On-Demand-Webinar

Combine real and digital operations to understand, predict and optimize CPG plant performance

Test CPG production scenarios, predict operational impact and improve asset utilization before changes go live.

Geschätzte Wiedergabezeit: 28 Minuten

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Automated CPG production line with a robotic arm moving cans along a conveyor

Rising costs, SKU complexity, sustainability expectations and labor challenges are making CPG production harder to plan and predict. Manufacturing leaders need better ways to evaluate decisions before they affect live output, resources or capital assets.

In this on-demand webinar, Siemens experts discuss how Optimize My Plant brings predictive digital twin capabilities into production design and operations. The conversation focuses on how CPG manufacturers can move from gut feel to data-driven decision-making by using a practical framework: understand, predict and optimize.

The webinar addresses a key question for CPG manufacturing leaders:

How can manufacturers keep production design and operations agile while improving capital asset performance, scale and utilization?

Watch the webinar for a discussion of:

  • The cost, SKU complexity, sustainability and labor pressures shaping CPG manufacturing
  • How Optimize My Plant supports the Siemens approach to understand, predict and optimize
  • How simulation models can connect with production data to support shop floor decision-making
  • Demonstrated use cases for new product introduction, maintenance planning and production schedule validation
  • Customer examples from chocolate manufacturing, cheese manufacturing and cosmetics production

The webinar highlights improvement opportunities including efficiency improvements up to 25%, production cost reductions up to 20% and reduced unscheduled downtime up to 30%.

Vorstellung des Referenten

Siemens Digital Industries Software

Kevin Hoorne

Industry Manager für CPG mit Schwerpunkt Produktentwicklungslösungen

Kevin Hoorne ist seit neun Jahren in der Lebensmittelindustrie tätig. Seine frühere Erfahrung umfasst sechs Jahre in einem Schokoladenverarbeitungsunternehmen und drei Jahre in einer Verpackungs- und Produktionsanlage für Molkereien/Käse.

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