Among the ways manufacturers can increase efficiency, productivity, and profitability is by improving cycle time—the average time it takes to manufacture a single lot from start to finish. There are several steps you can take to improve cycle time, including investing in technology that can automate repetitive tasks and improving communication and collaboration across your factory.
You’ll first need to map out your process and identify the bottleneck processes that limit the output of the entire factory – perhaps because they simply take the longest to complete or because there are too few of the required process tools to keep up with the needed processing. Focusing on these bottlenecks and inefficiencies can help reduce cycle time.
Several other factors impact cycle time. The time lots spend waiting to process can add significantly to cycle time, so look for ways to reduce wait times, such as through the use of automation or streamlining handoffs between different teams or departments. Similarly, complex processes with many steps take longer to complete so it is helpful to eliminate unnecessary process steps and streamline workflows. Another significant factor in cycle time is the number of lots in the factory—the work in progress (WIP). If WIP exceeds the factory’s capacity, there is an exponentially higher wait time between each lot. Variability is also a common impact on cycle time since fabs operate in the real world. Variability in processing time and the rate at which new lots are started in manufacturing are also frequent causes for delays. A manufacturing execution system (MES) can be a valuable tool in reducing cycle time.
The MES is the operational backbone of many factories and can help monitor, control, and optimize production processes in real-time. The SmartFactory MES can help improve cycle time by providing real-time visibility, automating data collection, using predictive analytics, improving communication and collaboration, and optimizing production processes.
- Real-time visibility into the production process enables you to monitor key performance indicators (KPIs) such as production output, downtime, and quality to identify and address issues quickly and minimize disruptions.
- Automated data collection eliminates the need for manual data entry and reduces the risk of data entry errors. The data can then be used to optimize the production process, identify bottlenecks, and improve cycle time.
- Predictive analytics can be used to forecast demand, identify potential production issues, and optimize production schedules.
- Improved communication and collaboration between different departments and teams involved in the production process also can help identify and address issues quickly.
- Dynamic process optimization through automated lot scheduling, dispatching, and routing based on real-time conditions within the factory can help improve productivity and reduce cycle time.
Whatever steps you take to reduce cycle time, it’s important to measure and track your progress, both to ensure the improvement steps you’ve taken are achieving the results you expect, and to identify areas that still need improvement. Be sure to celebrate your successes along the way!
