Co-designed training for factory of the future jobs
In manufacturing, digital technologies such as the internet of things, artificial intelligence, cloud/edge computing, virtual reality and collaborative robots are advancing smart automation. For many companies this means not only urgently adapting processes, but also retraining workforces. The EU-supported FIT4FoF project has developed a training framework for the manufacturing sector, co-designed with the workers themselves. “The data that we amassed on industry 4.0 technology trends, alongside the associated skills requirement, enabled us to develop an upskilling analysis tool which identifies which skills would help workers adopt new technologies,” says Jacqueline Kehoe, project coordinator, from Munster Technological University, the project host. A number of research papers have already been published.
Fit for factories of the future
Several surveys and reports have highlighted a significant need for upskilling of the global workforce. One report by the management consultancy McKinsey estimated that “Seventy-five million to 375 million may need to switch occupational categories and learn new skills.” According to Kehoe, “Paulo Leitão from the Polytechnic Institute of Bragança has talked about the fact that for factories of the future, many jobs currently in demand such as big data analyst and cloud services specialist didn’t exist 15 years ago, before industry 4.0.” Through a survey, desk research and workshops with industry and academic experts, FIT4FoF first determined what technological trends were most impacting manufacturing, to then identify the skills required. This allowed the team to create their training framework, co-designed with workers. Additionally, key stakeholders representing different business functions (such as HR or finance), alongside a worker representative who understands the shopfloor and an educator providing specific technology expertise, input into the final design. The project conducted pilots of the training framework in organisations of different size and type covering: automotive advance manufacturing in Spain, smart products and manufacturing in Italy, a medical devices smart factory in Ireland and smart manufacturing of appliances in Romania. Each pilot used the framework to design and deliver training tailored to its specific organisation, assessing issues such as: upskilling drivers (such as increasing productivity or reducing costs), how best to determine skills needs, as well as training design and ultimately delivery. “We are currently comparing the impact of our training to more traditional methods, which don’t seek participant input,” adds Kehoe. FIT4FoF also launched a community of practice for each pilot, to facilitate exchanges between shopfloors and business participants, for a better understanding of each other’s work roles. “The training framework is a fantastic achievement, allowing stakeholders to gather, in person or online, and design a training programme in hours,” says Kehoe. “Involving workers in its design exceeded employer expectations. Feedback about the results of the framework has been very positive, with all pilot partners indicating they will continue using it.”
A collective responsibility
While younger workers have grown up as digital natives, a significant section of the workforce needs to be upskilled in the use of the latest technologies. Kehoe calls for policymakers to increase awareness and knowledge about the benefits of digitalisation, as well employers to increase staff engagement in managing their own skills development. This, Kehoe suggests, can be supplemented with support for the sharing of industry best practice training initiatives, especially shorter and modular versions. Towards this end, the project partners are currently working to further expand the framework to incorporate more skills, as well as expanding it for the design of micro-credentials.
Keywords
FIT4FoF, skills, factories, industry 4.0, artificial intelligence, edge computing, cloud, training, robots, virtual reality, digitalisation
