deployed at factory level and on the concept of cloud-enabled Central Application Layer, able to improve overall business effectiveness with respect to the following perspectives:

• Increasing Availability (A) and then Overall Equipment Effectiveness (OEE) through increasing of MTBF.
• Continuously monitoring the criticality of system components by performing/updating the FMECA analysis.
• Providing alternative methods to estimate the condition and the Remaining Useful Life (RUL) of equipment components. (including physical-based models of the critical components and a data driven approach)
• Determining an optimal strategies and policies for the maintenance activities of each equipment component.
• Integrating the maintenance and production activities into a single schedule that optimizes the overall performances.
• Providing robust and customizable data analysis services.
• Allowing the company staff to actively participate to the maintenance management by an intra factory information service.

The PROGRAMS project aims at reaching its intended objective by developing the following novel technologies:

1. An easy to install hardware system to collect process data and exploit them at machine level (WP2).
2. Several alternative RUL computation methods (including a model-based prognostics method and a data driven approach) for the smart evaluation of equipment conditions (WP2-WP3)
3. A support tool to speed up the FMECA deployment (WP4)
4. A tool for reliability parameters estimation of components based on maintenance reports (WP4)
5. A novel DSS tool for optimal maintenance strategy determination (WP4).
6. A tool for merging maintenance and production schedules with integrated ERP support (WP4)
7. A platform to share maintenance and machines related information between involved personnel (WP5).

The proposed approach will have an important impact especially on the SME sector, where the need for flexibility, production efficiency, and strategies optimization analysis, often meets resource limitation, localized knowledge gap, and lack of available tools.

The main benefits of the project outcomes are expected along the following lines:

• Increased Availability and Overall Equipment Effectiveness

• Continuous monitoring of system components criticality

• Creation of physical-based models of the components which have a higher criticality level

• Selection of optimal strategies for the maintenance activities

• Integration of maintenance and production activities minimizing overall LCC

• Provision of robust and customizable data analysis services

• Development of an Intra Factory Information Service

The overall concept behind this project is based on 3 key layers:

1. Physical Layer: predictive maintenance techniques relied on data monitoring

2. Cloud Layer: allowing affordable time and space for elaboration techniques

3. ICT Layer: ICT infrastructure and protocols which are the backbone for the other two layers