How Edmund saves Amcor 190 000 Euro annualy per one factory

With Edmund AI, Amcor’s maintenance teams gain faster access to critical information, clearer troubleshooting paths, and better shift-to-shift continuity — all without changing their existing processes.

Jun 18, 2025

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The Challenge

Amcor NB operates five Allstein printing lines and ten cutting machines, where even short stoppages carry a cost of €1,200/h and €600/h respectively.
These are highly complex systems that rely on precise sequences, interlocks and parameter settings. Troubleshooting often requires navigating:

  • extensive documentation

  • historical maintenance logs

  • PLC logic and machine-specific behaviour

  • mechanical drawings, BOMs, and part databases

  • long-term institutional knowledge across shifts

Before Edmund, this information was spread across multiple systems, making it time-consuming to gather all relevant context — due to the complexity of the machines and the volume of information required to maintain them. Edmund’s role was to unify this information and make it instantly accessible.Provide instant answers to FAQs and common issues.

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The Solution: A “Digital Colleague” That Supports the Team

Edmund was deployed to complement Amcor’s existing maintenance expertise — not replace it.
It acts as a structured layer on top of existing documents, logs, manuals and historical fixes, enabling technicians to:

  • quickly access the most relevant information

  • avoid repetitive searching across multiple sources

  • validate hypotheses with data from past incidents

  • maintain consistency across shifts

  • capture know-how directly during troubleshooting

Technicians described Edmund as “another colleague on the shift”, someone who helps gather information when others may be occupied elsewhere.Track key metrics like resolution time and customer satisfaction.

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Quantified Results

Predictive Analytics

Across Allstein and cutting machines, the implementation delivered:

→ 36.75 hours of maintenance time saved per month

→ 441 hours saved per year

→ 10 hours of avoided machine downtime monthly

→ €15,900 saved per month in downtime reduction

→ €190,800 annual savings

Additional observed improvements:

  • 50% faster information search thanks to unified knowledge access

  • smoother onboarding for new team members

  • more time available for preventive and higher-value work

  • better knowledge continuity across shifts

  • fewer repeated troubleshooting cycles

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