Maintenance Improvement through Data Analysis (MIDA) is a feasibility study developed by Net Surfing in collaboration with Mooble , acompany located in Turin and aims to identify and implement solutionsfor predictive maintenance, improving maintenance processes.
The study, just completed, faces a global process of predictive maintenance that is not limited to the analysis of the single-machine process. The intention is to give visibility to the whole logical processes, connected to machines even not physically contiguous and the activities of suppliers that contribute to the maintenance.
Where companies perform continuous processes, complexity increases because many parameters contribute to the production. The physical-chemical processes, in fact, take into account many variables so predictive maintenance must also take account of the different processes that the machine has performed and will perform both individually and in the context of the logical process.
With this vision, the questions that you want to answer are:
- How is running the process (physical and logical) compared to standard values?
- What impact will have a malfunction of the single process on the quality, times and costs?- What is the cost of less efficiency? Until it is acceptable before it occurs a malfunction? What are the machines that you can use in place and in that moment?
- What machines or mechanisms affect the proper functioning of the whole process (physical and logical)?
The system collects data from existing sensors and placed on different devices depeding on the problems of study, embedded or simulating and monitoring the operation, both individually correlated to other variables of a logical process.
Wishing to offer a pro-active service, the system will propose a series of algorithms useful to identify the parameterized phenomena.
midaThe collected data will not be passed as they come to the asset management asystem but will be processed using algorithms to be developed so that you can communicate aggregated data that will be associated to a counter.
The architecture provides f a web service to transmit the values of the counters that are necessary for preventive maintenance and inspections.
There is also a feature that allows you to reprocess data modeling to identify predictive maintenance to achieve. The architecture is designed to be able to communicate with additional subsystems of the CMMS customer.
activeganttThe proposed solution supports the analysis to detect the correct policies for planning and scheduling maintenance activities. The Planning describes WHAT and HOW. Scheduling describes WHO and WHEN. Below are the general objectives of the Planning and Scheduling provided:
• Be sure that workers and contractors are always working on the right things and they're doing it the right way.
• Reduce the waste of time between one work and the other; emergencies should be minimized effectively(10% or less of work orders) - the operational use of the of the prioritization is the key to everything.
The project therefore has the ambition to provide a reusable model that favors optimal management of a plant / system. The platform intends to operate as designed:
a M2M platform and a cloud computing solution for efficient processing of large amounts of data.
a system of integration between plant, measuring system and Infor EAM that can address the various points of attention, such as:
• Analysis of critical equipment
• Definition of appropriate technologies,
• Determination of the frequency of inspections, with improvement over the existing
• Development of the system for estimating costs / benefits and identifying indicators and reports useful for predictive maintenance
L’operazione in corso di realizzazione è stata selezionata nell’ambito del POR 2007-13 del Piemonte e viene realizzata con il concorso di risorse del Fondo Europeo di Sviluppo Regionale (FESR), dello Stato Italiano e della Regione Piemonte (Asse 1Innovazione e transizione produttiva Attività I.1.3 – Innovazione e PMI).