Data-driven: How award-winning Corning teams power smart manufacturing


Manufacturing 4.0 digitalization technologies like machine learning, robotics, and advanced modeling are propelling progress during this Fourth Industrial Revolution.

James Graf, Steve Ingram, Ioannis Papavasileiou, and Farid Taghiyev contribute to Corning’s Manufacturing 4.0 teams.

Having the right people, materials, and equipment is only the start of manufacturing excellence today. As an industry leader, Corning also harnesses the power of data through interconnected digital systems to maximize value and effectiveness. 

The National Association of Manufacturers’ Manufacturing Leadership Council has taken note, again recognizing three Corning cross-functional teams as finalists for the 2023 Manufacturing Leadership Awards, an encore of 2022’s three-trophy performance

The awards honor those who are shaping the future of global manufacturing through digitalization, a concept known as Manufacturing 4.0, which emphasizes the use of smart machines, artificial intelligence, automation, and interconnected data to accelerate performance gains. This year, Corning won the High Achiever Award for Operational Excellence and was a finalist for two awards in the Engineering and Production Technology category.

Corning deploys Manufacturing 4.0 practices across its global operations. ©Christopher Payne / Esto

“These projects really exemplify the use of Manufacturing 4.0 principles: using data to drive better decisions, better efficiency, and better planning,” says Grethel Mulroy, project manager, Smart Manufacturing Solutions. 

“We’re competing against some of the biggest companies you know. This recognition demonstrates the quality of the work and the value Corning’s generating through digital,” adds Cathy Clark, IT director, Manufacturing. “We know these achievements can add value in different areas of the business, providing even greater return on investment.”

Let’s hear from members of the teams...


Corning Pharmaceutical Technologies:  SmartFlow algorithms boost vial production rates

As COVID-19 raged, Corning opened a new facility to make glass vials and accelerate vaccine distribution as part of the U.S. government’s Operation Warp Speed. Robots called automated guided vehicles (AGVs) transported 600-pound vial cassettes along the production line. 

During startup, however, sluggish AGVs caused bottlenecks, stifling output during a pandemic. 

“Previously, we might have seen this as a hardware problem requiring additional AGVs,” says James Graf, senior controls engineer. “But because we designed the plant with foundational digital architecture, we were able to access the systems data, understand what was causing the traffic jam, and quickly apply a smarter software solution to achieve the needed productivity with our existing AGVs.” 

“It was a real eureka moment seeing those two-ton vehicles responding to our code changes, making smarter decisions,” says Graf. “Digital expertise is like the grease that makes our whole manufacturing engine run faster and smoother.” 


Check out this video about Corning vial manufacturing which shows active AGVs at 4:12.

Corning pharmaceutical glass vials enhance the storage and delivery of drugs, providing more reliable access to medicines essential to public health.

Corning Optical Connectivity Solutions:  Video analytics enrich process understanding

Attaching tiny, 100-micron-diameter optical fibers to cable connectors is a delicate, automated task hidden inside specialized machinery. To improve production times and enhance product quality, Corning needed to systematically evaluate the process in action. 

A diverse team of experts devised a novel way to capture video of the process and then use machine learning to analyze the massive amounts of data generated via this image-evaluation framework. 

“We could identify process issues no one had been able to see before,” says Ioannis Papavasileiou, senior machine learning engineer. “With that baseline understanding, we could test new hypotheses and make improvements.”

Best of all, these techniques can scale to other production lines. “We now have a valuable tool to help advance quality and yield for more products across Corning’s businesses,” says Papavasileiou.

One of Corning’s connectorized cable solutions: an SC APC to SC APC patch cord.

Learn more about Corning’s leadership in optical communications technology and manufacturing.


Corning Manufacturing Support:
Modeling system optimizes materials use

Corning’s proprietary fusion manufacturing process requires several unique materials to create specialty glass. Corning sought to optimize use of these materials at the macro level through better purchasing and inventory management decisions and at the micro level via manufacturing process improvements. 

The cross-functional team’s solution? Build a multiscale business model that helps drive new efficiencies across the board. 

“The answers are in the data,” says Steve Ingram, an IT senior manager. “We not only understand how much material we have in our global supply chain, but we’re also now able to better forecast future needs and make smarter buying decisions on a macro scale.”  

“And on micro scale, our model—when fully implemented—can capture all the manufacturing steps,” adds Farid Taghiyev, an industrial engineering supervisor. “We will be able to run scenario analyses to generate detailed improvement plans to inform how we operate as well as how we schedule equipment upgrades.”

Such progress is part of an exciting, ongoing evolution. “These digital solutions are like a living organism,” says Ingram. “We keep feeding them data, updating our models, asking new ‘what if’ questions, and refining for better outcomes across multiple Corning businesses.”


Check out Corning’s proprietary fusion manufacturing process for precision glass.


Looking ahead

The teams credit Corning’s deep talent across IT, operations, and supply chain for the recent victories – and the successes to come. 

“Manufacturing 4.0 takes digital to the next level where you have interconnected systems talking to each other,” says Papavasileiou. “We can now make more informed decisions along the whole line—from raw materials to the final product.”

“We’re finding neat and reliable ways to get equipment, computers, and people all to interact with each other to get the job done in our manufacturing plants,” adds Graf. 

Collaborative wins make the work especially worthwhile.  

“What I love about my job is adding value,” says Taghiyev. “When we build something, be it a spreadsheet, a report, or a model, when it makes someone else’s job easier and more effective, that’s very satisfying.”