In their bottleneck processes, INX found that the experience level of the operator greatly affected machine uptime and throughput. Due to the current labor shortage, it was challenging to consistently staff highly experienced operators. They needed to make operational excellence easier for even their new operators. INX wanted to use data to empower their staff, but there were obstacles in getting the right information to the people who needed it.
INX knew that there were operational insights locked in their production data. By the end of 2022, 3 years had passed since INX had first implemented their MES. However, only a couple of people in their organization knew how to use the data they were capturing with the MES.
When using only their MES, visibility to data was delayed and finding the root cause of issues was difficult. For example, while there was some capability to categorize downtime using the MES, contextual information wasn’t captured automatically. When downtime occurred and operators worked to bring machines back up, it was challenging for them to also accurately maintain a record of cause and context for the downtime event. Ultimately, production information such as a downtime event was very delayed, inaccurate, and difficult to interpret for most team members. Although they tried, INX couldn’t truly make use of their MES data.
Seeing opportunity to drive operational efficiency, they chose to partner with Oden to transform their data strategy and to make excellence easier for all operators.
INX partnered with Oden to create a clear mission, vision, and goal for the project. The core of the partnership was to improve throughput and uptime by using Oden to enable data-driven decision making via descriptive and predictive analytics.
Oden’s Customer Success Manager met in daily huddles with the INX team to encourage rapid adoption and streamline the deployment process. Once deployed, Oden revolutionized how their data could be used. Now, the descriptive information of what is happening on the plant floor could automatically be made actionable with contextual information such as why and in what way these events occurred.
Oden’s solution created a closed loop continuous improvement process in real time. Operators saw the value of how information like downtime categorization was used by supervisors, maintenance, scheduling, and engineering teams to address their biggest issues more effectively. Operators were incentivized to actively participate in the data strategy of the organization.
The data affects everyone who draws a paycheck from the organization.
INX International Ink
Within 90 days of starting with Oden, INX had connected their contracted lines at the pilot site and driven adoption with 50 weekly users of Oden’s solution. Within their first months of use, INX was quickly able to categorize the reasons for 96% of downtime events at the pilot location. This information was updated in real time, accurate, and was easy for everyone to access. This brought clarity on how to find the biggest opportunities for improvement.
By day 180, asset availability was improved by 13% and changeovers were shortened by 71%. This amounted to over 2X ROI within the first 6 months.
Looking forward, INX expects these results to continue as Oden has been integrated into their daily operations. INX’s next steps with Oden include deployment of predictive quality tuned to their specific product / line combinations.
Oden will give me as a supervisor instant feedback on how the mills are performing.
INX International Ink
Make success easier for your operators with Oden.
About Oden Technologies
Oden is the fastest and least resource intensive way for manufacturers to get the analytics and guided insights their team needs to be problem solvers. Our software unifies siloed machine, production data, and prebuilt machine learning applications to provide real-time insight and context. Teams are enabled to make faster, more proactive decisions, and reduce firefighting. Our customers have deployed in 42 days, and have achieved 5x ROI in 12 months.