COURSE OVERVIEW

AI-Driven Manufacturing Transformation is a practical executive workshop designed to help manufacturing organizations understand how artificial intelligence, digital manufacturing technologies, and integrated production systems can improve operational performance, reduce inefficiencies, and accelerate smart factory transformation.

The workshop combines modern manufacturing concepts with practical business examples and demonstrates how AI-driven analytics, MES systems, predictive technologies, digital traceability, automated quality control, Lean optimization, and advanced planning can collectively create measurable operational value.

Participants learn how to move beyond isolated process improvements toward a connected, data-driven production environment where real-time visibility, intelligent analysis, and continuous improvement become part of everyday operations.

The program includes practical discussions, industry examples, and guided exercises that help organizations identify production bottlenecks, digitalization opportunities, and achievable pilot initiatives aligned with business priorities.

PROGRAM HIGHLIGHTS

• Introduction to AI-driven manufacturing and smart factory principles
• Real-time production visibility and integrated operational intelligence
• AI-supported Lean analysis and production optimization
• Predictive maintenance and condition-based operational strategies
• Digital traceability, quality automation, and connected manufacturing systems
• Integration of ERP, MES, SCADA, QMS, and production analytics platforms
• Business-focused approach to ROI, operational efficiency, and transformation planning
• Development of a structured 90-day pilot roadmap

AUDIENCE PROFILE

This workshop is designed for professionals involved in manufacturing operations, digital transformation, industrial IT, and operational excellence, including:

• C-level executives and plant managers
• Manufacturing and operations managers
• IT managers and industrial IT specialists
• Production engineers and process improvement teams
• Lean and continuous improvement professionals
• Digital transformation leaders
• MES/ERP project stakeholders
• Smart factory and Industry 4.0 teams

COURSE OBJECTIVES

Participants will learn to:

• Understand core principles of AI-driven manufacturing transformation
• Identify production inefficiencies using real-time operational data
• Apply AI-supported analysis to Lean manufacturing and continuous improvement initiatives
• Improve visibility, traceability, and production control through connected systems
• Understand predictive approaches for maintenance and operational reliability
• Connect manufacturing technologies with measurable business outcomes
• Identify high-impact digitalization opportunities in their own environment
• Structure a practical 90-day smart factory pilot initiative

COURSE DETAILS

Module 1: Foundations of Digital Manufacturing

• Introduction to modern digital manufacturing principles.
• Why companies shift from traditional to data‑driven operations.
• Role of technology providers such as Tom PIT in industrial digitalization.

Module 2: Real‑Time Insight, Automation & Connected Processes

• How real‑time data improves transparency, stability, and decision‑making.
• Digital traceability and automated quality processes.
• Integrating IT/OT systems (ERP–MES–SCADA–QMS) for operational consistency.

Module 3: Predictive Approaches, Advanced Planning & Value Creation

• Predictive and condition‑based approaches for reliability and efficiency.
• Digital planning and scheduling aligned with real‑time constraints.
• Linking technology to business value: ROI, benefits, risks.

Module 4: AI-Based Production Analysis (Lean & Continuous Improvement)

• Using AI for production performance analysis (OEE, bottlenecks, waste detection).
• Lean manufacturing principles supported by data (Muda, bottleneck identification, flow optimization).
• AI-driven root cause analysis (why downtime, defects, inefficiencies occur).
• Pattern recognition in production data (recurring losses, micro-stoppages, variability).
• Prioritization of improvement actions based on impact and effort (AI-assisted Kaizen).
• Turning raw production data into continuous improvement cycles.

Outcome: Participants understand how AI enhances Lean thinking from reactive analysis to continuous, data-driven optimization.

Module 5: Roadmap & 90‑Day Pilot Planning

• Identifying high‑impact opportunities in participants’ environments.
• Structuring a realistic, achievable 90‑day pilot roadmap.
• How to build long‑term transformation momentum after the pilot.

Participants should have:

• General understanding of manufacturing processes and operational workflows
• Basic familiarity with production KPIs such as productivity, quality, downtime, and cycle time
• Awareness of enterprise manufacturing systems (ERP, MES, SCADA, QMS)
• No advanced AI or programming knowledge required

Not available.

Rober Orehek

About

Robert Orehek is an expert in the digital transformation of business and manufacturing processes, with a strong focus on the practical use of modern information technologies in industrial environments. As CBDO at Tom PIT d.o.o., he works on the development and implementation of end-to-end digital solutions that help companies increase efficiency, transparency, and adaptability.

His professional focus is on process optimization, data integration, and the meaningful application of advanced technologies, including artificial intelligence, to support decision-making and improve production systems. In his lectures, he combines a strategic perspective with hands-on experience, showing how digitalization and AI can be applied realistically and effectively in manufacturing—not as buzzwords, but as concrete tools for measurable improvement.