Skilled Workforce: Operator Competence Management towards a skilled and resilient workforce (R-13030)

Lean management promotes the idea of multi-skilled (cross-trained) operators that are able to operate different work cells, which has many positive effects, as well on system performance as on human factors. Competence levels indicate how well (in terms of efficiency and quality) operators are able to apply knowledge and skills to achieve intended results. The industrial target group of manufacturing companies, sheltered workplaces and technology and service providers confirms that competence management on the shop floor needs to be more efficient, objective and resilient to operator availability and product mix changes. However, current models and assessment methods do not adequately grasp the complex nature of operator competence (evolution), which is seen as the main technological barrier towards effective utilization of competence management solutions on the shop floor. The SkilledWorkforce_sbo project targets a competence-based decision support framework that will result in efficient and qualitative task execution on the short term while in parallel aiming for optimal competence build-up and distribution within the workforce on the longer term. The project results will be compared to a state-of-the-use benchmark scenario where competence management is 100% manual and subjective, and targets: (1) 50% less time to identify and assess competence information, (2) 15% Overall Workforce Effectiveness (OWE) increase; and (3) average operator training time reduction by 30%. An iterative approach in three steps will gradually boost the framework's decision support levels listed in increasing order of ambition: (1) Competence dashboards; (2) competence-aware training strategies and task scheduling; and (3) integrated competence management, the last one being the breakthrough goal of this project to seamlessly integrate operator learning paths in task schedules

Keywords:Competence management, dashboards, e-learning, manufacturing, training

Disciplines:Other computer engineering, information technology and mathematical engineering not elsewhere classified

Project type:Collaboration project