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Cost Optimization in Manufacturing with Digital twin

Bhagyashri Kambale | May 05, 2022 | 761 views
COST OPTIMIZATION IN MANUFACTURING
Digital twins appear to be beneficial in cutting expenses for many industries. A growing number of companies in the manufacturing industry, as well as healthcare, oil & gas, and other industries, are using digital twin features to better understand and respond to changing business conditions.

Digital twins can be used to save costs at numerous levels or segments of your business. Their use raises awareness of situations and helps businesses make better decisions. This technology has been applied to:

  • Change to standard care and conditional support in the railways
  • Use predictive care to foresee major impacts on the oil and gas industry
  • Monitor patients in real-time to improve comfort and avoid life-threatening scenarios

So, how do digital twin solutions assist manufacturers in cutting production costs?

Digital twins enable manufacturers to detect early mechanical defects, allowing for faster or cheaper repairs. Companies can save money by adapting to changing circumstances. For example, a corporation may automatically plan repairs to minimize performance impact.

Many companies use digital twins to cut expenses in various operating scenarios. In this article, we will look at situations to help recognize the benefits of digital twins.


Why Use a Digital twin?


Better R&D

The adoption of digital twins provides more effective product research and design. It also generates large amount of data about expected performance or results in the process. This data can provide insights that enable businesses to make necessary product refinements before initiating production.


Superior efficacy

The use of digital twins can be beneficial even after a new product has been put into production. This can help mirror and monitor production processes to achieve and maintain optimal efficiency throughout the whole manufacturing process.


Product end-of-life

As far as product lifecycle management is concerned, digital twins can assist manufacturers in determining what to do with products that have reached the end of their expected life and require final processing, whether through recycling or other means. They can figure out which product materials can be gathered with the help of digital twins.


Cost Optimization in Manufacturing using Digital twin


Transportation Cost Optimization

Digital twins are commonly employed in high-value rolling commodities like trains to improve fuel efficiency and competitiveness (i.e., predictable repairs). However, in the case of passenger automobiles, cost savings have been recorded (for example, improving security maintenance at passenger doors and train wheels).

When switching from conventional to state-based prevention in stock care, the rail transport operator claimed an average 10% savings.


Oil and Gas Cost Optimization

Companies frequently utilize digital twins to simulate and analyze functions like oil metals, pipelines, and processing plants. Among the business objectives supported by forecasting adjustments, machine learning, and other analyses are an increase in automated excavation or processing processes, a reduction in off-peak hours (FTE), and downtime, and the extension of the life of high-value assets.

The oil and gas businesses claimed that historical data forecasts for building repairs had been discovered near a substantial portion of their offshore oil production. This gave them time to lead security operations. They saved a week of unplanned unemployment and production expenditures. In less than a year, their digital investment has returned twice as much as before.


Supply Chain Cost Optimization

Businesses are increasing their investment in IoT and supply chain monitoring. Utilizing modern supply chain characteristics such as digital twins can assist businesses in achieving enhanced business results.

Monitoring the location and condition of high-value assets can assist in identifying anomalies that suggest an increased risk of theft. Additionally, this technology can be utilized to determine the location of assets for the purpose of recovery. While digital twins in many of these circumstances are straightforward – simply a location – in others, the supervised data may include natural characteristics such as the temperature inside the frozen container, generator fuel levels, or ways of detecting asset depletion or interruption.


Final Word

Is a digital twin necessary for your business? Yes, most certainly. By creating a comprehensive virtual picture of a company's processes, digital twins remove the element of uncertainty from decision-making. According to Gartner, 13% of organizations utilizing IoT already have digital twins in place, while 62% are either implementing or planning to do so. Hence, do not hesitate to deploy a digital twin in your organization, as it is worthwhile to invest in a digital twin that will help you lower overall production costs in the long run.


FAQ


Why is a digital twin necessary?

Digital twins are becoming vital in business. By making a digital copy of the physical assets of a product or service in an industry, digital twins help with data analysis and give people a way to check how things work before they happen. This way, they can develop a solution to any problem before it happens.


What data should be in the digital twin model?

The concept of the digital twin is based on three unique components: the physical product, the digital/virtual product, and the connections between the two.


How much does a digital twin cost?

According to some experts’ estimations, the cost of implementing a digital twin is $50,000 or less. Complex processes will necessitate a substantial investment and a lengthy implementation period to model.

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