9732868 Hopp This grant focuses on development of a theoretically founded framework for the design and implementation of effective production policies for workers in agile workforce systems. Such systems include a wide range of organizations that utilize cross-trained workers and possibly dynamic task assignment/job-processing to respond to changes in system workload. The scope of our research includes: (1) constructing a detailed classification scheme for manufacturing and service environments that identifies key characteristics germane to the selection of a workforce policy, and (2) creating and analyzing a series of models with which to predict the performance of various policies in various environments and thereby gain insight into the factors that determine their efficacy. The primary focus of the research will be on logistical efficiency (e.g., maximizing performance in terms of throughput, flowtime, or work-in-process for a given workforce size). Because this research will be carried out in close collaboration with several industrial practitioners, real world considerations such as motivational effects, human factors, and managerial complexity will be addressed as well. The models and classification scheme developed through this research will provide benefits that include: (1) managerial insights into why and where agility in the workforce is effective, (2) a set of useful analytical models (performance predictors, quantification of opportunity, and near-optimal policies/organization schemes) to assist engineers in the analysis/design of agile work systems, and (3) extension of the queueing and systems modeling technology base to include classes of systems where machines and labor interact in new ways for productivity improvement. Technology transfer will occur through practitioner and research oriented publications, direct contact with industrial sponsors, and teaching efforts to instill well-founded principles of workforce agility in the minds of future engineering and manageme nt practitioners.
