Periodic Reporting for period 1 - PreCoM (Predictive Cognitive Maintenance Decision Support System)

Summary
Cheaper and more powerful sensors, together with big data analytics, offer an unprecedented opportunity to track machine-tool performance and health condition. However, manufacturers only spend 15% of their total maintenance costs on predictive (vs reactive or preventative)...

Summary

Cheaper and more powerful sensors, together with big data analytics, offer an unprecedented opportunity to track machine-tool performance and health condition. However, manufacturers only spend 15% of their total maintenance costs on predictive (vs reactive or preventative) maintenance.
The PreCoM project will deploy and test a predictive cognitive maintenance decision-support system able to identify and localize damage, assess damage severity, predict damage evolution, assess remaining asset life, reduce the probability of false alarms, provide more accurate failure detection, issue notices to conduct preventive maintenance actions and ultimately increase in-service efficiency of machines. The focus of the PreCoM project is to develop and apply an innovative system for Predictive Cognitive Condition-Based Maintenance (CBM) as a new model for sustainable factories and Maintenance 4.0.
The PreCoM system includes 24 hardware, software modules and machine databases, which can be grouped in seven different sub-systems/algorithms: 1) a data gathering system for exploiting a multi-sensor platform and a data gathering box and cloud; 2) a data quality algorithm for securing the data quality through detecting and localizing unhealthy sensors; 3) a predictive algorithm for detecting and localizing damages, predicting damage development and recommending what to do in rotating and non-rotating significant components; 4) a scheduling algorithm for scheduling production and optimizing maintenance; 5) a follow up algorithm for assessing the impact of the PreCoM system during and after the demonstration period; 6) a self-healing system for preventing the accumulated stress; 7) an end user information system for optimizing maintainability and supporting maintenance staff as well as production and maintenance managers. A central PreCoM cloud enables the connection and data exchange between all modules and sub-systems.
The consortium includes 3 end-user factories, 3 machine-tool suppliers, 1 leading component supplier, 4 innovative SMEs, 3 research organizations and 3 academic institutions. Together, we will validate the PreCoM system in a broad spectrum of real-life industrial scenarios (low volume, high volume and continuous manufacturing). We will also demonstrate the direct impact of the platform on maintainability, availability, work safety and costs in order to document the results in detailed business cases for widespread industry dissemination and exploitation.

Work Performed

In the first half of the PreCoM project (months 1-18, 1 November 2017-30 April 2019), the consortium carried out a progressive definition of the PreCoM system concept and design. The work enabled the consortium to design concretely the PreCoM system, its functionalities, modules, hardware and communication, as well as the dedicated PreCoM cloud and database, the overarching ?PreCoM Brain? and the steering rules to secure right recommendations to the end user companies. Each module has been under development, improvement, accommodation and test by its respective partner owner, in strict collaboration with demonstration companies and their respective machine tool suppliers for what concerns industry needs and data availability. In addition to the modules, a 'PreCoM Brain' was developed as a set of rules that will run for avoiding contradictions and selecting the best recommendation from modules to be sent to the end-user company.
At this stage, the project is conducting all necessary steps to finalise the development, test and installation of the PreCoM system and all its (cloud, database, hardware and software) modules by October 2019, in order to enable the demonstration and evaluation of the PreCoM system in the three use case companies from November 2019 to August 2019.

Results

The PreCoM project is working to finalise a working prototype that goes beyond the state of the art of solutions for predictive maintenance (Maintenance 4.0) currently available in the market. We expect to produce an overall working and effective prototype of the PreCoM system, as well as a set of modules/sub-systems which can be exploited also individually (or in other combinations) by partners. We expect that the PreCoM system will impact positively on the levels of in-service availability, maintainability, quality and worker safety. The results from the planned demonstration will inform about the impact and feasibility of our innovations for entering the market and addressing real industry needs.
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Predictive Cognitive Maintenance Decision Support System
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