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Case Study: Assembly Productivity Improvements

Leela AI’s visual intelligence platform drives productivity improvements at heavy equipment manufacturer

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The Challenge

A US based manufacturer was looking for ways to increase production capacity on an assembly line for large industrial equipment. At any given time, up to a half dozen units are being assembled by multiple technicians, primarily using portable tools. The craftsman-like assembly process can take several weeks. Each unit is highly customized and requires different components and processes. As a result, the opportunity for robotic automation and data analysis based on PLC derived data are limited.
The customer performed time and motion studies to measure productivity. Yet considering the extensive customization and complexity, the analysis was incomplete.

The Solution

A manufacturing rep saw a demo for Leela Platform. The cloud-hosted software uses camera input coupled with AI algorithms to measure and interpret the interactions between manufacturing workers and their tools, machines, parts, and products. The software can help engineers measure key performance metrics, identify and analyze bottlenecks, and discover and transfer best practices. Leela Platform is especially useful for analyzing complex manufacturing tasks involving human workers — a typical blind spot for sensor-driven IoT.
The heavy equipment manufacturer agreed to an on-site pilot. Set-up was easy, requiring only the magnetic mounting of a few industry-standard cameras that send encrypted data back to the cloud using a standard Internet link.
The team at Leela AI presented Leela Platform with ten video samples of the production stations and taught the AI to identify common objects and actions within the assembly area. Working closely with the customer’s industrial engineers, Leela AI staff fine-tuned the AI and enabled the desired privacy protection features, ranging from face and body blurring to optional disabling of video review.

Within three weeks, the system began to provide actionable insights. The fast training time is enabled by Leela AI’s hybrid causal/neural networks architecture, which is capable of rapid self-learning.

Leela Platform recorded assembly time for each station, as well as value vs. non/value added time for the whole line. The software tracked tool and equipment use and measured tasks such as picking up and carrying tools and parts, attaching parts with various tools, and tracking assembly steps. With the help of our visual AI tool, the customer compared metrics between stations, shifts, and time periods, and identified and flagged potential safety issues, such as time spent working too high up on ladders.
At the end of each shift, teams reviewed the analytics from the Leela Viewer KPI dashboard, which was displayed on a wall-mounted screen. Leela Viewer displays multiple timelines for easy comparison and analysis. It also enables industrial engineers to drill down and watch videos with labeled object overlays and task identifications.

The Payoff

Six months after the pilot was initiated, the customer had measured significant improvements in efficiency and capacity from process changes inspired by Leela Platform insights. Armed with this information, the team implemented changes to the production process that improved line capacity by 11%. The metrics also enabled more informed adjustments to the staffing plan to avoid over- or under-staffing.

The pilot’s success encouraged the customer to sign a commercial contract and expand the software to cover more assembly stations. The company is now expanding the scope of the engagement to support lean manufacturing process adherence, including flexing and 5S.

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Want to see how Leela AI can improve assembly operations?

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