In the wake of the global COVID-19 closure, companies that have lost money will be looking for new ways to create and save money. The introduction of Internet of Things (IoT) involving digital twins seems to be helpful in reducing costs. Companies have been using these innovative methods to improve their awareness and automatically tailor their business responses to changing circumstances.
IoT and Digital twins can be used in countless ways to reduce costs. Their use enhances awareness of situations, helping organizations make better business decisions. Organizations have used this technology to:
- Switch to standard care and conditional support in the railway industry.
- Use predictive care to anticipate disruptions to the major impact on the oil and gas industry.
- Monitor patients in real time to increase comfort and avoid life-threatening situations in health care.
Applicant leaders are increasingly using IoT and digital twins to improve awareness of situations and make better business decisions. These technologies can help reduce costs, from the railway, oil and gas industries, healthcare, and supply chain industries.
Companies may first use digital twins to save money by improving awareness of the situation. For example, digital twins can help companies detect mechanical failures before they can stop production, which allows repairs to be done early or at a lower cost. Companies can save more money when they develop their business response to such changing circumstances. For example, a company might automatically schedule repairs to multiple pieces of equipment in a way that minimizes impact on performance.
We have seen many examples of companies using digital twins to reduce costs in a few different types of operating conditions. The following usage scenarios are described in this white paper to help you understand how such emergencies are created using IoT and Digital twins:
Transportation Cost Optimization
Use Case – Rolling stock
It is well-known that digital twins are used in high value rolling goods, such as trains, to improve fuel efficiency and improve efficiency (i.e., with predictable repairs). However, cost savings have been observed in passenger vehicles (for example, improving security maintenance at passenger doors and train wheels).
The rail transport provider reported an average of 10% savings when moving from conventional care to state-based prevention in stock care.
Oil and Gas Cost Optimization
Due to their large portfolios of high value assets, companies in the oil and gas industry have been aggressive in taking digital twins.
Use Case – System Operations
It is a common practice for companies to use digital twins to model and analyse functions such as oil metals, pipelines, and processing facilities. Examples of business objectives supported by forecasting adjustments, machine learning and other analyses include an increase in automatic excavation or processing operations, reduction of off-peak hours (FTE), downtime, and prolong the life of high value assets.
The oil and gas company reported that, by means of a forecasting forecast for building repairs in historical data, they had detected near a large part of their offshore oil field. This gave them enough time to take the lead in maintaining security. This helped them to avoid a week of unplanned unemployment and loss of production costs. By itself, the move has yielded a return on their digital investment that has doubled in less than a year.
Healthcare Cost Optimization
We have not yet seen a strong acceptance of digital twins across the healthcare industry, but early adoption models are promising and set a good example for a variety of applications.
Use Case – Patient Monitoring
Digital-based analyses based on the patient’s real-time telemetry and patient medical records are used to monitor patients and generate “risk points” of near, potentially life-threatening, “blue code” (such as heart or respiratory failure). Although pressure ulcers (or “bed sores”) do not usually endanger life, they are a problem everywhere that contributes greatly to the patient’s comfort. This can be avoided using double-digit digital analysis of biometric sensor data in hospital beds and gurneys.
One health care provider reported that the use of digital twins to monitor a patient reduced the incidence of bed sores by 85% and reduced the caregiver’s use. One healthcare provider has used patient digital twins to reduce code blues by 60%.
Supply Chain Cost Optimization
Supply chains are a place where businesses increase their investment in IoT and telemetry. Utilizing new features such as digital twins within the supply chain can help companies achieve improved business results.
Use Case – Spoilage and Theft Mitigation
Monitoring the location and condition of high value assets (for example, vehicles and medicines) may help to identify deviations that indicate a high risk of theft. This technology can also be used to identify the location of assets for recovery purposes. Digital twins in many of these cases can be simple – just a place – but in some cases the supervised information may include natural factors such as temperature in the frozen container, generator fuel levels, or methods to detect depletion or disruption of assets.
Another automotive management company reported that the use of digital twins and analysis enabled them to negotiate a 25% discount on their insurance costs. The company that supplied blood and plasma was able to reduce its compliance rates by more than 90 percent in the cities where they had submitted the solution. The same enterprise also used the digital twin data of the pallets to renegotiate its insurance fee structure, as the risk model had changed now that they had real time data.
Kanoo Elite is best known for conducting extensive research on digital twin technologies, as well as a set of industry styles to transform applications across all industries. to bring Augmented Reality (AR) to asset management. Kanoo Elite is an important player to use the life cycle of engineering for digital twin systems, so that your teams can simplify product design and development. We have built a wealth of knowledge as a result of our participation in successful Digital Twin collaborative projects, and we have a natural continuity to help you develop a complete digital twin implementation to transform your offshore monitoring and maintenance assets.