Program Overview
This program provides a comprehensive understanding of production line automation and smart manufacturing tailored for FMCG plants. Participants will delve into Industry 4.0 technologies, their functional benefits in improving quality and efficiency, and real-world case studies of successful automation implementations. Through interactive exercises and situational problem-solving, the course equips attendees to identify opportunities, address challenges, and drive automation strategies in their manufacturing environments.
Features
- Understand the foundational concepts of Industry 4.0 technologies and their application in FMCG production.
- Evaluate the functional benefits of automation in improving quality, efficiency, and sustainability.
- Analyze real-world case studies to identify best practices in smart manufacturing.
- Develop actionable strategies to implement automation in a production environment.
Target audiences
- Manufacturing and Operations Professionals
- Process Engineers
Curriculum
- 3 Sections
- 29 Lessons
- 1 Day
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- Introduction to Industry 4.0 Technologies for FMCG Plants9
- 1.1Industry 4.0: Overview of the fourth industrial revolution and its role in modern manufacturing.
- 1.2Cyber-Physical Systems (CPS), Internet of Things (IoT), Artificial Intelligence (AI), Big Data, Cloud Computing, Smart Sensors.
- 1.3Core Components of Smart Manufacturing: Integration of automation, real-time data analysis, and advanced robotics.
- 1.4Technologies Driving Smart Manufacturing: IoT-enabled machines for real-time monitoring; AI and machine learning for predictive quality control; Robotics for assembly and packaging automation.
- 1.5Digital Twins, Predictive Maintenance, Autonomous Robots, Edge Computing.
- 1.6Discussion on the current challenges faced by FMCG plants in adopting Industry 4.0.
- 1.7Real-life scenarios where automation has transformed manufacturing efficiency and product quality.
- 1.8Interactive Exercise: Scenario 1: Identify key pain points in an FMCG plant that could benefit from Industry 4.0 adoption.
- 1.9Interactive Exercise: Scenario 2: Assess how IoT-enabled devices could address quality control challenges in a production line.
- Functional Benefits in Quality and Efficiency Improvement11
- 2.1Automation’s Role in Enhancing Quality: Reducing human error in quality control; Consistent monitoring and adjustments to maintain product quality.
- 2.2Statistical Process Control (SPC), Automated Vision Systems, Quality Management Systems (QMS).
- 2.3Efficiency Gains Through Automation: Optimized production speeds and downtime reduction; Real-time analytics for resource allocation
- 2.4Lean Manufacturing, OEE (Overall Equipment Efficiency), Just-in-Time (JIT) production.
- 2.5Cost Reduction and Waste Minimization: Energy-efficient operations and sustainable practices; Traceability of production batches for better control over raw material use.
- 2.6Understanding the risks and challenges in balancing automation with human involvement.
- 2.7Evaluating the impact of automation on the workforce and retraining needs.
- 2.8Case study: An FMCG company’s journey of automating its packaging line using AI-powered vision systems to reduce defective product rates.
- 2.9Case study: How predictive maintenance increased equipment uptime by 20% in a bottling plant.
- 2.10Interactive Exercise: Scenario 1: Participants review a sample production line and suggest improvements using automation tools.
- 2.11Interactive Exercise: Scenario 2: Breakout groups simulate a scenario where predictive maintenance could prevent a breakdown on the production line.
- Case Studies of Automation in FMCG Manufacturing9
- 3.1Successful Automation Implementations in FMCG: From traditional systems to fully automated lines
- 3.2Key areas: Packaging, sorting, quality control, and assembly; Keywords: Smart Sensors, Machine Learning Algorithms, Data-Driven Decisions.
- 3.3Challenges Faced During Implementation: Overcoming resistance to change; Initial capital investment and ROI calculation; Integration of legacy systems with modern automation.
- 3.4Challenges Faced During Implementation: Overcoming resistance to change. Initial capital investment and ROI calculation. Integration of legacy systems with modern automation.
- 3.5Exploring the scalability of automation solutions across small and large plants.
- 3.6Case study: How a leading FMCG company reduced production lead time by 30% with the adoption of robotics for material handling.
- 3.7Case study: The application of big data analytics to optimize product quality across multiple FMCG production lines globally.
- 3.8Interactive Exercise: Scenario 1: Participants collaborate to analyze a case study on automation in a chocolate production line and identify key lessons learned.
- 3.9Interactive Exercise: Scenario 2: Using simulation software, participants test automation strategies on a mock FMCG production line.
Instructor
