Equipment-as-a-service: a model that will revolutionize Polish industry?

  • designing better hardware — Connecting the supplied hardware to IoT platforms ensures that data sets from different production cycles are collected, analyzed and sent to R&D departments for further analysis and use. Feedback from machines allows for improvements in functions, performance and operations.
  • Develop a predictive maintenance strategy — one of the expected benefits of intelligent manufacturing is predictive maintenance. In this case, historical data collected from past applications and equipment failures serves as the information needed to develop a predictive maintenance strategy for the equipment being designed.
  • Revenue Growth — EaaS creates a new revenue hedge for manufacturers interested in leasing equipment. The EaaS model may also include subscription plans dedicated to small and medium-sized manufacturing companies that match their financial capabilities. In the case of manufacturers, on the other hand, equipment that is no longer in use may be leased out to third parties needing such services at the end of the production cycle.
  • reducing financial outlays — the purchase of production equipment is a capital-intensive expenditure that many manufacturers struggle with. Traditionally, SMEs have dealt with these higher costs by outsourcing certain components to contract manufacturers, which, however, leaves them with no control over the manufacturing process. EaaS gives the opportunity to return CAPEX to OPEX while ensuring that SMEs remain responsible for the production process and the quality of the products produced.
  • more efficient use of data — the EaaS model is also associated with providing manufacturers with data on equipment and production patterns, which aims to optimize the use of machines and their efficiency.
  • lower operating costs — under EaaS, the service provider is responsible for maintaining production equipment and updating software, firmware or hardware. This lowers manufacturers’ operating expenses and helps SMEs to concentrate on their primary production responsibilities.




Data intelligence for Industry 4.0

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Data intelligence for Industry 4.0

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