Effective management of the supply chain processes has made it imperative for businesses to implement “Digital Twin Technology” to detect threats, suggest corrective actions, and simulate supply chain possible outcomes. A digital twin refers to a computerized version of a physical asset or process. It contains sensors that collect data to feed the physical asset. The notion of a digital twin begins with the conversion of manual business processes into an automated form. The resulting digital copy then simulates physical entity through the use of next-gen technologies like the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), sensors, data analytics, and augmented reality. Let’s explore the impact of the digital twin in supply chain.
According to Gartner’s IoT implementation survey on Feb 20, 2019, 13% of organizations are already using digital twin for implementing IoT in their projects, whereas, 62% are in the process of establishing one. Gartner predicted that investment in this technology is expected to reach $15.66bn by 2023.
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Impact of Digital Twin in Supply Chain
A digital twin in supply chain enables businesses to create a mirror of internal and external business processes. Organizations use business-related information to create a continuous loop that enables decision-makers to fine-tune their supply chain network.
The digital twin uses cognitive analytics to detect patterns and identify variability from the plan of actual demand. Digital twin analyzes the rise and fall levels of demand, arranges alternative supplies and test promotions to shape demand in the most profitable manner.
A supply chain digital chain can be used for:
* Forecasting and testing operations
* Monitoring risk and testing contingencies
* Inventory optimization
* Transportation planning
* Testing supply chain design changes and development
On the supply side, the digital twin predicts and prescribe planning remedies like freeing up capacity or booking additional external capacity. For instance, in the aviation industry when a particular aircraft type is growing in popularity due to high operating efficiency, the planning twin can emulate rising demand by identifying customer choices, routes, and regions. It then simulates the best initiative to ensure faster deliveries.
On the fulfillment side, businesses are piloting driverless trucks that are outfitted with Radio Frequency Identification (RFID), operational sensors, electronic parts catalogs, and barcodes. Logistics partners can use digital twin technology to apply predictive maintenance techniques for better fleet management, minimized supply disruptions, and timely deliveries.
Underlying Technology Trends Enabling Digital Twin in Supply Chain
Internet of Things (IoT)
The rapid growth of IoT is a critical factor driving the adoption of digital twins. Businesses often underestimate the volume of data generated by IoT platforms. They use different tools to manage and analyze the gathered data. A digital twin is an ideal way to access, structure and analyze complex product-related data. With data analytics and additional software, digital twins can optimize an IoT deployment for maximum efficiency. Accurate data enables businesses to predict future performance and possible failure.
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