Fast scheduling of human-robot teams collaboration on synchronised production-logistics tasks in aircraft assembly

The deployment of human-robot teams (HRTs) promises to realise the potential of each team member regarding their distinct abilities and combines efficiency and flexibility in manufacturing operations. However, enabling effective coordination amongst collaborative tasks performed by humans and robots while ensuring safety and satisfying specific constraints is challenging. Motivated by real-world applications that Boeing and Airbus adopt HRTs in manufacturing operations, this paper investigates the allocating and coordinating of HRTs to support safe and efficient human-robot collaboration on synchronised production-logistics tasks in aircraft assembly. We connect the operations research and robotics communities by formulating the problem with precedence constraints, spatial constraints, temporal constraints, and synchronisation constraints that fits within the classic multi-robot task allocation (MRTA) category into a flexible job shop scheduling problem. Two exact approaches, including mixed-integer linear programming (MILP) and constraint programming (CP), are proposed to formulate and solve this problem. A benchmark set with 80 instances (e.g., small/medium-scale and large-scale instances) that corresponds to real dimensions of industrial problems with production tasks, subtasks, locations, deadlines, human worker eligibility and capacity, robot eligibility and capacity, material handling system capacity, and travel times is developed. Experimental evaluation with a total of 1200 independent tests on the benchmark set shows the superiority of the CP approach comparing the MILP approach for efficiently solving real-life scheduling problems of HRTs collaboration on synchronised production-logistics tasks in aircraft assembly.