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Robotics Process Automation for Smart Manufacturing

This course provides a comprehensive introduction to Robotics Process Automation (RPA) within the realm of smart manufacturing. Learners explore RPA's concepts, integration with manufacturing, and impact on production efficiency and quality.

Camila Rossi
Camila Rossi
Electrical Engineering | core | 4 hours |   Published: Jul 2024
In partnership with: Coursera

Overview

1KSTUDENTS*
94.9%RECOMMEND*

This course includes:

  • 4 hours of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

This course provides a comprehensive introduction to Robotics Process Automation (RPA) within the realm of smart manufacturing. Learners will explore the foundational concepts of RPA, how it integrates with manufacturing systems, and the transformative impact it has on production efficiency and quality control. The course context involves examining case studies where RPA has been successfully implemented, understanding the challenges faced, and learning the key strategies for effective deployment. 

Skills You Will Gain

Industrial Automation
Production Efficiency
Quality Control
Robotics Process Automation
Smart Manufacturing

Learning Outcomes (At the end of this program you will be able to)

  • Define the key components of RPA in manufacturing. 
  • Describe the integration of RPA with existing manufacturing systems. 
  • Analyze case studies to identify effective RPA strategies. 
  • Evaluate the impact of RPA on production efficiency and quality control. 

Prerequisites

Basic understanding of manufacturing processes, familiarity with industrial automation concepts, introductory knowledge of programming logic, and awareness of quality control principles.

 

 

 

Who Should Attend

Manufacturing Engineers, Process Designers, Automation Technologists, Production Managers, Quality Assurance Specialists  

Curriculum

1Module 1.1: Understanding RPA in the Manufacturing Sector

Segment 01 - Introduction and Welcome

Segment 02 - Fundamentals

Segment 03 - RPA and Manufacturing Systems

Segment 04 - Case Studies of RPA in Industry

2Module 1.2: RPA Deployment and Integration Strategies

Segment 05 - Designing RPA for Manufacturing Processes

Segment 06 - Overcoming Integration Challenges

Segment 07 - RPA and Continuous Improvement

3Module 1.3: Measuring the Impact of RPA

Segment 08 - KPIs for RPA Implementation

Segment 09 Calculation of RPA Implementation KPIs

Segment 10 - Real cases and the impact of RPA implementation

4Module 2.1: How to develop RPA bots

Segment 11 - Introduction to Module 2

Segment 12 - Low Code, No Code and Code

Segment 13 - RPA Tools

Segment 14 - Our RPA Choice for Practicing

5Module 2.2: Setting Up Your UiPath Environment

Segment 15 - Installing UiPath Studio

Segment 16 - Navigating the UiPath Studio Menu

Segment 17 - Navigating the UiPath Studio Process Interface

6Module 2.3: Basics of Building an Assisted RPA Bot

Segment 18 - Introduction to UiPath activities, sequences and flowcharts

Segment 19 - Hello World

Segment 20 - Assisted Bot with UiPath

7Module 3.1: Developing Unassisted RPA Solutions with UiPath

Segment 21 - Introduction to Module 3

Segment 22 - Creating a basic unattended bot for data processing

Segment 23 - Utilizing UiPath activities for backend operations

Segment 24 - Testing the bot in a non-interactive environment

8Module 3.2: Automation Complex Processes

Segment 25 - Integrating Different Data Sources and Applications

Segment 26 - Using UiPath-s Recording Feature for Complex Task Automation

Segment 27 - Implementing Logic and Decision Making

9Module 3.3: Publishing and managing a bot

Segment 28 - Overview of UiPath Orchestrator and Its Role in RPA

Segment 29 - Navigating the Orchestrator Dashboard

Segment 30 - How other RPA tools manage their bots

10Module 4.1: Integrating RPA with IoT and Industry 4.0

Segment 31 - Introduction to Module 4

Segment 32 - The Synergy of RPA and IoT

Segment 33 RPA in Smart Factory Ecosystems

Segment 34 - Case Study IoT-Enhanced RPA Transformations

11Module 4.2: Scaling RPA for Large-Scale Manufacturing

Segment 35 - Strategies for RPA Scalability

Segment 36 - Managing RPA at Scale

Segment 37 - Case Study Scaling RPA in Automotive Manufacturing

12Module 4.3: Future Trends and RPA's Evolving Role

Segment 38 - Next-Gen RPA in Manufacturing-

Segment 39 - RPA and AI- The Frontier of Manufacturing-

Segment 40 - Case Study- Pioneering RPA in Advanced Manufacturing-

Segment 41 - Wrap-up & Key takeaways

Instructors

Camila Rossi

Camila Rossi

With a passion for pioneering ventures in artificial intelligence (AI) and its multifaceted applications across diverse sectors like education, health, politics, and entertainment, I've dedicated over three years to spearheading groundbreaking initiatives. My journey as a trailblazer extends beyond mere innovation; it's about crafting solutions that not only harness the power of AI, chatbots, and non-fungible tokens (NFTs) but also profoundly impact learning outcomes and engagement within the edtech landscape. Through my role, I aim to redefine the educational experience by integrating cutting-edge technologies that inspire curiosity, foster critical thinking, and empower learners to navigate the complexities of the digital age. As an educator, my commitment extends beyond technological advancements. I'm driven by a deep-seated desire to impart knowledge and insights on AI and Industry 4.0 technologies. My experience as a professor goes beyond conventional teaching; it's about equipping managers and executives with the tools and strategies necessary to navigate the ever-evolving landscape of Industry 4.0. By bridging the gap between theory and practical application, I strive to empower professionals to optimize business processes and drive performance while upholding ethical standards and promoting social well-being, diversity, and equity. In addition to my academic endeavors, I actively engage in collaborative initiatives aimed at fostering dialogue on the ethical implications of AI advancement. As a member of GA.IA - Grupo de Análise Integrada de IA, I contribute to high-level discussions that transcend conventional boundaries, addressing the ethical complexities and challenges inherent in the evolution of AI. Through my involvement, I seek to facilitate a deep and continuous dialogue that navigates the ethical nuances of AI, ensuring that as we embrace the possibilities of this technology, we do so with a steadfast commitment to ethical principles and societal well-being.
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