Introduction

In the rapidly evolving field of production management, the integration of new technologies has become essential to maintain efficiency, competitiveness, and innovation. This training program aims to introduce participants to the latest advancements in production management, from automation and artificial intelligence to data analytics and IoT. By exploring these technologies, participants will gain insights into how they can be leveraged to optimize production processes, reduce costs, and enhance product quality.

Target Audience

• Production managers and supervisors

• Manufacturing engineers and team leaders

• Supply chain and logistics professionals

• Operations managers looking to integrate advanced technologies

• Professionals in process improvement and production planning

• Anyone interested in learning about the impact of new technologies on production management

Objectives

• Understand the role of new technologies in optimizing production processes.

• Explore specific technologies, such as IoT, AI, and robotics, that transform production management.

• Learn strategies for integrating new technologies to improve efficiency and reduce production costs.

• Gain hands-on experience with data analytics tools for predictive maintenance and quality control.

• Develop a roadmap for implementing new technologies in existing production frameworks.

Outlines

Day 1:

Introduction to Emerging Technologies in Production Management

• Overview of technological advancements in production management

• Key trends: Industry 4.0, Smart Manufacturing, and Digital Transformation

• Exploring the role of automation and robotics in production

• Case studies: Successful integration of technology in production processes

• Group discussion: Identifying potential benefits and challenges

Day 2:

Internet of Things (IoT) and Data Analytics in Production

• Understanding IoT and its applications in production environments

• Real-time data collection and remote monitoring of production processes

• Introduction to data analytics and predictive maintenance

• Hands-on exercise: Setting up and analyzing IoT data for production insights

• Workshop: Developing a predictive maintenance strategy

Day 3:

Artificial Intelligence (AI) and Machine Learning in Production

• Fundamentals of AI and machine learning applications in production management

• Process optimization through AI-driven decision-making

• Quality control and defect detection using machine learning

• Case studies: AI applications in predictive quality and process improvements

• Interactive session: Identifying AI opportunities within participants' production environments

Day 4:

Advanced Automation and Robotics in Production

• Understanding the latest in robotics and automation technologies

• Exploring collaborative robots (cobots) and their role in modern production lines

• Integrating robotics for inventory, assembly, and inspection tasks

• Hands-on activity: Case simulation for robotic integration

• Group project: Designing a basic automation plan for specific production tasks

Day 5:

Implementing and Managing New Technologies in Production

• Roadmap for technology integration: Planning and budgeting considerations

• Addressing the challenges of technology adoption and change management

• Ensuring cybersecurity and data protection in technology-enabled production

• Measuring ROI and tracking the effectiveness of technology implementations

• Final workshop: Creating a personalized action plan for technology integration