The Problem | Front-Line Experience

There is a good chance you’ve taken a refreshing drink from a can colored with ink from INX International. As a leading global manufacturer of ink and coating solutions for commercial, packaging, and digital print applications, you can see packaging and printed materials with their colorful ink on it everyday. As is the case with any manufacturer, INX is continuously attempting to improve the overall equipment effectiveness (OEE) of its production and empower frontline workers to make more informed decisions in real time.

To accomplish these goals, INX implemented a manufacturing execution system (MES) to capture more data from its lines, providing valuable insights into operations. However, due to the system’s complexity, access to critical data was limited to a select group of staff. As a result, INX faced challenges in fully leveraging the MES to identify the root causes of downtime and performance fluctuations, presenting opportunities for improvement in efficiency and overall productivity.

Front-line operations play a crucial role at INX, and workforce dynamics have evolved as experienced staff retire and a growing number of junior employees join the team. While this shift has brought fresh energy, it also highlights the need for enhanced training and skill development to maintain operational excellence. This trend is not unique to INX but reflects a broader shift occurring across the manufacturing industry.

“We had a very experienced workforce until about 2016 when we started seeing retirements. Our average workforce tenure was about 15 to 16 years. Now, we’re down to about 12 and that number continues to drop.”
— Chris Rodgers, Director of TPM, INX International Ink Co.

The Solution | Oden

In 2022, INX began their journey with Oden by implementing Oden’s Factory Analytics product for greater analytical insight and reporting capabilities. Within three months, Factory Analytics had 50 weekly users. INX was quickly able to categorize the reasons for 96% of downtime events, which resulted in a 71% reduction in changeover time and a 13% improvement in asset availability. 

These were already fantastic results, but there was an opportunity: all of this analysis was being done after problems (downtime) had arisen, and the business was still reactive rather than proactive. INX identified that they needed to enact more improvements directly at the frontline and empower operators to increase performance without long feedback loops.

In 2024 INX made a pivotal addition: Process AI, Oden’s AI-enabled solution that provides process optimization recommendations to frontline operators in real time. With it, INX enabled:

Process Optimization Recommendations
Optimal process settings are generated automatically for every run based on current conditions, and provided to the operator in an easy-to-use interface. This allows INX’s operators to adjust their process in real time to maximize performance, reduce costs, and improve quality, depending on their goals.

Predicted Quality Outcomes
To ensure real-time recommendations are producing in-spec quality, historical data is leveraged to generate predictive quality models. These models allow tradeoffs to be made in real time; INX’s operators now have the confidence to make the recommended process changes as they can see the holistic impact they will have across performance, cost, and quality.

Predicted Quantified Results
Predicted cost savings, increased output, and other outcomes help INX’s operators and others on the front line understand how implementing recommendations will help them reach their goals and incentivize their actions.

“Our customers always say that being a front line operator is more of an art than a science. We used to think we should try to infuse some science into the equation to help the operators. But we’ve realized it’s better to make it easier for operators to become artists.”
— Willem Sunblad, Co-Founder & CEO, Oden Technologies

Results | High-Achieving Operators

Over the two years with Oden’s products, INX achieved a +21.4% increase in OEE, including a 11% increase to availability from Factory Analytics and a 20.4% increase in performance from Process AI.

INX was able to achieve a significant increase in production speed while maintaining quality and cost. INX was able to move from a 24/7 to a 24/5 schedule and reduce their costs by 4 FTEs, as these increased production speeds mean that their total capacity increased by over 4.7M lbs in that period.