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

The digital transformation has led not only to changes in industrial production, but also in the approach to business. What role does the Equipment-as-a-Service model play in this process?

Twenty years ago, companies that were the first to use digital technology to optimize business operations had to establish physical data centers, develop specialized applications, and hire professionals to keep the entire architecture working properly. It generated huge costs, so only large enterprises could afford it.

With the emergence and development of technologies such as cloud computing, open-source or the Software-as-a-Service (SaaS) model, the landscape of digital transformation has also irreversibly changed. Currently, enterprises can spend several thousand dollars on creating a digital process for servicing business operations and leave the responsibility for maintaining used solutions in the hands of suppliers. This change is Equipment-as-a-Service (EaaS).

What is EaaS?

Equipment-as-a-Service is a business model that consists of renting equipment to end users and in return charging periodic fees for its use.

This service-based subscription model, also known as Machine-as-a-Service, offers a number of benefits to both EaaS suppliers (OEMs and machine builders) and customers (manufacturing sites).

MaaS is a machine (or piece of equipment) provided by the supplier with guaranteed performance, which ultimately helps to keep driving and improving your business. It does not require an investment to purchase and is additionally maintained by the supplier. In this way, you move away from buying equipment as one-off payments, and instead finance its purchase partly based on the productivity of the machine. In this model, companies generally focus on “subscriptions”.

With IIoT connectivity, machine-as-a-service fulfills the traditional capabilities of a factory machine while contributing to other business goals.

Why is it worth it?

The beginnings of industrial data collection were limited to obtaining input data and using it to determine product quality, schedule and perform financial calculations. While this provided manufacturers with an opportunity to summarize profits from production cycles, the collected data did not provide insight into the condition of the machines, nor did it provide information on how to improve their design or operational capability. This meant that both OEMs (Original Equipment Manufacturers) and end users were unable to predict the actual performance of the equipment.

With the development of Industry 4.0, new ways of assessing the viability of machines and entire operations began to appear, driven by IIoT, IoT, cloud computing and edge computing platforms. These interconnected technologies ensure connectivity with production halls.

In the context of changes taking place, EaaS can be defined as a change in the way manufacturers design equipment with smart manufacturing in mind, focusing the responsibility and responsibility on delivering equipment as a service, not a product.

Thus, two types of service models can be distinguished. The first one includes OEMs that provide hardware to enterprises in a subscription model. In this variant, the devices are located in the subscribing party’s objects. The manufacturer leases the machine for a specified period of time, and the subscription fee covers maintenance and repair tasks, while the OEM is also responsible for software updates and replacement of spare parts. As reimbursement, the OEM owns the device data and may use it for research and development, predictive maintenance, or any other purpose for which it decides to use it.

The second model is to outsource factory equipment to customers for a specific period of time. This means that customers who do not have the equipment needed for specialized applications due to costs can partner with service providers and use their equipment at the equipment supplier’s facilities. In turn, the service provider receives subscription payments, machine data, and in some cases also a percentage of the final sales made.

Benefits for OEMs

Equipment manufacturers who become service providers thanks to this model can obtain a number of benefits, related not only to the new way of generating revenues, but also to the fact that they become eyewitnesses of the development of an intelligent factory. They include, among others

  • 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.

Benefits for production plants

The end user of each EaaS model is the manufacturer or the party that uses the device for production related activities. In this case, the end-user EaaS benefits include:

  • 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.

Would you like to learn more about how the EaaS model can help in the digital transformation of your enterprise and change the business model? Contact Rafał Pieczyński or Szymon Arciszewski.

Data intelligence for Industry 4.0