Use Cases

SMART-PDM is certainly a use case rich project. There are 12 use cases listed below.

You can see the outcomes of the work on these use cases more closely via Demo Videos.

Use case Use case title Country
UC1 Hot rolling millTUR
UC2 Heavy commercial vehicleTUR
UC3 Wind power plantTUR
UC4 Seed drill FIN
UC5 Wood Chipper FIN
UC6 Hydro power plantFIN
UC7 Saw millsFIN
UC8 Milling machines ESP
UC9Grinding machinesESP
UC10Assembly machinesESP
UC11 Home appliancesPRT
UC12Smart flexible assembly lineROU

Use case 1: Hot rolling mill (TUR)

The first objective of this use case is to accurately predict the wearing on the rollers, and hence their remaining useful life. A step was taken to add different attributes, as well as the frequency of data recording, at least once per second. The pilot site belongs to Kocaer Hot Rolling.

Some of the added features have changed over time. Attributes that will make it meaningful to save time-based instead of look-up table have been made suitable by Kocaer.

Picture courtesy of Enforma. Do not reproduce without prior written consent.

Use case 2: Heavy commercial vehicle (TUR)


  • Predicting brake pad wearing in vehicles
  • Predicting engine oil system fault in vehicle
  • Predicting fuel system fault in vehicle

The objective of the firstly considered use case is to accurately predict the thickness of brake pads on busses, and hence their remaining useful life. In order to achieve this, vehicle data acquired & wirelessly transmitted from the ECU, and the measured thickness data in maintenance records are considered.  

Once this objective is accomplished, the goal is shift the the maintenance paradigm from one being “fixed-interval” to “variable interval”, where the service intervals are determined by SMART-PDM.

The owner of the pilot, Anadolu Isuzu, sends heavy vehicle data used for predictive maintenance application includes features such as speed, voltage, slope, braking condition, latitude and longitude of the vehicle in motion.

Use case 3: Wind power plant (TUR)

The objective of this use case is to create a decision support system based on input data from the wind turbines. The owner of the use case is Zorlu Enerji.

  • Data from SCADA will help predict failure.
  • Early predicted failures will boost the power plant’s performance curve and decrease O&M costs.

Use case 4: Seed drill (FIN)

The owner of this use case is Junkkari.

  • Scope of the project:​
    • Increases effectiveness in grain production
    • Fault detecting forehand​ and increase overall usability.
    • Current model is “run to failure”
    • Gather additional information about sowing and sowing conditions
  • Current failure model:
    • Only visual observation
    • “Run to failure” model
    • Failure means downtime, and sowing season is too short for that
  • Goal:
    • Sophisticated way to offer predictive maintenance
    • Next step in grain production

Use case 5: Wood chipper (FIN)

The owner of this use case is Junkkari.

  • Current model:
    • “Run to failure” and operator observes machine visually
    • It is hard to tell when blades are worn out and operating is not cost-effective anymore
  • Scope:
    • Enable predictive maintenance for woodchipper
    • Connect machine to the cloud services with cell phone
  • Goal:
    • Mobile app that shows operator information about machine condition:
      • Blade condition (acceleration sensors or strain gauge strip)
      • Hydraulic oil temperature
      • Air temperature
      • Bearing temperature
      • Overall information like working hours
      • No-stress feature occurrence frequency

Use case 6: Hydro power plant (FIN)

The owner of this use case is Caverion.

  • Critical infrastructure for electricity supply. Need low amount of failures and comprehensive planned maintenance.
  • Availability = Maximize duration of reserve capacity + Timing in demand peaks and during the spring floods.
  • Maintenance operations need to be optimized by dependability risk management and condition based maintenance operations.
  • Moving towards automated RAM analysis in key role!
  • RAM stands for Reliability, Availability, Maintainability

Use case 7: Saw mills (FIN)

The owner of this use case is Caverion.

  • Saw mills are notable part of the forest industry ecosystem.
  • Effective use of raw material joins timber, pulp and paper but nowadays also biofuels to same value chain.
  • Saw mills exploit local raw material and operates in global business. Timber market has notable cyclic variation in demand.
  • Saw mills are cost sensitive business including maintenance operations, use of energy and logistics.
  • Agile maintenance operations needed because process deviations are common, raw materials and bottlenecks in production line vary and number of equipment is high.
  • The requirements are entirely consistent with hydro power use case, i.e. requirement is that coverage of dependability analysis are comprehensive and up to date.

Use case 8: Grinding machines (ESP)

Use case centered on machine tools manufacturer DANOBAT.

A servitisation roadmap (methodological guide) has been used to develop Advanced Services for the Manufacturing sector, driven by DANOBAT as Machine Tool builder.

The goal of this use case is to transform the machine tool industry by converting it from a product-based business model to a product-service model using the Industrial Internet of Things, or IIoT and a advanced service platform.

Vertical grinding machine example

Use case 9: Milling machines (ESP)

Zayer builds tailor made milling machines and wants to provide a machine health status assessment to their customers as well as for themselves in order to plan maintenance actions.

  • Decrease maintenance costs by planning most of the actions as they have to send technicians all over the world.
  • Connect the machine to the platform and see basic KPIs measured.
Milling machine example

Use case 10: Assembly machines (ESP)

Mondragon assembly builds assembly machines for different sectors. These machines have several stages where different jobs are performed. In this case a gas flow controlling valve production machine is going to be considered.

  • The degradation of the electrode affects the quality of the weld
  • Due to malfunctioning of welds safety issues can arise
  • Electrode changes: 25 per day per welding machine per line
  • Prediction of electrode wear is vital for ensuring production quality and increasing productivity
Example of an assembly machine

Use case 11: Home appliances (PRT)

Owner of the use case Sonae/VPS. The objective of this use case is to develop a system that can detect and predict home appliance faults by analysing their power consumption patterns and, eventually, other parameters:

  • Develop a device (the smart connector) to collect energy consumption
  • Integrate a secure and reliable communication middleware
  • Develop UI for end-users and maintenance/after-sales professionals 
  • Develop algorithms capable of analysing consumption patterns
  • Develop reactive and predictive maintenance algorithms able to detect and/or predict faults in home appliances

Use case 12: Smart flexible assembly line (ROU)

Flexile Robotic Line Laboratory with sensors, motors, conveyors and robots

Our aim: build a Digital Twin model to support implementing a failure detection and propagation model, as well as preventive and predictive maintenance algorithms.