Use Case: Improving Parts Management
This article outlines how Emcien can drive inventory improvement and cost reduction automatically with parts data to aid in parts management. The objective of this use case will be to discover patterns in parts usage to improve kitting, inventory planning, availability, and minimizing obsolescence costs.
Align your data with a use case
Note: This procedure uses the Truck Manufacturing example data set. Your data should be similar to the example data, with columns for material names for a manufacturing environment.
Data Prep
Optimize your data.
This data set contains truck manufacturing data in the wide format. The wide format is the more universal and most commonly used Emcien format. You can use the wide format for multi-dimensional data, such as demographics or configurable products. In the wide format, each transaction is identified by a single row of data.
In our example, the column names are different kinds of parts used in the manufacturing of trucks. This parts data is ideal for any analysis that seeks to optimize bundling, kitting, or to minimize materials cost in manufacturing. If your data does not look similar to the wide format data here, don’t worry. Emcien Patterns also works with ‘receipt’ type data. For more information about data preparation and different data types supported, see our Data Prep Guide.
Uploading Data
Upload your data for analysis.
This article covers how to upload data files to Emcien using File Transfer Protocol (FTP).
Make sure you've prepared your data before uploading to Emcien. Check out the Preparing Your Data article for more information. You can also email us at [email protected] for help getting started.
Upload using Drag and Drop
In Emcien version 2.14 you can now drag and drop files into the application for processing. If you are using a previous version you can use one of the other methods listed below.
Uploading Data to the Emcien Cloud
You can upload data files to Emcien using SSH File Transfer Protocol (SFTP) and your preferred FTP client, such as FileZilla or Cyberduck.
To connect to Emcien using your FTP client, use the following credentials:
Host: feeds.emcien.com
Username: {Your Emcien Feeds server Username}
Password: {Your Emcien Feeds server Password}
Uploading Data on Mac or Linux
Launch your preferred FTP client. If you do not have a preferred FTP client, we recommend Cyberduck.
For this article, we use screenshots of Cyberduck.
Click Open Connection.
Enter the below credentials and click Connect.
Your FTP client will then display the files on your server.
Server: Your Emcien URL. This URL was set by your IT resource during installation.
Username
Password
Drag and drop your data file to the server files in your FTP application.
On the Emcien home page click Analyze Data. You’ll see the data files on this screen.
Uploading Data on Windows
Click the Start button . The Start menu is displayed.
On the Start menu, click Computer. The Computer folder is displayed.
Right-click anywhere in the folder and click Add a network location.
The Add Network Connection wizard is displayed. Click Next.
On the next tab,select Choose a custom network location. Click Next.
On the next tab, enter your Emcien URL.
Then click Next.
Clear the Log on anonymously checkbox.
Type data in the username field. Click Next.
On the next tab, name your shortcut Emcien by typing it in the Type a name for this network location field. Click Next.
On the next tab, click Finish.
Type feeds1 in the password field. Check the Save password checkbox so you can connect directly in the future.
Click Log On. You can now drag data files into this folder.
On the Emcien home page, click Analyze Data. You’ll see the data files on this screen.
Analysis
Begin your analysis.
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Using your preferred Internet Browser, navigate to the Emcien Sign In page:
- local VM users, go to: http://localhost:5115
- For cloud users, go to: http://patterns.emcien.com/
2. On the Home page click ACME Truck parts.
Results
See your results.
The Dashboard page for the truck analysis data set is displayed below. The interactive graphic on the home screen is the Connections Map, a representation of the analyzed data displayed by how materials were ordered (or connected) together.
Each color represents the connections identified as relevant patterns in the data set. Mousing over each section will display examples of the corresponding clusters. These include Core and Typical Connections (materials frequently purchased together), and Low Volume Disconnected Items (materials rarely purchased that are prime for elimination). Notice at the top of the screen the links to separate tabs in the engine.
Clicking on the perspectives tab will bring up a list of each kind of data connection found in the analysis.
The perspectives screen organizes the analyzed results into three groups of patterns that match many use cases. The default view shows Core Clusters, which are the high frequency and highly correlated items in the data. Opportunities for Bundling and kitting are in items that often sell together and are sold together frequently, which are seen easily in Core Clusters. Core Clusters are the connections that are central to understanding the data.
To leverage these results, click the “Download CSV” button in the upper right hand corner to save the analysis as a CSV file, to be imported into Excel or other manufacturing solutions (also available as an API).
Clicking on the Non-Obvious Clusters shows us opportunities in inventory management for avoiding shortages or excess inventory. In the example above, if we were to run out of the Dual-Elect Battery switch, we would potentially effect the sales of Wheelbase 451. These are connections that don't occur frequently, but when they occur, they mostly occur together.
Clicking the Disconnected Items shows us excellent candidates for inventory reduction. Seen here are items that don't have any meaningful connections with other items. If an item on this list is low margin or has high storage cost it can be considered for reduction.
Another feature that can be helpful for inventory management is the Substitutions feature, located at the top of the screen in a tab next to perspectives.
Emcien software automatically identifies similar items or parts that can be replacements for each other, showing an opportunity to either remove one of the items from production or reduce the inventory of both items. These are the individual items that “act” like other items in the data set- meaning that these items are ordered with the same group of items but are rarely, if ever, seen together. In this example, we have two similar shades of green which are ordered fairly often, but never ordered together.
Parts Commonality
Finding parts commonality and standardization is a valuable capability for manufacturing and supply chain offered by Emcien. To achieve this, go to the Cluster Search screen using the search drop-down menu:
And search for clusters with a large size (pictured below are clusters of at least 7 items):
These clusters are groups of items ordered together frequently. These results are similar to our Core Clusters, but provide standard configurations for large groups of items.
For more detail on performing searches, see our Guide to Searching.
Each of these product relationships can be analyzed automatically to identify hidden carrying costs and opportunities for bundling and more efficient product planning. For help using Emcien to optimize your inventory you can contact your Services team member directly or email us at [email protected] and we will connect you with a services professional.
