Periodic Reporting for period 2 - PROGRAMS (PROGnostics based Reliability Analysis for Maintenance Scheduling)
Période du rapport: 2019-04-01 au 2021-03-31
Considering the increasing manufacturing plant size and complexity, unassisted maintenance management is becoming a losing strategy.
PROGRAMS developed methods and technologies that gather and exploit available knowledge to maximize the overall plant availability and minimize the maintenance costs. The main solutions offered by PROGRAMS are:
1) an easy to install hardware system to collect process data and exploit them at machine level;
2) several alternative Remaining Useful Life (RUL) computation methods (including a model-based prognostics method and a data driven approach) for the smart evaluation of equipment conditions;
3) a support tool to speed up the FMECA deployment;
4) a tool for reliability parameters estimation of components based on maintenance reports;
5) a novel Decision Support System (DSS) tool for optimal maintenance strategy determination;
6) a tool for the optimal merge of maintenance and production schedules that integrates an opern interface with legacy ERPs;
7) a platform to share maintenance and machines related information between involved personnel.
The proposed solutions have been combined into a seamless suite of software solutions that demonstrated how an integrated approach to the maintenance management can actually lower the costs that a company must face.
PROGRAMS developed methods and technologies that gather and exploit available knowledge to maximize the overall plant availability and minimize the maintenance costs. The main solutions offered by PROGRAMS are:
1) an easy to install hardware system to collect process data and exploit them at machine level;
2) several alternative Remaining Useful Life (RUL) computation methods (including a model-based prognostics method and a data driven approach) for the smart evaluation of equipment conditions;
3) a support tool to speed up the FMECA deployment;
4) a tool for reliability parameters estimation of components based on maintenance reports;
5) a novel Decision Support System (DSS) tool for optimal maintenance strategy determination;
6) a tool for the optimal merge of maintenance and production schedules that integrates an opern interface with legacy ERPs;
7) a platform to share maintenance and machines related information between involved personnel.
The proposed solutions have been combined into a seamless suite of software solutions that demonstrated how an integrated approach to the maintenance management can actually lower the costs that a company must face.
The PROGRAMS project activities allowed to complete and validate several solutions which were identified as key enablers for the deployment of Predictive Maintenance (PdM), not only on new instrumented equipment, but also on legacy ones.
The consortium developed of a SW/HW tool named Equipment Control Module (ECM). At its core lies the Smart Box, an advanced Industrial PC capable retrieving all data available on the legacy pilot lines. In addition the Smart Box allows the local data analysis as well as the secure data forwarding to a cloud based database. The ECM can locally exploit the collected data by adapting the process parameters to the equipment degradation and by provisioning to the operator of all information required to monitor the process from remote.
The Behaviour Prediction Tool (BPT), offering physical models based RUL evaluation, was completed and deployed on the pilot lines. The consortium also completed the Quick RUL tool (to exploit design analysis formulas to provide RUL estimation for critical components of the end users equipment) and the Advanced System Invariant Analysis (that exploits the local sensors data and a data driven approach to evaluate the overall status of the whole production equipment or of selected subsystems).
In order to determine for each equipment component when it is profitable to deploy PdM, or if it is better to follow more "traditional" approaches, the PROGRAMS consortium completed the development of the Maintenance Decision Support System (MDSS) that optimizes not only the choice of cost-effective maintenance strategies, but also the best maintenance policies. The MDSS interacts with several other tools like the Life Data Assessment tool (that analyses maintenance reports to model the components probability of failure), the Reliability and Maintainability (R&M) simulation tool and the Life Cycle Cost computation tool. The platform integrating them was named MSO (Maintenance Schedule Optimization) tool.
The data collected and computed by the platform is exploited to ease the performance of the Failure Modes, Effects and Criticality Analysis (FMECA). The PROGRAMS FMECA tool not only exploits all data made available by the PROGRAMS platform to partially fill the Criticality Matrix, but also guides the operator though all the complex steps required to perform the Criticality analysis.
In order to schedule and integrate maintenance operations with the factory production plan, the consortium completed the Smart Scheduling Tool (SST) that accesses all the suggested times for maintenance, transforms them into actual maintenance activities and merge them with production operations. If a legacy ERP system is not available the SST includes the functionality to perform the modelling of the production activities.
The Maintenance Service Platform (MSP) allows all involved personnel to contribute in a constructive and continuous way to the sharing of all maintenance related information. The implemented functionalities exploit the popular social network paradigm to increase the penetration level of the tool.
Robust and customizable data analysis services, the PROGRAMS workflows, have been deployed to extract from raw sensors data formatted any meaningful features that can be thus easily used as input by the platform software modules.
All the developed solutions were customized to the end user pilot lines and iteratively tested and improved, until they provided a level of performance in line with (or in many cases better than) the requirements initially defined.
As a direct consequence of the project efforts, an average 65% lowering of the overall LCC by the deployment of optimal maintenance strategies and policies was demonstrated. The Throughput has been improved by 19%. The robustness of the equipment monitoring capabilities to estimate the critical components status has been evaluated in 84% using test benches for accelerated wear induction and simulated failures. The time to perform a full FMECA has been lowered by more than 40% on both pilot lines while the time required to solve problems on the field was cut by the 20%.
