UBlockout Ramps Shift Production to 100 for Dream Business with TilliT and AWS

When UBlockout planned its international expansion, finding the right manufacturing software solution was a critical success factor for the business. UBlockout shades are made to order with each one having different, stringent size and functionality requirements to meet. Conventional manual processes to meet these requirements would add cost and complexity to the business and limit the company’s ability to further scale its operations. 

With its expansion to Dallas, Josh Boorman, co-founder, and chief experience officer at UBlockout started looking for enterprise platforms to standardize and scale the process. However, it was a struggle, as Boorman said, “Everyone we spoke to said that it would take six to 12 months to be able to deliver a solution. We wanted to find a reliable manufacturing platform that could be implemented quickly and had the ability to scale with us as we grow”.

The search for the right collaborator ended with AWS Partner TilliT. Its solution is natively built on Amazon Web Services (AWS) using AWS Lambda as the primary compute platform, AWS IoT Core and AWS IoT Greengrass to capture data from the factory floor, and other AWS services like Amazon DynamoDB, Amazon Aurora, Amazon API Gateway, and Amazon Simple Storage Service (Amazon S3). This serverless solution helps power smart factories so organizations can manage every step of their manufacturing process. “TilliT integrates people, materials and equipment to harmonize the process of manufacturing, for efficiency, quality, cost, and customer satisfaction,” according to Rafael Amaral, co-founder, and chief technology officer at TilliT.

In less than five months, TilliT implemented a low-code, configurable solution that integrates Magento, the ecommerce backend platform that also supports the customization of the shades for UBlockout. Now, a customer’s order moves from Magento to HubSpot—UBlockout’s customer relationship management tool—where it is reviewed and finalized. TilliT then processes that information and provides directions to different workstations and operators on the shop floor. 

Amaral explained, “TilliT manages the full execution lifecycle. When the order is ingested into TilliT, it appears as a sequence list of jobs that is distributed automatically through the facility to each part of the line. Then the granular process of executing that production demand begins at the level of a single order.”

Every step of the manufacturing process is orchestrated—from staging raw material, to cutting aluminum and fabric, and assembling the shades. Once the production is complete and the shades are checked by QA, the information is sent into the system where it reconnects with TilliT to coordinate with Magento and the shipping vendor.

The entire production process—from order to shipping set up—takes about 35 minutes.

As a result of this process, UBlockout has now implemented a process that can sustainably manufacture up to 100 shades in a shift. Achieving this—and still effectively manufacturing a different, customized shade every time—has been instrumental in allowing UBlockout to scale its business and set itself up for further rapid growth.

A replicable, scalable process has also translated to improved quality. “We can consistently deliver quality and we have visibility into the entire process, from ecommerce to our machines. Even our fabric layout table and cutting saw get measurements directly from TilliT via the ecommerce website, so we eliminate manual errors,” said Boorman.

Standardizing operational procedures has also meant that all new employees can hit the ground running. Boorman said, “It’s very fast to introduce someone to an asset on the shop floor and have them follow the process. We can now onboard a new team member within a day.”

UBlockout plans to continue scaling and expanding its operations from the current facility in Dallas to new facilities in other parts of the USA to improve speed of delivery to customers. Now that it has a standardized procedure in place, improvements in the QA process using visualizations based on artificial intelligence are also in the pipeline, with cameras at every station to identify potential quality issues.