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When it comes to maintaining machines and systems, the top priority aim is to avoid breakdowns by means of a targeted and rapid technical service. Maintenance models applied in industry can be categorised according to their degree of maturity as either reactive, planned, status-based or predictive.
reactive maintenance is concerned, the service provider, e.g. the machine’s manufacturer, is informed about a machine breakdown. The provider will then send a service technician to resolve the problem. Since the technician must first diagnose the problem and, if necessary, acquire replacement parts, reactive maintenance can lead to long interruptions in operations.
In order to avoid this,
planned maintenance can be carried out. This involves regular inspections of the machine to be maintained by the service technician. This way, problems are identified early on and worn parts can be replaced where necessary even before an interruption occurs. This service model reduces downtime, but can also lead to unnecessary deployment of service technicians, since the intervals between maintenance should not be too long in order to avoid previously occurred interruptions.
Status-based maintenance is a service model that has only become possible thanks to the Internet of Things (IoT). All relevant machine data can be recalled via the internet at any time. This means that the current status of every system can be monitored and analysed. If the values are not good enough, then a service technician can be tasked fully automated with the maintenance directly.
predictive maintenance, the development of data over a period of time is analysed and correlations identified. This means machines can be compared with one another and enables the identification of condition constellations that, with a certain probability, have led to subsequent breakdowns. What’s more, observation of all machines in the overall context facilitates more efficient planning and coordination of service assignments. From a broader perspective, this leads to more targeted, more effective and more efficient service.
A fundamental challenge in the implementation of IoT-supported service processes is integration into the existing service management IT landscape. It is only through this integration that the potential of the new service models can be fully exploited. Key points here are the presentation of current machine information on the installed base, the communication between data analysis and management software (e.g. automatic set-up of service assignments), and the automated and precise allocation of staff and materials so that recognised faults can be rectified efficiently as well as the optimal support of the service technician with mobile applications.
Syskoplan Reply has many years of experience in the planning and implementation of service management projects. Over this time they have developed numerous solutions for big-name clients. As a partner in the “Industrial Services and Enterprise Systems” competence centre, Syskoplan Reply, runstogether with the University of St. Gallen, looks at processes, systems and technologies that will be relevant for the future of industrial maintenance. Syskoplan Reply is also a ramp-up partner of SAP HANA IoT Edition and has already worked with industry partners to successfully implement predictive maintenance solutions with SAP HANA and SAP CRM, as well as a mobile application based on SAPUI5 and SAP Fiori.
Syskoplan Reply is a leading IT services provider in the SAP environment and develops innovative, flexible and reliable IT solutions, particularly in the areas of Customer Relationship Management (CRM) and Business Intelligence (BI). We implement innovative IT solutions, using adaptable and agile IT platforms extended with customer specific components. This enables our customers to differentiate in the market and create sustainable competitive advantages. In addition, our customers benefit from our close partnership with SAP, strong industry knowledge and our partnership based collaboration.