A multi-skill RCPSP variant for persons with disabilities in sheltered workshops

Sheltered workshops face the challenge of meeting their manufacturing objectives while considering the individual competencies and assistance needs of persons with disabilities. Moreover, work processes in sheltered workshops are weakly structured, allowing for frequent task interruptions and changes based on the preferences of impaired work persons. While the Industry 4.0 literature provides many real-time scheduling algorithms for incorporating multiple objectives and constraints, these algorithms fall short of the characteristics of sheltered workshops. The resource-constrained project scheduling problem (RCPSP) is an optimization problem for computing manufacturing plans considering multiple objectives and resource constraints. Among many different RCPSP variants proposed in the literature, the multi-skill RCPSP (MSRCPSP) variant considers the individual skills of work persons when generating manufacturing plans. With the ongoing digital transformation of enterprises, new assistance systems enter the market, providing individual support to impaired work persons and compensating for lacking skills and abilities. This paper proposes an MSRCPSP variant that incorporates assistance systems and learning tasks compensating for competence gaps in the skill matrix of impaired work persons. Furthermore, it decomposes tasks into individual work objects, which accounts for frequent task interruptions and task preferences of work persons. The algorithm is described and demonstrated using a manufacturing data set from an actual sheltered workshop. In a small evaluation study, the algorithm is tested by scheduling two impaired work persons in the assembly department of a medium-sized manufacturing company in the primary labor market. The evaluation study proves its real-world applicability and the suitability of scheduling algorithms for participation and inclusive work.