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Artificial intelligence (AI) has the potential to have a profound impact on modern industrial processes. In this post-graduate course, students will review how AI algorithms work and then explore the current capabilities, risks, applications, evolution, and ethics of AI in advanced manufacturing and mechatronics. Having identified an opportunity to use AI at their workplace, students will conduct cost-benefit analyses to enable informed decision-making for AI investments. Students will examine strategies for monitoring the integrity of AI solutions. Finally, students will identify factors used to evaluate the success of implementing an AI solution, including cost, quality, delivery, and performance metrics.
The interconnected and digitized nature of Industry 4.0 delivers numerous benefits to manufacturing organizations, but also introduces cybersecurity challenges. In this post-graduate course, students will learn to identify cybersecurity threats, and vulnerabilities throughout the manufacturing environment. Students will illustrate why cybersecurity challenges must be addressed and then follow a standard-based systematic approach to tackle them. Students will learn the importance of continuous attention to cybersecurity to stay ahead of evolving threats and vulnerabilities, and how to build this ongoing attention to cybersecurity into their organizations. The course enables students to communicate effectively with stakeholders about cybersecurity.
Business Intelligence (BI) refers to the technologies, processes, and strategies that organizations use to collect, analyze, and transform raw data into actionable insights for making informed business decisions. In this course, students will examine a wide range of BI activities, including data collection, data analysis, data visualization, reporting, and monitoring. Students will assemble information and generate insights for decision-makers that can guide strategic and operational decisions. This course is designed for professionals at the management level who are seeking to enhance their decision-making capabilities with data-driven insights.
Industry 4.0 mechatronic systems can improve speed, lower expenses, and reduce waste in factory manufacturing tasks and processes. In this course, students will be introduced to mechatronic systems used in common manufacturing environments. Students will investigate inefficient manufacturing processes and identify Industry 4.0 mechatronics solutions to help improve these inefficiencies. Students will write a technical report including a cost-benefit analysis and justify the implementation of a proposed mechatronics system solution in a mock presentation to stakeholders. Finally, students will examine the roles and qualifications of personnel needed to design, deploy, maintain, and repair a mechatronic system.
In this post-graduate course, students will advance their ability to communicate accessibly and inclusively throughout organizational change in the manufacturing industry. Students will practice leading and communicating about change throughout its lifecycle, from proposing the change, to supporting an organization during change, through to evaluating the success of the change. Students will learn strategies to create psychological safety within their teams and with stakeholders through open communication, inclusive practices, clear processes, and collaboration. The skills students learn in this course will support their role in organizational growth and innovation.
In this culminating course, students will be challenged to apply their knowledge and skills of advanced manufacturing technology in a real-world application. Working closely with an industry partner and their course instructor, students will identify an actual business need, write a technical report containing a cost-benefit analysis, and pitch their solutions to company decision makers. Upon approval, students will manage a team of specialists through one or more phases of the implementation and lead the change throughout the organization introduced by the innovation. Finally, students will evaluate the impact of the solution on the organization.
Is a robot the solution to automating your manufacturing process? Building on their knowledge and experience in advanced manufacturing and mechatronics, students in this course will review the types of robotic systems available and learn to identify inefficient processes and “dirty, dull, or dangerous” tasks. Students will examine key performance indicators and investigate the requirements and constraints that inform a robotic systems solution. They will learn how to organize a team of specialists and tradespeople to design, install, commission, and deploy a robotic system. Finally, students will explore strategies for predictive maintenance and continuous improvement of the manufacturing process.
Automation helps manufacturing companies remain competitive by reducing manufacturing costs, delivering products on time, and increasing product quality. In this post-graduate course, students will examine common automation components including programmable logic controls (PLCs), input/output (I/O) cards, analog-to-digital converters, solenoid valves, switches, motors, and sensors. Students will compare data collected using bar codes, radio frequency identification (RFID), and vision systems and identify data that determines overall equipment effectiveness (OEE). Students will investigate if a current product or process is suitable for automation and analyze risks and return on investment. Finally, students will draft a roadmap to implement automation in stages.
Companies that manufacture products using traditional methods and materials are finding opportunities to use composite materials in their product design and development process. In this post-graduate course, students will survey products suitable and unsuitable for composites. Students will explore the advantages and disadvantages of various composite materials, processes, and technologies and review regulatory requirements, specifications, and qualifications for composite products. After identifying feasible uses for composites in their workplace, students will design, prepare tooling, and lay up a prototype composite part. Recounting this hands-on experience, students will examine composite manufacturing process flow in order to reduce waste, save time, and optimize productivity.
In this post-graduate course, students will investigate additive manufacturing (AM) to improve cost, quality, delivery, and performance within organizations. Students will be faced with design challenges in order to gain experience solving problems using AM. The students will find pain points within their organizations that could be solved using AM, analyze the factors and risks, perform a cost-benefit analysis, and create a proposal to ensure that organizational leaders can make informed investment decisions. Students will itemize the key components of technology adoption, data management, and operational plans, so that AM can be successfully implemented and sustained.
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Recognition of Prior Learning (RPL) is a process which documents and compares an individual's prior learning gained from prior education, work and life experiences and personal study to the learning outcomes in College courses/programs. For more information, please visit www.rrc.ca/rpl.