Integrating Worker differences into Workforce Planning

In today’s global and competitive market, manufacturing companies are working hard to improve their production system performance. Most companies develop production systems that can help in quality improvement, cost reduction and throughput time reduction. Manufacturing systems typically consist of different elements including production methods, machines, processes, control and information systems. Human issues are an important part of manufacturing systems, yet most companies do not pay sufficient attention to them. The majority of a company’s improvement comes when the right workers with the right skills, behaviors and capacities are deployed appropriately throughout a company. Developing an integrated workforce planning system that incorporates the human being is a challenging problem. To achieve this goal, a multi-objective mixed integer nonlinear programming model is developed to determine the amount of hiring, firing, training, overtime for each worker type and the amount of the break for each worker. This thesis considers a workforce planning model including human aspects such as skills, training, workers’ personalities, capacity, motivation, learning rates, and fatigue and recovery levels. This model helps to minimize the hiring, firing, training and overtime costs, minimize the number of fired workers with high performance, minimize the break time and minimize the average worker’s fatigue level. The results indicate that the worker differences should be considered in workforce scheduling to generate realistic plans with minimum costs. This thesis also investigates the effects of human fatigue and recovery rates, and human learning rates on the performance of the production systems. Moreover, a decision support system (DSS) based on the proposed model is introduced using the Excel-LINGO software interfacing feature. It is shown that considering both technical and human factors together can reduce the costs in manufacturing systems and ensure the safety of the workers

Decision support tool for dynamic workforce scheduling in manufacturing environments \

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).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.by Radhika Malik.M. Eng

A Healthy Work Schedule: Improving Dynamics for Nurses’ Health

Rotating shift work is an unavoidable, integral aspect of nursing at a large hospital in the Midwest; however, the fatigue involved in rotating shift work is avoidable. Research has shown how fatigue related to rotating shifts can impact nurses and ultimately affect patients. Fatigue caused by rotating shift work has been proven to decrease nurses’ levels of alertness and vigilance, which directly correlates to higher incidences of errors with patients. In addition, nurses who work rotating shifts have been proven to have problems with psycho-physical health, biological functions, and social relationships. It is through an understanding of the risks related to rotating shift work and the application of Watson’s Caring concepts and Caritas Processes that nurses have the opportunity to explore strategies to combat the associated negative effects. This exploration of strategies led to a search for options to design a three week schedule that allows for sufficient recovery time between rotating shifts for nurses who work on a medical, surgical, progressive care unit. The creation of a healthy work schedule was based on nurses’ feedback and an understanding of the institutional scheduling procedural guidelines. Ultimately the goal is to create a schedule that allocates time for nurses to customize self-care habits and routines that nurtures self in order to serve others