An Industry 4.0 company, Raven.ai is helping manufacturers accelerate continuous OEE improvement by sharing real-time data insights and guiding actions

OEE stands for Overall Equipment Effectiveness. It is a method of analyzing the performance of a machine or piece of equipment compared to its theoretical maximum capacity. OEE applies only to periods when the machine or piece of equipment is scheduled to run, though, i.e. you don’t include overnight downtime if the machine is not scheduled to run overnight. OEE is one of the most important performance measurements in modern manufacturing facilities. By optimizing OEE, you can increase capacity, reduce costs, improve quality, and/or increase efficiencies in your production lines.

You may have significant capacity potential in your factory that OEE optimization can release. This will increase production and/or make your operation more efficient and cost-effective. In addition, taking steps to improve OEE is almost always more cost-effective than the alternatives. This particularly applies in the long-term but often also applies in the short and medium-term too. The alternatives include adding a new shift, increasing overtime, purchasing new equipment, outsourcing production, or opening a new facility.

Raven.ai is one such manufacturing technology leader that has developed an Industry 4.0 technology solution that solves the challenges that many of its team members have faced in their past lives: a fast and simple way to capture, analyze and act on contextualized production data. It has loved building Raven and seeing so many teams work well than ever before with it. The company and its team helps organizations empower the frontline and improve operational performance with its automated contextualization and OEE software. Raven combines and analyzes data from machines and input from operators to provide a real-time, meaningful timeline of events with context for everything that’s happening on the line — accounting for 100% of production time and OEE losses. By replacing manual pen-and-paper tasks with smart devices, operators can tag the exact reason for downtime and inefficiencies with the touch of a button. With round-the-clock data collection, Raven’s visual UI displays real-time alerts to drive what actions and improvements to take next, driving continuous improvements across plants. Powered by AI-based cloud analytics and IoT/edge devices, Raven enhances the day-to-day work of frontline teams.

OEE software: Trusted by leading manufacturers worldwide

Give your frontline a voice by capturing their critical insights using intuitive HMIs. Empower them to win each shift with gamification, real-time performance insights and guidance. Pull data from your existing machines and systems to automatically record downtime reasons, and capture frontline context to account for 100% of production time. Gain an accurate, bird’s eye view of what’s happening now and in the past so you can resolve real-time and systemic issues — fueling your factory’s continuous improvement. Raven’s Automated Downtime Labeling helps capture and contextualize production data to accurately account for how machines and people spend their time.

Raven connects to your existing machines, sensors and systems (PLC/ERP/MES) to automatically pull data into your production timeline provide context on machine states and label downtime reasons. This means less time and repetitive effort from operators, and more productivity on the shop floor. Trust us, they’ll appreciate less questions asked.

Replace pen-and-paper tasks with a simple tap. Your frontline can tag the exact reason for downtime with Smart Assistant placed on your lines and work stations.  Capturing human context is critical to understanding what’s happening on the shop floor and making improvements. With a visual and intuitive HMI on their machines, operators are engaged to provide meaningful context in just a few taps – and only when machines can’t provide the context. With or without greasy gloves, context is captured easily and operator burden is reduced by 10x. Supercharge your Industry 4.0 tech stack with the only solution that contextualizes all shop floor and production data. Raven integrates with existing machines and systems for data harmonization across all your smart factory devices and apps. So you can start identifying areas for improvement as soon as data starts flowing, for rapid time-to-value. Monitor the live status of machines and view real-time target performance by shift using OEE monitoring software. With insights front and center on the line, in standups and 1:1 chats, operator and supervisors can drive immediate improvements.

With Raven’s real-time reporting platform, spend less time crunching numbers and more time on improving production processes. Every minute a machine isn’t running means a lost opportunity. Review trends over time to identify top losses and improvement opportunities as often as needed. Understand availability and throughput, while pinpointing losses. With visibility into metrics that matter, it’s easier to identify bottlenecks and determine a plan of action to correct problems now, rather than later. Accessible from any browser on desktop or mobile, visual dashboards and reports give you real-time performance stats on your production lines, even when you’re not in the factory. With a real-time glance into their productivity on digital displays and end-of-line dashboards, your frontline knows right away when they’re winning or losing – igniting motivation to hit targets.

Martin Cloake | Chief Executive Officer

Martin is an experienced executive and award-winning technology entrepreneur with a background in Manufacturing, Data Science, IP, and Operations Management. He holds multiple patents and he is a Mechanical Engineering graduate from McGill University in Montreal, Quebec.

Mr. Cloake published articles and post regularly on the topics of Industry 4.0, Leadership, Manufacturing, and Augmented Management.

“Our team has developed an Industry 4.0 technology solution that solves the challenges that many of our team members have faced in their past lives: a fast and simple way to capture, analyze and act on contextualized production data.”