Decision support tool for dynamic workforce scheduling in manufacturing environments \
Author(s)Malik, Radhika, M. Eng. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Mary L. Cummings.
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Scheduling for production in manufacturing environments requires an immense amount of planning. A large number of factors such as part availability, production cost, space constraints and labor supply must be taken into account. Considering these factors, tasks are scheduled into shifts and allocated the required human resources. However, when actual production begins, the original schedule must be updated regularly due to the dynamic nature of the environment. An enormous challenge in these rapidly changing environments is the reallocation of workers to tasks in real-time due to events such as worker absences, emergent tasks and unanticipated delays. The focus of this thesis is the development of a decision support tool that can assist shift supervisors to rapidly generate new worker-task assignments during a shift to ensure that production stays on track. This research discusses the systems engineering development process of the aforementioned decision support tool including the initial planning and analysis, the interface design, and the resource allocation algorithm. The development process was iterative, with evaluations and feedback at every step facilitating the refinement of the tool. Emphasis was laid on creating a collaborative framework between the human operator and the automated planning algorithm. While automated planning algorithms are a critical component of resource allocation systems since they can solve complex multivariate scheduling problems much faster than humans, they are inherently brittle and unable to respond to uncertainties in dynamic environments. Thus, in this system, the human operator is given high-level planning tasks and the ability to set goals, while the automation handles the creation of the detailed planning and scheduling assignments. Another factor that was stressed was the inclusion of ergonomic risk. Worker-task assignments that do not take into account ergonomic risk exposure can lead to repetitive stress injuries over time, causing manufacturing plants to incur substantial medical expenses. Any system that allocates (or re-allocates) workers to tasks must take into account the ergonomic risk that workers are subjected to due to the tasks they perform in the given shift. The system was evaluated through extensive interactions with individuals from an aircraft production line, including senior level management and representative users from the production floor. The evaluations yielded positive results. Both the management and the representative users were able to identify the applicability of the tool immediately, and all individuals agreed that the system could be very useful in real production environments. The shift supervisors from the shop floor affirmed that the tool captured all major pieces of information they consider while making re-planning decisions. To better assess the potential of the tool and to refine it further, future research should initiate pilot studies to compare the proposed tool with current methods used for decision-making, which are paper schedules and best judgment of human operators.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 113-116).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.