Deborah J. Medeiros

Improving patient flow in a hospital emergency department

Hospital emergency departments in the US are facing increasing challenges due to growth in patient demand for their services, and inability to increase capacity to match demand. We report on a new approach to patient flow in emergency departments, and a simulation model of the approach. Initial results from the model show that the approach is feasible, and a pilot study demonstrates substantial improvements in patient care.

Part orientations for CMM inspection using dimensioned visibility maps

Abstract This paper presents a methodology for determining a set of part orientations on a coordinate measuring machine (CMM), given part descriptions and tolerance information. A part frequently needs more than one orientation for inspection, and therefore it is important to determine a set of part orientations such that all tolerances under consideration can be inspected. The methodology utilizes the visibility map (VMap) to represent accessible directions from which measurements for inspecting a tolerance can be performed. The concept of VMap dimensionality is proposed to provide the basis for clustering VMaps as well as to facilitate the clustering procedure. The presented heuristic groups dimensioned VMaps into a set of disjoint VMap clusters, providing a reasonably small number of part orientations. The algorithms are implemented in C++ and tested on a SGI workstation.

Simulation of robotic manufacturing cells: a modular approach:

This research provides a general modeling approach for the design and analysis of computer-controlled manufacturing cells containing robots, sensors, automatic machines, and orientation devices. The development process is described and alternative concepts are discussed. The developed ap proach allows a simulation model to be constructed by se lecting appropriate modules from an available library and linking them together. A demonstration manufacturing cell developed by McDonnell Douglas for the Air Force In tegrated Computer-Aided Manufacturing (ICAM) program is utilized to illustrate the concepts and a more complex exam ple is presented to illustrate the versatility. This approach is flexible because alternative configurations can be modeled quickly and easily. Individuals with significant expertise in cell design but little experience in simulation can create simulation models of manufacturing cells and perform mean ingful analysis.

Evaluating arrival rate uncertainty in call centers

Inbound call center operations are challenging to manage, in large part because there is considerable uncertainty in estimates of arrival rates, which vary over time. We have developed a general purpose simulation model for inbound call center operations which supports time varying and uncertain arrival rates along with variable staffing. We outline the conceptual and technical design of the simulation model. We then define and conduct an initial experiment that uses the model to evaluate the impact of arrival rate uncertainty on call center performance. We find that arrival rate uncertainty creates significant planning challenges for managers attempting to satisfy tight performance targets, particularly one-sided performance measures. We also find that abandonment rate has a major impact on call center performance

Partial cross training in call centers with uncertain arrivals and global service level agreements

Inbound call center operations are challenging to manage; there is considerable uncertainty in estimates of arrival rates, and the operation is often subject to strict service level constraints. This paper is motivated by work with a provider of outsourced technical support services in which most projects (client specific support operations) include an inbound tier one help desk subject to a monthly service level agreement (SLA). Support services are highly specialized and a significant training investment is required, an investment that is not transferable to other projects. We investigate the option of cross training a subset of agents so that they may serve calls from two separate projects, a process we refer to as partial pooling. Our paper seeks to quantity the benefits of partial pooling and characterize the conditions under which pooling is most beneficial. We find that low levels of cross training yield significant benefit.

A genetic algorithm for sequential part assignment for PCB assembly

We present a genetic algorithm for printed circuit board (PCB) assembly, which simultaneously solves the feeder assignment and component sequencing problems. The algorithm uses a unique gene selection procedure that increases the convergence rate without degrading the solution quality. We have compared the performance of our algorithm with existing approaches and have demonstrated improved performance. We have also implemented the algorithm on a Quad IIIc insertion machine for surface mount components. The resulting suboptimal assembly times estimated by the algorithm have been found to be close to the actual optimal values.

Multiple machine JIT scheduling: a tabu search approach

This paper presents an approach to solving the multiple machine, non-preemptive, earliness-tardiness scheduling problem with unequal due dates in a flow shop with machine tiers (FMT). In this variant of the flow shop problem, machines are arranged in tiers or groups, and the jobs must visit one machine in each tier. The processing times, machine assignments, and due dates are deterministic and known in advance. The objective is to find a permutation schedule that minimizes the total deviation of each job from its due date. A tabu search (TS) meta-heuristic combined with an LP evaluation function is applied to solve this problem and results are compared to optimal permutation solutions for small problems and the earliest due date schedule for large problems. Several neighborhood generation methods and two diversification strategies are examined to determine their effect on solution quality. Results show that the TS method works well for this problem. TS found the optimal solution in all but one of the small problem instances and improved the earliest due date solutions for larger instances where no optimal solutions could be found.

Real-time simulation for decision support in continuous flow manufacturing systems

Conventional, hierarchical, and optimizing approaches to real-time decision support using simulation are developed and compared. Issues related to the use of simulation for real time decision support are considered. The decision support systems are tested using an emulation of a continuous flow manufacturing system.

Shop scheduling using Tabu search and simulation

An important goal in scheduling products through a manufacturing facility is to assure that the work is completed as close as possible to its due date. Work that is late creates downstream delays, while early completion can be detrimental if storage space is limited. This paper reports initial results in developing a scheduling procedure for an automated steel plate fabrication facility. The approach uses Tabu search combined with simulation to schedule product through a set of machines. Performance of the procedure is evaluated by comparison to the optimal solution for small problem instances, and to a good heuristic for larger problems. Results show that the Tabu search method works well for this problem. Combining Tabu search with simulation allows the incorporation of more realistic constraints on system operation.

A simulation-based backward planning approach for order-release

The problem of order release planning for a make-toorder production facility is addressed. Traditionally, order-release planning in a multi-stage shop is performed with material requirements planning (MRP) logic. MRP assumes infinite resource capacity and component lead times that are estimated using historical data, past experience, and rules-of-thumb. These assumptions often result in infeasible plans that make the task of scheduling difficult. An approach to order release planning termed qRP (resource planning based on queuing simulation) is discussed. qRP generates order release plans via a backward bill of material explosion logic similar to MRP except that a queuing simulation model of the facility is used. The simulation model captures the appropriate level of detail to provide a more realistic picture for planning. Component lead times are time-based (dependent on the current state of the shop) and may change from period to period. Automatic factory and simulation model generators are developed to compare this dynamic lead time approach with the static approach offered by MRP. Generalizations are made for key manufacturing attributes.