The analysis of the data structure used by the customer is performed in order to identify its best integration with SMART.R. We explore also different solutions to increase the efficiency of the data collection.
SMART.R is an integrated software solution designed to analyze and cope with complex processes, where reliability is crucial for the asset utilization. The software integrates the best mathematical-statistical tools for processing and analyzing data and it is specifically designed to support the product reliability estimation. Also, activities such as design parameters correlation, reliability benchmarking and statistical process control are efficiently performed by SMART.R which is specifically designed following customer needs.
SMART.R is developed using reliability and statistical models that are chosen based on the case study characteristics. The customization of the graphic interface, of the output type and format is made according to customer preferences and is tested through “pilot” applications
The development and the delivery of the final release to the client is supported by a know-how transfer, by coaching services and by training on the job. During this phase SMART.R can be redesigned or upgraded to perform new tasks or to integrate new tools.
• Ad hoc development
• Ability to work with big data samples
• User friendly
• Automation of repetitive operations
• Focused on client needs
Ferrari Gestione Sportiva
An advanced version of SMART.R is currently employed by Ferrari Gestione Sportiva, where a qualified operator is available for coaching and for technical support and to plan reliability analysis. In addition, the development team, continuously update and upgrade the mathematical models implemented into the software in order to provide the client a full support through the years.
In this case study the advantages of using SMART.R were clearly identified in:
• The ability to quickly manage large amount of data respecting the short product development time
• The explanation of the uncertainty and dispersion of the data coming from the field
• The understanding of the effects of different environmental conditions on the product life and performance.