Supply Chain Digital Twin Platform

RUBICON Develops a Custom Digital Twin Supply Chain Management Platform for a Global Client

“The digital twin platform helps me overlook operations globally. It provides agility and I can quickly reply to questions related to material flow when necessary. It speeds up the whole improvement process and finding quality issues.”

(Global Supply Network Steering Manager)

Intro

Industry 4.0 is a technological framework, which focuses on digitalization and analytical capabilities in order to identify events on a real-time basis. A digital twin is a part of Industry 4.0 and it is a virtual replica of a physical asset, system, or process, which is becoming an important part of modern manufacturing. This virtual representation combines digital aspects of how the equipment is built and real-time aspects of how it is maintained and operated. The software aims to detect, predict, and optimize using real-time analytics to deliver value to businesses. Our Digital Twin Platform enables supply chain visualization in a graph form and helps our client to query, visualize, and analyze connected data.

Background

After successfully delivering a custom SCM data platform, RUBICON continued the partnership with the client and went on to deliver a Supply Chain Digital Twin Platform. The aim of this platform was to enable users to better understand and manage their supply chain data, by applying graph analytics and supply chain visualization of a graph. This platform enables users to query and analyze material and product flow in the supply chain. After rendering, the user can traverse through the graph, apply additional filters, and, for example, see where the material is used in the product line. The aim was to deliver a less costly and more efficient platform than the already existing off-the-shelf platform. Having thousands of different products and large datasets makes it hard to remember them all and spot when something is wrong. With the graph that allows for easy visualization of that data, we accelerated the improvement processes and found quality issues. Our product was successfully delivered in the designated timeframe.

The Client

The Chemical & Consumer is a global company that operates worldwide with its headquarters based in Western Europe. Positioned in several markets in the world, ranging from beauty care to laundry and home care, the company has been around for over 100 years.

The Project

The Problem

One of the main problems faced by our client was that the already-existing off-the-shelf platform for visualization of the supply chain material and products flow was costly. In addition, they encountered several performance and usability issues whilst rendering a large number of nodes in the graph.

The Solution

RUBICON’s solution to the client’s problem entailed a custom-made Supply Chain Digital Twin platform that enables supply chain visualization using sequential graph layout and enables graph analytics. The solution included building a full-stack cloud-native platform on Azure, using a Graph database, data pipelines, and implementing an SPA application that enables graph visualization of the data. A custom-made platform is designed to be more efficient, easy to use, and less costly compared to the already existing off-the-shelf one.

Digital Twin Platform preview #1

Project Objectives

• The general goal was to replace the already existing off-the-shelf platform with a more efficient and less costly custom-made Supply Chain Digital Twin platform
• Allow the user to overlook the entire material flow globally
• Enable user-friendly and performant UI visualization of the supply chain as a graph, by making sense of the connected data in the graph
• Implement supply chain visualization using sequential graph layout
• Improve filtering of the supply chain data, traversal through the graph, and graph analytics
• Have the most suitable DB engine for storing and querying supply chain data
• Build an ETL Data Pipelines to easily extract data from the sources and manage it consequently

The Challenges

While developing the Supply Chain Digital Twin solution, our team overcame the following challenges:

• Replacing off-the-shelf solution that has performance and usability issues with customizable full ownership solution.
• Visualizing the supply chain data in Sequential graph layout. The sequential layout is designed to display data in situations where information flows from one level to another, such as material and products flow in the supply chain.
• UX/UI challenge to make sense of the connected data in the graph.
• Ensuring filtering of supply chain data in multiple dimensions, like plant and/or material data.
• Enabling navigation and traversal through the graph, by expanding and collapsing nodes.
• Implement graph visualization based on the D3.js’s tree layout, that is using the Reingold–Tilford “tidy” algorithm.
• Defining and implementing graph data model and data architecture for the application. The company’s provided multiple data sources, from their internal systems, that are in flat relational format.
• Choosing the best-fit DB engine for querying and storing supply chain data that satisfies application business requirements, enables sequential graph layout visualization, filtering data, aggregating data, traversing, and calculating.
• Designing and implementing data ETL (Extract Transform Load) pipelines to extract data from provided sources, transform the data into a graph data model, and load that data into the systems Neo4j Graph DB.

The Software Development Process

The whole software development process started with a Lean Inception workshop, where the client and our developers got together intending to develop a project scope. For us, it was crucial to understand the business domain, supply chain material flow, and the data we dealt with. When we agreed on the project scope, our developers started developing a Proof of Concept for core use cases of the application, in order to test multiple Graph DB engine choices. Another Proof of Concept was developed for Sequential Layout Graph Visualization of the material flow. After we successfully completed the POCs, we could proceed with the development of the project itself. Consistent collaboration and communication between the team and stakeholders, and working together towards understanding the complex supply chain data flows ensured a successful outcome of the project.

The development period started in July 2021 and lasted until the end of November 2021.

The RUBICON team consisted of:

• Product Owner
• Software Architect
• UI/UX Designer
• DevOps Engineer
• Frontend Developers
• Backend Engineer
• Data Engineer
• QA Tester

Results

Due to exceptional knowledge and consistent collaboration, our team delivered the final product in five months.

They managed to:

• Create a Digital Twin platform, a custom full-stack cloud solution for graph analytics, filtering, traversing, and visualizing the supply chain data
• Implement a custom application that visualizes supply chain data in Sequential graph layout, using D3.js JavaScript library
• Make the software that enables graph analytics filtering the supply chain data in multiple dimensions, as well as the navigation and traversal through the graph
• Utilize the Neo4j Graph database engine, intended for querying and storing big supply chain datasets
• Implement data ETL pipelines, that transforms and loads the data into the system on a daily basis

Digital Twin Platform preview #2

Technology Stack

Back-End Technologies

• C#, ASP.Net Core
  - Implementing the backend API
• Neo4j
  - Storing and modeling the supply chain data
  - Querying the supply chain
• Azure Data Factory
  - Automating ETL data processing of supply chain data

Azure Technologies

• Azure Active Directory
  - Implementing single sign-on authentication
• Azure Application Insights
  - Monitoring the application
• Azure App Service
  - Hosting the backend API
• Azure Storage Account
  - Storing datasets for graph database and hosting the frontend single page application
• Azure Virtual Machine
  - Hosting the Neo4j database

Front-End Technologies

• D3.js
  - Implements tree layout, that is using the Reingold–Tilford “tidy” algorithm for layout and node position calculation
  - Implements Sequential graph layout
  - Navigation, traversal, and interaction with graph nodes
• Angular
  - SPA implementation

DevOps

• Azure DevOps
  - Used for all-out collaboration with source control, work tracking, and continuous integration and delivery
• Docker
  - Packaged our solution for easy and quick deployment
• Iaac with Terraform- Terragrunt
  - To provision and configure our environments we used a combination of terraform and terragrunt

Digital Twin Platform Preview

Digital Twin Platform

Information

• Company: Global Chemical & Consumer Goods company
• Region: Western Europe
• Industry: Consumer Goods
• Project Duration: July 2021 — November 2021
• Project: Supply Chain Digital Twin Platform

Originally published at: https://www.rubicon-world.com/case-studies/digital-twin-scm-platform/