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Interactive Demo

Welcome to the interactive demo. Here, you’ll learn the steps to implementing a successful data initiative project, and understand how you can use Doodlebase to leverage the power of today’s reporting and data-analysis technologies.

Introduction

After receiving an increase in returned products, Acme Inc. is determined to understand how they can reduce manufacturing cost and increase quality of their video player devices.

Tools Overview

Step 1: Define Your Objective

Purpose: The purpose of this project is to improve the manufacturing process of Acme's video player device by establishing visibility across their supply chain. They’ll start by creating a Doodlebase Network for their factory in Shenzhen, China.

Identify Key Processes: Acme’s next step is to define the data they’d like to capture. Acme’s engineers are interested in collecting data from the following manufacturing processes (machines): Serialize, SMT, Wash, ICT, ESS, & Final Test.

Step 2: Establish Your Network

Create a Network: Now, a Network is created for Acme that will capture data related to their video player product. Later, Acme may use additional Networks for additional products within Doodlebase.

Create Routes: The next step is to use the Doodlebase Route Designer software to create one route for each machine Acme wants to collect data from. Since Acme is interested in collecting data from five machines, they’ll create five routes.

Learn more about the Doodlebase Route Designer

Step 3: Connect Your Machines

Send your data: Now, it’s time for Acme to send data from their machines to their Doodlebase Network. To do this, they’ll need to access the machine’s client (computer), and write a program that collects, structures, and sends data to Doodlebase.

Structure your data: Before data can be sent to a Doodlebase Network, it needs to be structured. To make this process easy, Acme uses the Doodlebase Transformer, a .NET and COM capable library that offers simple methods used to collect, structure, and send data to Acme's Doodlebase Network.

Learn more about the Dooldebase Transformer

Transforming data into information

Acme’s data is structured, and stored securely in the Doodlebase cloud. It can now be accessed from anywhere in the world. Here are some things Acme can do with their data:

Build Dashboards

Build automatically refreshing, interactive dashboards for business users, engineers, and contractors.

Share with Users

Keep everyone on the same page by adding users to the Network, enabling them to use the data however they want.

Third Party Services

Use the Doodlebase APIs to “plug in” third party products such as machine learning, reporting, and more.

Reports

Defining Reports: To fulfill their mission of improving the manufacturing process, Acme wants to build live, interactive dashboards that can be accessed by their business and engineering teams. They set out to build the following dashboards:

  • Factory Summary: Used as a starting point to uncover supply chain issues
  • Process Analysis: To investigate process (machine) related manufacturing issues
  • Product Analysis: To investigate product & component related manufacturing issues

Building Reports: To make the report building process easy, Acme will use Query Builder with Microsoft Power BI. With Query Builder, Acme can quickly access portions of their data for instant reporting feedback and root cause analysis.

Learn more about the Doodlebase Query Builder

Acme then publishes their reports online to be shared with their users. You can interact with Acme’s reports below by clicking the various visuals such as the bars in the bar graph for dynamic cross-filtering. This interaction is made possible by Doodlebase’s schema.

The report above reveals that there is a potential issue with the ICT process on January 11th. On that day, eight products failed their test. Let’s examine the Process Analysis Dashboard below to understand if this issue is related to the process (e.g. faulty machine) or product (e.g. cheap components). Click on the ICT1 process and select different variables to examine a run chart for each failed variable.

As you explore the run charts above, notice how variables are not consistently exceeding their control limits. Therefore, the issue is not likely process (machine) related. Next, let’s view the Product Analysis Dashboard to examine the nature of product failures.

After reviewing the symptom and cause information of the failed products above, there seems to be a common issue in LED failures. Acme concludes that by improving the quality of their LED components, they’ll be able to improve product yield and decrease rework time.

Conclusion

After further investigation, Acme’s process engineers make the recommendation to switch to a new LED components manufacturer. As a result, product yield increases by 5%, and rework time is cut by 30%. Not only is Acme saving $55,000 in monthly cost on their products, they’ve also achieved their goal of delivering higher quality products.

First Pass Yield

Increase in 5% due to higher quality LED components.

Rework Time

Less product defects means less time spent reworking failed products. Product Lookup dashboards also enable easier information access for improved rework time.

Cost Savings

Less scrap material, fewer product returns, and a higher overall quality improve factory-wide savings by $55,000 a month.

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Custom Reports

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connect@doodlebase.io

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