Against each one of the parameters (such as, Fuel Pump or Battery), one can maintain the corresponding time series data from the field, thereby reflecting the exact state of the physical asset at any point in time. Thus, the abstract model captures static as well as dynamic data (time series data) plus the actual location (GPS coordinates). Time series data (both current as well as historical) can be used for:
- Predictive maintenance: Developing statistical models can help predict failure of the asset and enable proactive maintenance preventive, predictive and prescriptive can be carried out, thereby saving time, money and productivity.
- Remote control: Location data can be used to enforce geo-fencing, leading to tracking and tracing of stolen vehicles. An excavator in the field may be allowed to operate only in a specified region and during specified business hours, on a business contract. If the contract is breached, alerts will be generated for the relevant stakeholders.
- Product design: When R&D engineers design a specific model of excavator, they use several reference performance curves to perform sizing of the various parameters like max engine-capacity, max RPM, max bucket-depth, etc. Digital Twin can help understand the performance of a new variant in an excavator before committing to expensive changes in the manufacturing process.
- Remote monitoring: With the help of Digital Twin, an operator can visually experience the operation of the excavator and immediately figure out if there's a problem and if yes, where it is. An expert, sitting in, say New York, can instruct the operator of the excavator from any corner of the world.
- Remote operation: It is a continuous process of tracking various parameters of the asset and comparing their values against the optimal operating values. The goal is not only to avoid outage but also to automate service assurance by automatically identifying performance issues and giving the insight needed to manage problems proactively.
- Virtual Reality (VR) based training on the Digital Twin: The field agent can be trained using virtual reality to fix various issues in step-by-step manner, dramatically reducing the cost of maintenance.
From a Digital Twin of an asset to a Digital Twin of a collection of assets
Imagine a factory with several machines, each performing a separate task. A Digital Twin can be created for every machine in the factory. Once created, one needs to capture the interaction between the Digital Twins – what information is exchanged between a pair of Digital Twins and how the states of twins change on receiving specific messages. This actually creates a sophisticated model with rich visualization of a system of state machines with complex interactions between various Digital Twins.
Wipro, by virtue of its Digital Twin Platform, is able to bring two distinct worlds of PLM and IoT together and create a unique value proposition in a seamless manner.