At ClearObject, we’re passionate about helping manufacturers achieve operational excellence. Recently, we partnered with a client facing complex production challenges and a desire to move beyond the limitations of traditional OEE metrics.
Overall Equipment Effectiveness (OEE) has long been the gold standard for measuring performance, but in this case, OEE as a metric is incomplete.
Our client, a leader in complex engineered composite solutions, found that their intricate production processes, involving multiple workstations and significant work-in-progress (WIP) accumulation, were not adequately captured by traditional OEE metrics. They needed additional, more granular insights into cycle times, throughput, and WIP levels.
Goals:
Our client’s number one goal was to understand and reduce cycle times. If you consider Little’s Law:
WIP = Cycle Time * Throughput
Cycle time reduction can therefore be achieved either by limiting work in progress (WIP) and/or increasing throughput. Here, they want to keep WIP constant, so they will need to increase throughput.
Limitations of OEE:
The concept of Overall Equipment Effectiveness has been around for decades, and as we’ve mentioned before it is a great metric to track on your journey to improve performance. At the same time, complex manufacturers may need to look deeper to uncover opportunities for efficiency improvements.
The formula for Overall Equipment Effectiveness:
OEE = Availability * Performance * Quality
It’s a simple enough equation, made easier with artificial intelligence (AI) providing accurate and reliable inputs through computer vision technology. Yet OEE doesn’t always accurately capture set up time, time in queue, or even performance. For instance, a machine that has the capacity to run six mandrels at a time may only run one. Traditional OEE might track this machine’s consistent speed with high quality as maximizing efficiency, but in truth it is below capacity.
Set up time, work in queue, performance throttles, and more can be missed and cause unacceptable impacts on cash flow.
The ClearObject Approach:
“With ClearObject, we can get information that is much more holistic than OEE.”
-VP of Strategy & Operations at an Enterprise Polymer Manufacturer
This client’s production process was bottlenecked by WIP and extended cycle times. They needed a solution that could provide a deeper understanding of their operations and empower them to make data-driven decisions. One that was agnostic to all the different types of equipment and signal sources.
Our AI + Vision solution provided the answer. Our team collaborated with the client to develop a custom AI + Vision solution that went far beyond OEE. By strategically placing cameras throughout their facility, we were able to capture real-time data on machine utilization, operator activity, and WIP levels at each workstation.
By capturing real-time data on machine utilization, operator activity, WIP levels, and more, we gave the client unprecedented visibility into their manufacturing processes, all while removing the need to work at the control layer.
ClearVision, our Vision AI solution avoids the complications of Control Engineering which is difficult to manage and expensive to maintain, especially with today’s talent drought. ClearVision can also be configured to provide a broader range of data than traditional controller solutions.
Our Client used ClearVision to identify and address bottlenecks, optimize WIP, and reduce cycle times, resulting in increased throughput and profitability.
The Results:
- ClearObject Vision AI captured real-time data on machine utilization, operator activity, and WIP levels
- Client increased throughput and profitability
- Client gained unprecedented visibility into their manufacturing processes to:
- Identify and address bottlenecks
- Optimize WIP
- Reduce cycle times
Is your manufacturing operation struggling with similar challenges?
Explore the transformative potential of this technology with ClearObject.