- What is the economic context surrounding education and training programs in AM?
- Are there enough quality AM education and training programs available to provide workers with the necessary skills to work with robots?
- What is the quality of programs that are currently available, and are they effective?
- Should existing AM programs be updated? If so, in what ways?
- What are promising practices for AM education and training programs?
In many factories today, robots are already working alongside human workers and have been doing so for some time. Analysts anticipate that this trend is likely to grow as industrial robots become increasingly sophisticated and advanced. At the same time, there likely will be a shortage of human workers who hold the necessary technical and nontechnical skills to work with, program, and repair their machine counterparts. Given this reality, it is critical that new workers and those who are in the process of retraining have access to effective and affordable training programs. But do we have enough quality programs to serve this need? And what factors constitute a "quality program"?
The RAND Corporation was asked to assess the state and future of education and training in advanced manufacturing (AM) using robotics, with a special focus on the U.S. Midwest region and the state of Pennsylvania — areas that currently are and historically have been hubs of manufacturing and provide important test cases for answering questions about the availability and content of AM training programs. The research team examines the economic context in which education, training, and workforce development programs currently operate and potentially will operate in the near future; reviews available programs and evaluates their curricular content and instructional practices and technologies; and reviews promising educational practices in these areas. The team also offers recommendations for stakeholders to consider as they work to meet the needs of the future AM workforce.
General research on certain educational practices points the way forward in shaping new AM programs and strengthening those that exist
- There is a critical need for better and more-integrated workforce data systems that support data-driven policies for building a better AM workforce. This need can only be addressed by all stakeholders, including employers.
- A weak or absent policy response to the transition to AM with robotics in the short to medium term might aggravate negative impacts for less educated and vulnerable workers or fail to draw the large, skilled workforce needed by employers.
- The number of AM-related education and training programs is growing, but, based on newly available data, many programs do not offer field-based experience, industry-based credentials, or an emphasis on nontechnical "21st-century" skills (e.g., problem-solving and dependability and reliability).
- Based on the available research evidence and federal guidelines for determining quality research evidence, education and training programs in AM using robotics should focus on industry-based credentials, apprenticeships, and student wraparound support services. Program providers should continue to experiment with the exact format of these practices, while conducting rigorous evaluations of them.
- Collect quality data from all stakeholders for a robust, data-driven workforce development system.
- Assess in detail the need for a skilled AM with robotics workforce, to plan for and promote AM jobs accordingly for national and subnational labor markets.
- Emphasize nontechnical 21st-century skills more in education and training programs.
- Bring intermediary organizations to the education and training table more to bring small to medium-sized manufacturers to the table more, too.
- Conduct more-rigorous research on promising practices in education and training in AM and other critical industries for a wide variety of students.
The research described in this report was prepared for the Advanced Robotics for Manufacturing Institute (ARM) and conducted by RAND Education and Labor.
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