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Modeling and Implementing Digital Tw...

Konda, Vasudev,

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Modeling and Implementing Digital Twins and Deploying Digital Technologies for Optimization and Control of an End-to-End Supply Chain /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling and Implementing Digital Twins and Deploying Digital Technologies for Optimization and Control of an End-to-End Supply Chain // Vasudev Konda.
Author:	Konda, Vasudev,
Description:	1 electronic resource (158 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
Contained By:	Dissertations Abstracts International86-07B.
Subject:	Systems science. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31637765
ISBN:	9798302179500

Modeling and Implementing Digital Twins and Deploying Digital Technologies for Optimization and Control of an End-to-End Supply Chain /
Konda, Vasudev,

Modeling and Implementing Digital Twins and Deploying Digital Technologies for Optimization and Control of an End-to-End Supply Chain /Vasudev Konda. - 1 electronic resource (158 pages)

Source: Dissertations Abstracts International, Volume: 86-07, Section: B.

In today's competitive environment companies are going through high pressure to continuously improve their internal processes. Delivering the products on time is very important for any company. Customers are highly demanding faster delivery of products, pushing for reduce the price and decreased supply chain cost. To remain competitive, Organizations need to respond fast to changes in demand, maintain healthy margins to be able to invest in product development and secure its market position. This research objective is to analyze the end-to-end supply chain cycle time (order to delivery) at the current state, apply advanced data mining and process mining algorithms, and find new lead time parameters. And also, to compare lead time parameters before and after and see the possibility of optimization and reduce cycle time. In this exercise two components play a critical role, demand planning and order fulfillment.The demand planning involves, applying AI techniques on the historical data and evaluating demand variations, proposing alternative supplies, or test promotions to shape the demand that favors the bottom line. This type of analysis is new as organizations are beginning to trust AI techniques.Use of process mining to analyze the business process may be included in the customer order fulfillment life cycle (from order creation to delivery) to identify bottlenecks inthe process flow. If any issues are identified in the process, those can be corrected to streamline the process. The overall objective of this work is to create a Supply Chain Digital Twin, which is a digital representation of physical supply chain (mirror image). Digital Twin is a foundation for this analysis. Applying data mining and process mining techniques to optimize supply chain is certainly a pathway to Supply Chain Orchestration.

English

ISBN: 9798302179500Subjects--Topical Terms:

3168411
Systems science.
Subjects--Index Terms:

Demand variations

Modeling and Implementing Digital Twins and Deploying Digital Technologies for Optimization and Control of an End-to-End Supply Chain /
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520 $a In today's competitive environment companies are going through high pressure to continuously improve their internal processes. Delivering the products on time is very important for any company. Customers are highly demanding faster delivery of products, pushing for reduce the price and decreased supply chain cost. To remain competitive, Organizations need to respond fast to changes in demand, maintain healthy margins to be able to invest in product development and secure its market position. This research objective is to analyze the end-to-end supply chain cycle time (order to delivery) at the current state, apply advanced data mining and process mining algorithms, and find new lead time parameters. And also, to compare lead time parameters before and after and see the possibility of optimization and reduce cycle time. In this exercise two components play a critical role, demand planning and order fulfillment.The demand planning involves, applying AI techniques on the historical data and evaluating demand variations, proposing alternative supplies, or test promotions to shape the demand that favors the bottom line. This type of analysis is new as organizations are beginning to trust AI techniques.Use of process mining to analyze the business process may be included in the customer order fulfillment life cycle (from order creation to delivery) to identify bottlenecks inthe process flow. If any issues are identified in the process, those can be corrected to streamline the process. The overall objective of this work is to create a Supply Chain Digital Twin, which is a digital representation of physical supply chain (mirror image). Digital Twin is a foundation for this analysis. Applying data mining and process mining techniques to optimize supply chain is certainly a pathway to Supply Chain Orchestration.
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690 $a 0546
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