A Case Study on Enhanced Predictive Maintenance in the Paper and Pulp Industry
A Set of Challenges
The paper and pulp giant faced daunting challenges due to its dependence on motor-driven rollers critical to its manufacturing processes. The traditional maintenance approaches, reliant on manual inspections and subjective assessments, were no longer sufficient. These methods led to variability in maintenance effectiveness, influenced by the diverse experience and expertise of the personnel, resulting in unexpected equipment stoppages and significant production downtime.
Implementation
The deployment of ADI OtoSense involved several key phases:
Real-Time Alerts
Optimize Maintenance Schedules
Improve Allocation of Maintenance Resources
Conclusion
The collaboration between the paper and pulp manufacturing giant and its strategic technology partner showcases the transformative impact of predictive maintenance powered by ADI OtoSense. This case study highlights how cutting-edge AI and sensor technology can revolutionize traditional industrial maintenance practices, setting a new standard for operational excellence in the paper and pulp industry.
Future Outlook
Buoyed by the success of this initiative, the company is poised to further leverage predictive analytics across its operations, aiming to sustain its leadership in operational efficiency and sustainability. The industry-wide implications of this successful partnership underscore the potential for predictive maintenance technologies to redefine manufacturing standards across the paper and pulp sector.
Success Stories
Trusted by Experts
Explore transformative success stories from across industries. Witness how businesses have leveraged ADI Otosense to achieve remarkable efficiency gains, reduce downtime, and enhance decision-making, inspiring you to explore the possibilities within your own operations.
"Our collaboration with ADI Otosense on the Smart Factory NISSEI project is pivotal for our digital transformation, enhancing safety and efficiency."
Yoshihiro Murakami
Manager Presto Production Division
"Although the site had detected signs of abnormality due to increased vibration, it was difficult to determine whether the operation should be stopped immediately or wait until the next maintenance, given that the cause of the abnormality was not yet clear. SMS gave us insights into deciding the next action to prevent unplanned downtime."
Shota Akatsuka
Advanced Info Tech Center
"One of the major benefits of this sensor is that you don’t have to set alarm levels. This solution is self-learning. So, you don’t waste time on false positives, and you don’t have to deal with false negatives."
Joris Bracke
Directeur, Bracke EB Groep
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