• EP 6 — Otis's Jolly Ehiabhi on Driving Smart Factory Success Through People-First Digital Transformation

  • Jan 16 2025
  • Length: 44 mins
  • Podcast

EP 6 — Otis's Jolly Ehiabhi on Driving Smart Factory Success Through People-First Digital Transformation

  • Summary

  • In this episode of Manufacturing Intelligence, Jennifer, and Andrew sit down with Jolly Ehiabhi, Smart Factory System and Process Manager, at Otis, who shares his remarkable journey from agricultural engineering in Lagos to spearheading Industry 4.0 initiatives. Jolly's unique approach combines deep technical expertise with a strong focus on people and team building, making him a standout leader in manufacturing transformation.

    He offers valuable insights on implementing real-time monitoring solutions, navigating legacy system integration, and building effective cross-functional teams. The conversation also explores practical strategies for digital transformation success, Jolly’s predictions for the future of AI in manufacturing, and the exciting potential of predictive maintenance and digital twins.

    Topics discussed:

    • Implementing successful real-time monitoring solutions through careful stakeholder engagement and cross-functional team building strategies.
    • Integrating legacy systems and new technologies, including practical approaches to machine connectivity and data collection.
    • The role of predictive maintenance in reducing costly downtime and improving manufacturing efficiency through data-driven insights.
    • Developing and implementing digital twin technology for improved factory visualization and operational planning.
    • The importance of balancing technical innovation with people-first leadership approaches in manufacturing transformation.
    • Practical implementation of Industry 4.0 initiatives, including shop floor visualization and real-time monitoring systems.
    • The evolution of manufacturing analytics from spreadsheets to advanced visualization tools and predictive capabilities.
    • Future opportunities in manufacturing intelligence, including AI implementation and the potential for increased operational efficiency.

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