-
- News
- Books
Featured Books
- pcb007 Magazine
Latest Issues
Current IssueVoices of the Industry
We take the pulse of the PCB industry by sharing insights from leading fabricators and suppliers in this month's issue. We've gathered their thoughts on the new U.S. administration, spending, the war in Ukraine, and their most pressing needs. It’s an eye-opening and enlightening look behind the curtain.
The Essential Guide to Surface Finishes
We go back to basics this month with a recount of a little history, and look forward to addressing the many challenges that high density, high frequency, adhesion, SI, and corrosion concerns for harsh environments bring to the fore. We compare and contrast surface finishes by type and application, take a hard look at the many iterations of gold plating, and address palladium as a surface finish.
It's Show Time!
In this month’s issue of PCB007 Magazine we reimagine the possibilities featuring stories all about IPC APEX EXPO 2025—covering what to look forward to, and what you don’t want to miss.
- Articles
- Columns
Search Console
- Links
- Media kit
||| MENU - pcb007 Magazine
Modeling an SMT Line to Improve Throughput
June 6, 2018 | Gregory Vance, Rockwell Automation Inc., and Todd Vick, Universal Instruments Corp.Estimated reading time: 5 minutes

One of the major challenges for an electronics assembly manufacturing engineer is determining how an SMT machine will impact throughput. Typically, an SMT equipment supplier will ask for a few (5-10) products to simulate the throughput capability of their machine. Unfortunately, if the engineer works in a high-mix, low-volume environment, he may need to know the impact of a new machine on 1,000 or more products. Currently, there are no simulation tools to effectively model this. This is confirmed in the 2015 IPC International Technology Roadmap for Electronics Interconnections, which states, "In order to better deal with the demands for increased interconnection density and respond to market demands for better return on capital investment in assembly equipment, there is a need within the manufacturing industry for continued improvement in tools and software for modeling and simulation. Needs in this area include better methods of load balancing and improved machine utilization. The tools for determining the balance on assembly lines will need to be flexible to handle the mix of assembly types that manufacturers now face."
Rockwell Automation partnered with Universal Instruments to develop a tool to model a large quantity of products and the impact of varying SMT line configurations. The information used for the modeling includes placements per panel and components placed per hour. With these tools, an electronics assembly plant can be analyzed to identify improvement opportunities and perform "what if" analysis to model impact of machine changes.
Goals for the SMT Line Model
1. Determine the right machine for the product mix.
2. Determine if products are running as fast as they should.
3. Determine if electronics assembly products are built on the optimal line configuration. This is crucial in plants with multiple line configurations.
Development of the SMT Machine Model
1. Discovery that machine cycle times were poor
After sample product simulations were run by Universal Instruments, it was discovered that observed cycle times were two to three times longer than simulated cycle times. This led to a focused effort to understand why. A kaizen event was held to map out the process and observe product builds. Several items that impacted the product cycle time were uncovered. These items were:
1. Component library placement speed slowed down.
2. Imbalance between placement beams/heads due to not having enough nozzles to pick and place the required component packages for the products.
3. Bypassed nozzles and spindles.
4. Large quantity of placements from a single component input.
5. Panel transfer rate into and out of the machine slowed down.
6. Poor optimization and component split between machines on an SMT line.
7. Operator variation in responding to the process.
The most significant item impacting cycle time was not having the necessary quantity of nozzles available for the mix of component packages for the products that the machine/line was building. To maximize flexibility to move products between lines, machines of the same type were equipped with a standard nozzle configuration. The nozzle configurations were changed only when a new component package was needed. To address this problem, a regular nozzle review was implemented to ensure the machines have sufficient nozzles available to optimize the machine programs.
Products were reviewed for the above issues. As items were addressed, the observed cycle times were reduced to align with the simulated cycle times.
2. Realization that cycle time does not represent SMT machine utilization
Cycle time represents how a product is running compared to a benchmark but does not reflect utilization of a machine based upon its throughput capability. For pick and place machines, throughput can be measured in components placed per hour (CPH).
Table 1. Sample of range of placements per panel to run IPC and manufacturer tests.
Manufacturers provide CPH specifications for SMT machines in two ways. The first method is what is often called "Maximum CPH", which represents the maximum speed the manufacturer was able to achieve and the second is based on "IPC 9850", which has CPH categorized by package type. The “placements per panel” required to run these tests are shown in Table 1.
The "IPC 9850" performance tests are useful to compare equipment models and manufacturers to each other, but they do not necessarily represent the products manufacturers are building. This complexity can be understood by comparing Table 1 to the sample product complexity of global product mix in Table 2.
Page 1 of 2
Suggested Items
Nolan's Notes: The Next Killer App in Component Manufacturing
05/02/2025 | Nolan Johnson -- Column: Nolan's NotesFor quite a while, I’ve been wondering what the next “killer app” will be in electronics manufacturing and why it has been so long since the last disruptive change in EMS. I believe the answer lies in artificial intelligence, which has exploded as the next disruptor.
IPC Excellence in Education Award: Zenaida Valianu
05/01/2025 | Nolan Johnson, I-Connect007Zenaida Valianu is the training manager at IPC who brings more than 25 years of expertise in standards and training development to her role. She has revolutionized IPC certification training programs by significantly enhancing their content with comprehensive curricula and engaging materials. She has also been instrumental in developing essential workforce training courses and contributing to various other initiatives.
A Visit With ‘Flexperts’ Mark Finstad and Nick Koop
05/01/2025 | Joe Fjelstad, Verdant ElectronicsAt IPC APEX EXPO 2025, I chatted with seasoned flex experts Mark Finstad and Nick Koop about "Flexperts" and their roles as leading educators and in the realm of standards development for this increasingly indispensable electronic interconnection technology. They have been teaching about lessons learned and how to successfully navigate the “seas” of flexible circuits to help their students avoid the hazards that have taken down many of their predecessors in the past.
Real Time with... IPC APEX EXPO 2025: Improving the Electronics Industry With Advanced Packaging
04/30/2025 | Real Time with...IPC APEX EXPODevan Iyer, the Chief Strategist for Advanced Packaging at IPC, shares insights from his recent presentation at the EMS Leadership Summit. The discussion covers the importance of understanding market segments in IoT, power electronics, and high-performance computing. EMS companies are encouraged to specialize, invest wisely, and collaborate to meet customer needs.
Real Time with... IPC APEX EXPO 2025: The Role of AI in Advanced Packaging
04/30/2025 | Real Time with...IPC APEX EXPOIn a follow-up to his keynote, Dr. Ahmad Bahai, discusses the critical intersection of advanced packaging, computing, and AI in semiconductor innovation with Nolan Johnson and Devan Iyer. He emphasizes the need for new approaches to handle the data economy and highlights AI's role in optimizing electronics manufacturing. The conversation covers challenges in power and thermal management, the impact of AI on EDA tools, and bio-inspired innovations. Predictions about future trends point towards increased efficiency in design and manufacturing.