6 solutions (ASIA, QuickRUL, ECM, MSO, SST, MSP) are ready to reach the market within 1 year from the project end and business plans have been prepared for them. The remaining solutions developed by the project could reach the market in a later stage.
The consortium participated in more than 20 events despite the COVID19 pandemic, including scientific and industrial conferences, exhibitions, and fairs. Furthermore 12 scientific publications have been presented in prestigious conferences.
The consortium developed of a SW/HW tool named Equipment Control Module (ECM). At its core lies the Smart Box, an advanced Industrial PC capable retrieving all data available on the legacy pilot lines. In addition the Smart Box allows the local data analysis as well as the secure data forwarding to a cloud based database. The ECM can locally exploit the collected data by adapting the process parameters to the equipment degradation and by provisioning to the operator of all information required to monitor the process from remote.
The Behaviour Prediction Tool (BPT), offering physical models based RUL evaluation, was completed and deployed on the pilot lines. The consortium also completed the Quick RUL tool (to exploit design analysis formulas to provide RUL estimation for critical components of the end users equipment) and the Advanced System Invariant Analysis (that exploits the local sensors data and a data driven approach to evaluate the overall status of the whole production equipment or of selected subsystems).
In order to determine for each equipment component when it is profitable to deploy PdM, or if it is better to follow more "traditional" approaches, the PROGRAMS consortium completed the development of the Maintenance Decision Support System (MDSS) that optimizes not only the choice of cost-effective maintenance strategies, but also the best maintenance policies. The MDSS interacts with several other tools like the Life Data Assessment tool (that analyses maintenance reports to model the components probability of failure), the Reliability and Maintainability (R&M) simulation tool and the Life Cycle Cost computation tool. The platform integrating them was named MSO (Maintenance Schedule Optimization) tool.
The data collected and computed by the platform is exploited to ease the performance of the Failure Modes, Effects and Criticality Analysis (FMECA). The PROGRAMS FMECA tool not only exploits all data made available by the PROGRAMS platform to partially fill the Criticality Matrix, but also guides the operator though all the complex steps required to perform the Criticality analysis.
In order to schedule and integrate maintenance operations with the factory production plan, the consortium completed the Smart Scheduling Tool (SST) that accesses all the suggested times for maintenance, transforms them into actual maintenance activities and merge them with production operations. If a legacy ERP system is not available the SST includes the functionality to perform the modelling of the production activities.
The Maintenance Service Platform (MSP) allows all involved personnel to contribute in a constructive and continuous way to the sharing of all maintenance related information. The implemented functionalities exploit the popular social network paradigm to increase the penetration level of the tool.
Robust and customizable data analysis services, the PROGRAMS workflows, have been deployed to extract from raw sensors data formatted any meaningful features that can be thus easily used as input by the platform software modules.
All the developed solutions were customized to the end user pilot lines and iteratively tested and improved, until they provided a level of performance in line with (or in many cases better than) the requirements initially defined.
As a direct consequence of the project efforts, an average 65% lowering of the overall LCC by the deployment of optimal maintenance strategies and policies was demonstrated. The Throughput has been improved by 19%. The robustness of the equipment monitoring capabilities to estimate the critical components status has been evaluated in 84% using test benches for accelerated wear induction and simulated failures. The time to perform a full FMECA has been lowered by more than 40% on both pilot lines while the time required to solve problems on the field was cut by the 20%.
6 solutions (ASIA, QuickRUL, ECM, MSO, SST, MSP) are ready to reach the market within 1 year from the project end and business plans have been prepared for them. The remaining solutions developed by the project could reach the market in a later stage.
The consortium participated in more than 20 events despite the COVID19 pandemic, including scientific and industrial conferences, exhibitions, and fairs. Furthermore 12 scientific publications have been presented in prestigious conferences.
The main progress of PROGRAMS is the demonstration that an integrated maintenace approach can greatly reduce the maintenance related costs. Such an achievement will have a great importance for European small and medium enterprises because they usually cannot afford the cost of a full-fledged maintenance department taking care of all Predictive Maintenance (PdM) related aspects (like the models’ creation and tuning or the estimation of components degradation). The PROGRAMS suite will allow instead SMEs to manage such aspects with limited costs and training, thus extending the benefits of PdM to the bulk of European industries and, in turn, increasing their competitiveness on world markets.
The main benefits of the project outcomes were provided along the following lines:
• Increased Availability and Overall Equipment Effectiveness.
• Continuous monitoring of system components criticality.
• Exploitation 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 Life Cycle Cost (LCC).
• Provision of robust and customizable data analysis services.
• Deployment of an Intra Factory Information Service.
These benefits will impact especially on the European SME sector, where the need for flexibility, production efficiency, and strategies optimization, often meets resource limitation, localized knowledge gap, and lack of available tools.
The main benefits of the project outcomes were provided along the following lines:
• Increased Availability and Overall Equipment Effectiveness.
• Continuous monitoring of system components criticality.
• Exploitation 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 Life Cycle Cost (LCC).
• Provision of robust and customizable data analysis services.
• Deployment of an Intra Factory Information Service.
These benefits will impact especially on the European SME sector, where the need for flexibility, production efficiency, and strategies optimization, often meets resource limitation, localized knowledge gap, and lack of available tools.