How to calculate and reduce cycle time
When it comes to production environments, it’s always a matter of how much can be produced, how quickly and at what cost. After all, how effective are we?
Cycle time is one of the best measures we can use to analyze the efficiency of a production process and allows managers to better understand how efficient a process, operator, machine or job is.
What is cycle time?
Cycle time is the total time the production team spends producing a single unit.
Time measurements are the backbone of a manufacturing business. And cycle time is a crucial KPI that allows companies to accurately plan, order materials, and set production and inventory budgets.
Cycle time varies dramatically between manufacturers due to differences in process, the types of products being developed, and what factors they include in the “cycle” measurement.
Users should be aware of what is included in the time calculation and should specify whether the measurement tracks a process or a unit. It should also be clear whether the calculation includes waiting or holding times.
For example, if cycle time is calculated to reflect the time it takes machines to complete the entire set of operations for a part, it is called machine cycle time.
If cycle time is calculated to reflect loading and unloading time between operations, it is known as effective cycle time.
Don’t confuse lead time and takt time! What is the difference between Takt Time, Cycle Time and Lead Time?
How do you calculate the cycle time?
Once the elements of measurement are defined, the calculation is relatively straightforward. In this case, the cycle time is the total production time divided by the units produced:
Ct = Pt/Pu
- Ct = Cycle time
- Pt = Net production time
- Pu = Units produced during net production time
How to reduce cycle time?
Several steps can be taken to reduce cycle time. These are best practices in most continuous improvement initiatives and are found in Lean and Six Sigma methodologies:
Start a process map
A process map manually maps the workflow of a part or finished product throughout the process and at individual workstations. Often, inefficiencies, bottlenecks, wait times, and other issues are “baked in” by legacy procedures or manual data management. Process mapping enables teams to identify and implement improvements.
Calculate the times of existing cycles
You can’t know where to go if you don’t know where you are. Even if the calculation is based on manual data, a rough cycle time used as a benchmark will provide a foundation to build on. This trend is related to the company’s overall equipment effectiveness (OEE). In companies with manual data management, OEE is unfortunately assumed to be higher than it is.
Eliminate waste
With a fully mapped process and an understanding of existing cycle times, improvement teams can begin to eliminate the waste that causes short cycle times. Common types of waste include:
- Quality problems where defective goods are not caught before completion or must be reworked to first quality
- Excessive manual documentation, “passengers” or other error-prone documentation
- Non-value added work
- Overproduction
- Underproduction
- WIP staging, internal material transport or machine layout
Implementation of standard work documentation
Once the problems and root causes are identified and an improvement procedure is implemented, it is essential that the process does not deviate from the new standard and affect the number of cycles.
Standard work formalizes how tasks should be performed. May include instructions for specific operator order of tasks, movements, communication and other standards. This documentation should be available to anyone performing a task and should be used to train new workers. This will help keep cycle times low and prevent deviations.
Machine capacity audit
Most manufacturers have a wide range of finished goods or parts. They can range from simple to complex. This product mix is in action every day based on customer orders so the capacity of the machine must be audited in absolute terms and relative to the complexity of the product.
Do you have enough machine capacity to build a schedule if it is heavily weighted toward a large order of the most complex and time-consuming parts? The schedule must be flexible enough to anticipate this and create production schedules that optimize machine capabilities relative to the order position.
Disadvantages of manual tracking to reduce cycle time
Cycle time is a valuable metric in manufacturing and it is critical to find a baseline to compare current performance and initiate improvements. While these tools are important to get started, truly reducing cycle times requires effective data tracking, process control, and a high degree of organization.
Once started, the amount of manual data management, analysis and recording becomes overwhelming. And because these manual processes take time, they cannot be done with the frequency necessary to continue progress past a certain point.
Such a process is also prone to error. From simply transposing numbers to missing data to outliers, mistakes can prove costly in an effort to improve cycle times. If this goes on too long, managers no longer get the information they need and operators feel overwhelmed with paperwork and forms, which can lead to longer cycle times.
Automate data collection to reduce cycle times
The MachineMetrics Machine Data Platform puts your data to work in a powerful, data-driven analytics engine that connects to equipment throughout the factory.
Data is collected to monitor and report accurate task times, causes of downtime and other critical factors needed to reduce cycle time. By using real-time data from the source, manual recording becomes unnecessary. Actionable insights are generated to allow you to see the results of improvements and dive deeper to drive continuous improvement.
MachineMetrics also provides prescriptive and predictive insights to address waste. Because assets and machine components such as spindles and sensors are connected at the point of production, quality issues can be addressed when or before they occur.
These insights also reveal trends that help you identify areas where you can make additional changes, such as WIP stages, machine layout, transportation bottlenecks, and more.
MachineMetrics helps manufacturers achieve a more accurate “paperless” manufacturing environment. And once improvements are implemented, robust, configurable workflows mean standard work is digital and at the fingertips of anyone who needs it – at a much higher quality.
If you’re interested in reducing cycle times to unlock capacity and improve efficiency, we may be able to help. Book some time with our team to learn the impact of the machine connectivity platform on your work.
This article was written by Jacob Lauzier, Co-Founder and CTO at MachineMetrics, Inc. and was originally published here.
