IoT-based predictive maintenance

The next level of preventive maintenance

Maintenance of machinery and devices has always been a key process in manufacturing companies to increase the uptime, the performance and the lifetime of their production lines. As part of the company's green transition, maintenance can also be a significant contribution to extending the lifetime of machinery and equipment, thereby enhancing the utilisation of resources.

The first major change in the way companies approached maintenance was the transition from corrective to preventive maintenance policies. This changed the whole concept and execution of maintenance processes, going from firefighting to prevention. IoT is now enabling another fundamental transition bringing the widely spread time-based preventive maintenance policy to the next level.

Supported by the extensive use of sensors and connectivity, IoT makes it possible to have a timely and punctual understanding of the current operational state of a production line as well as of the conditions of its key components. Thereby, preventive maintenance can become condition-based, depending on real-time data about the state of a component instead of average life-time expectancies. When such data is combined with data about previously experienced errors – typically using statistical or machine learning models - the ability to forecast failures and transition to a predictive maintenance policy is at hand.

Nevertheless, more valuable maintenance policies come at a price, and not all equipment requires condition-based or predictive maintenance. Maintenance analysis methods such as the FMECA (Failure Mode and Effect Criticality Analysis) can assess the criticality of each failure based on its detectability, severity and occurrence, and thereby support the identification of optimal maintenance policies.

Maintenance Process Improvement (MPI) – the process to higher maintenance value

FORCE Technology is an internationally certified expert in materials and constructions. We combine this extensive domain knowledge with our expertise in IoT to a unique MPI approach to increase the value of preventive maintenance. Please find more information on materials and construction here.

Once a FMECA process has identified the candidates in the production line for condition-based or predictive maintenance, the critical equipment as well as their key failure indicators are defined in a cooperation between FORCE Technology experts and engineers operating on the production line. The equipment is IoT-enabled through the application of sensors measuring the identified key failure indicators and the establish-ment of a communication network for transmitting the data. The obtained IoT-based maintenance solution, now in a prototyping phase, goes through an iterative development process, where the solution is calibrated according to the monitored data to calibrate the maintenance parameters and design the optimal condition-based maintenance policy. Many insights may come up during this process which leads to changes in the approach.

When the prototyping phase is completed, the calibrated maintenance solution can be scaled – either using the designated IoT infrastructure or through a retrofit of the existing PLC/SCADA infrastructure.

A fundamental aspect of this solution development process is having a “non-invasive” prototyping process, in order to avoid any unexpected disruption in production. Furthermore, the application of sensors and the data collection processes are performed without violating any GMP/GLP compliance certification. Nevertheless, the implementation of a new solution for supporting maintenance – and thereby changing the previously certified process – will include a new certification.

Preventive maintenance goes beyond manufacturing

The adoption of a preventive maintenance strategy is not only limited to the manufacturing field. Several fields may take advantage from it, going from agriculture to services, to maintain either their products, assets and facilities or to ensure the quality of the services they provide to their customers. The analysis method (FMECA) and the MPI must be adjusted to the discipline in question but the basic IoT thinking and the core process remain the same. 

FORCE Technology can provide an IoT-based MPI process in any industry and/or business field.

If you want to learn more about predictive maintenance with IoT solutions, please contact us or read more about IoT solutions here