Featured Product
This Week in Quality Digest Live
Six Sigma Features
Mark Rosenthal
The intersection between Toyota kata and VSM
Scott A. Hindle
Part 7 of our series on statistical process control in the digital era
Adam Grant
Wharton’s Adam Grant discusses unlocking hidden potential
Scott A. Hindle
Part 6 of our series on SPC in a digital era
Douglas C. Fair
Part 5 of our series on statistical process control in the digital era

More Features

Six Sigma News
Helps managers integrate statistical insights into daily operations
How to use Minitab statistical functions to improve business processes
Sept. 28–29, 2022, at the MassMutual Center in Springfield, MA
Elsmar Cove is a leading forum for quality and standards compliance
Is the future of quality management actually business management?
Too often process enhancements occur in silos where there is little positive impact on the big picture
Collect measurements, visual defect information, simple Go/No-Go situations from any online device
Good quality is adding an average of 11 percent to organizations’ revenue growth

More News

Abdallah Samaha

Six Sigma

Stepping Into Cloud-Based Quality Control

Lin Engineering deploys cloud-based SPC to monitor quality of overseas facility

Published: Monday, July 7, 2014 - 23:00

Lin Engineering is a California-based manufacturer of hybrid step motors that was founded in 1987 as a consulting company specializing in step-motor applications. Today, Lin Engineering is the largest manufacturer of 0.9-degree step motors in the motion control industry. As the quality and custom-product manager at Lin Engineering, I’d like to share how we experienced stepping into cloud-based quality control.

Quality focus and challenges

Our corporate quality policy is to incorporate 4.5 sigma into daily operations as a means of continuous improvement. We expanded our 4.5 sigma and mean value control initiatives and realized that we needed a statistical process control (SPC) system that would allow for real-time quality monitoring and process control. The mean value control initiative embraces the philosophy that producing “to target” is more effective than producing “within spec.”

This approach removes the boundaries of tolerance during the manufacturing processes and focuses only on the specification target. For example, if a machinist is producing a gearhead shaft with the intent of keeping the outside diameter within spec, the tendency is to machine the outside diameter on the larger side of the specification because it’s easier to remove additional material if needed. But if another machinist is creating the part into which the shaft will be fitted, the tendency is to produce that part’s inner diameter on the lower end of specification, with the same philosophy of being able to remove material if needed. Even if these two components are within spec by themselves, they still may be difficult to fit together during the next stage of production, thus creating variation in the final product. Using SPC would help us to produce all components to target and reduce variation, which meant our production would be more efficient and we could produce a consistent, quality product every time.

In addition, we were monitoring quality in the early stages of product development by manually testing prototypes and samples. Although we consider certain factors (e.g., supplied material, tool wear, operator skill, time of day, and environmental conditions) relatively constant for short periods of time, these same factors contribute to manufacturing variability and reduce capability during high-volume production that spans days or months.

Our Lin Engineering facility in Nanjing, China, created another challenge: We needed to ensure that products produced in our China facility were without defects. Oftentimes overseas suppliers don’t deem a defect to be as great as it would be perceived in the United States. If products from the China facility fail inspection in the United States, it is costly to ship them back to China. And we didn’t want to fall short on our promises to customers by providing anything less than top-quality product.


In our search for an SPC provider we chose InfinityQS. Its ProFicient platform provides a manufacturing intelligence hub powered by a centralized SPC analysis engine. The software offered us a complete package that included both basic and advanced analytical tools and tracking mechanisms. The software’s ability to collect data based on time intervals throughout the product life cycle allows for adjustments to bring machining or assembly back to the ideal specification, which also upholds our mean value control initiative.

We are now able to collect data at the beginning of processes, such as component outside diameter and inner diameter, to ensure minimum deviation from the target. Then, at final inspection, we measure complete product performance to prevent any defects from slipping through the cracks.

In order to integrate information from our overseas facility, Lin Engineering has adopted the cloud-based deployment of ProFicient on Demand, which allows us to monitor the quality of our China location in real time and access information anywhere, whenever it is needed. For example, when an out-of-spec issue occurs in our China facility, we instantaneously receive an automated email alert, allowing operators to take immediate corrective action—long before the product is shipped.

Lin Engineering is also utilizing ProFicient’s control charts and reporting capabilities. On the manufacturing floor, operators use the X-bar and range charts to monitor real-time quality, whereas management reviews tracking charts to identify areas for continuous improvement.


• Reduced defects by monitoring supplier quality in real time

• Instilled mean value control—“target” rather than “within spec” philosophy

• Obtained confidence in meeting customer requirements and producing a high-quality product

• Verified capabilities and viewed trends through control charts

Results and benefits

Because of our ability to measure subcomponents, produce to target rather than within spec with mean value control, and monitor both internal and supplier quality, we have seen a reduction in defects on finished goods, as well as reduction in inspection requirements. Control charts provide us with additional insight. Using a parameter essential to motor performance in our control charts, top management is able to look at trends around this parameter and easily gauge whether manufacturing processes are functioning at an optimal level.

While we’re already using some of ProFicient on Demand’s functions, namely the control charts, we are contemplating expanding to the other modules, such as assignable cause and corrective action, and inspection.

We are looking to improve our confidence in our capabilities and numbers, which will guarantee a quality product to our customers. Such confidence is important to our future—it allows us to meet our customer requirements as promised. This is a tool that will get us there by helping us to communicate better with our suppliers, using data to drive such communications.



About The Author

Abdallah Samaha’s picture

Abdallah Samaha

Abdallah Samaha is the quality manager and custom product manager for Lin Engineering, a U.S. manufacturer of hybrid step motors that focuses on leading technology designs, high-quality products and customer service excellence. He holds numerous certifications from the American Society for Quality (ASQ), a master of science in mechanical engineering from University of New Orleans and a bachelor of science in mechanical engineering from University of Louisiana at Lafayette.