From there, engineers evaluate the complexity of the assembly process and the time required for each step. That typically involves detailed timing studies of the most demanding stations to define the overall system configuration. Once those parameters are established, the machine platform is selected based on production requirements. 

Electric actuators and robotic workcells are often used for lower-volume applications with cycle times of 2 seconds or longer, while cam-based systems are better suited for higher-volume production, capable of processing multiple parts simultaneously while approaching 1-second cycle times.

 

Start With Process Visibility

Cycle time optimization begins with understanding where time is actually being spent.

“Often it is testing procedures like leak testing, harmonic or vibration testing, or forms of electrical testing that are bottlenecks,” says Sam Kleindienst, application engineer at Edgewater Automation. “A lot of time, those are costly stations, so they are pushed to go as quick as they can to minimize the number of parallel stations needed.”

“Settling times are most overlooked,” he adds. “Tests in theory can be done in certain cycle times, but to get them as accurate or consistent as required can often take more settling time that is easily overlooked.”

For identifying bottlenecks, engineers rely on both tools and experience. 

“There are simulations that can be programmed and analyzed, but my go-to is a good ol’ fashioned timing chart,” Kleindienst says. “That lets me quickly look at problem stations without the full effort of a complete concept and simulation programming.”

 

Eliminate Bottlenecks Through Line Balancing

A single slow station can limit the performance of an entire system.

“Running event simulation software like JaamSim often helps find bottlenecks in multistation systems,” says Trudeau. 

But resolving them often requires changes to the system itself.

“Cycle time losses usually appear during test and debug—early stages of running the equipment,” he explains. “Even after proper sizing calculations, we sometimes find that a component falls short in the real-world application. An example was a pneumatically actuated rotary indexing table. The table was sized accordingly, but was unable to achieve the expected cycle speed. The solution was to reduce mass on the dial being indexed. This had the desired outcome as physical constraints did not allow for upsizing the indexer and would have contributed to project delays.”

In other cases, bottlenecks require changes to material handling. Trudeau points to a pallet-based system that fell short of its cycle time target during debug.

“We had a recent project that was a pallet-based power-and-free system with operators performing manual parts loading that, during the debug phase, exhibited a shortfall in cycle time,” Trudeau explains. “The culprits were pallet hard stops and gaps between pallets. The pallet hard stops introduced unexpected ‘bouncing,’ preventing high-speed pallet transfer through the conveyor system. Hard stops were replaced with pneumatic cushioning stops, eliminating ‘bouncing’ and allowing for higher pallet travel speeds. We analyzed the system and found there were delays at certain pallet transfer locations. Additional pallet accumulation was added, and system timers were optimized to get more pallets in motion where practical.” 

 

Optimize Part Flow and System Layout

Material handling and layout often determine whether a system achieves its theoretical cycle time.

“While equipment and component selection gives us the ‘possible’ cycle time, layout and parts flow have the greatest impact on achieving what is possible,” says Trudeau. “Robots, actuators, and cylinders have minimum travel and actuation times. Those speeds will not be achieved if the machine layout is not well thought-out.”

In multi-station systems, poor flow can create congestion. 

“Handling of multistation systems can have an impact on cycle time and equipment cost, layout and size,” says Kleindienst. “Often to keep parallel stations running without traffic issues, they need to be broken off of the main line and properly spaced to allow needed part queues and product exit routes that don’t delay adjacent stations.”

Engineers also caution against overcomplicating part handling. 

Kleindienst says a common mistake is having robots handle too many parts at once, which can create issues if parts are not properly constrained or the end-of-arm tooling is not compliant enough to pick multiple parts reliably from a single taught position.

 

Apply Automation Strategically

Not every process benefits equally from increased automation.

“Just because you can, doesn’t mean you should,” says Brian Romano, Ph.D., director of technology development at The Arthur G. Russell Co. “We like to use the term ‘the elegant solution,’ the one that matches the need of the customer’s budget, product life cycle, and internal support capabilities. Being able to match all these needs alongside the customer’s business use case helps to dictate the system design and overall cycle time.”

Overly complex systems can introduce inefficiencies that offset potential gains. The most effective designs balance performance with simplicity, ensuring that automation enhances cycle time, not hinders it.

 

Focus on Motion Efficiency

In high-speed assembly, motion and travel distances can significantly impact cycle time. 

“Minimizing motion distances goes a long way to improving cycle time,” says Kleindienst.

Reducing travel distance between processes can significantly improve cycle time, because every inch of motion adds time to each cycle, he explains.

However, speed must be balanced with system performance. “Motion control axes need to be designed to a level that anticipates not only the rated speed, but the abilities to accelerate and decelerate at full load,” says Romano. “We have seen systems on other machines where the accel and decel are not considered and therefore, eat into the real cycle time.”

System tuning also plays a role. 

Romano adds, “An overdamped velocity response will increase overall cycle time. An overdamped response can delay the time for a stabilized ‘in-position’ signal and increase the needed station cycle time.”

 

Use Data to Drive Continuous Improvement

Cycle time optimization does not end once a system is installed.

“The first and most typical way is to monitor the components of OEE,” says Romano. “The performance helps tell how well our machine is operating at the rated theoretical rate. The availability tells us how well our machines are synchronized… Finally, as long as the customer product is within specifications, the quality aspect shows us how well our machine processes are operating.”

Romano says engineers also rely on more detailed programming to monitor station-level performance, such as whether stations are running slower than at commissioning, photoelectric sensor signals are degrading, lighting intensity for vision systems is declining, drive current is increasing, or overall air flow is rising. This type of monitoring shifts the focus from basic process performance to overall machine health and helps identify cycle time issues and inefficiencies. These insights allow manufacturers to identify emerging issues and maintain consistent performance over time.

 

Design for Consistency, Not Just Speed

Ultimately, the goal of cycle time optimization is not maximum speed, but reliable, repeatable performance.

Cycle time improvements often require tradeoffs between speed, complexity and maintainability. 

“This is where engineers who leave their desk, either to walk out to the floor or get on the phone with end users, really shine,” says Kleindienst. “Decisions that seem straightforward behind a computer screen are not always the best in the long-term.”

For manufacturers looking to improve existing systems, the path forward depends on the situation.

If a line is experiencing higher scrap rates, the root cause can range from raw material variability and worn tooling or fixtures to process equipment that needs maintenance or issues with vision inspection lighting, says Romano.

“In some cases, it might be time to consider another business case and perhaps another duplicate machine or one that matches the need in excess of the existing equipment,” he says.

 

For more information on automated assembly, read these articles:
Automated Assembly Systems: Trimming the Delivery Timeline
Manual, Semiautomatic or Fully Automatic?
Debug, Checkout and Startup