Julie Ann Stuart Williams

Matching daily healthcare provider capacity to demand in advanced access scheduling systems

Advanced access scheduling, introduced in the early 1990s, is reported to significantly improve the performance of outpatient clinics. The successful implementation of advanced access scheduling requires the match of daily healthcare provider capacity with patient demand. In this paper, for the first time a closed-form approach is presented to determine the optimal percentage of open-access appointments to match daily provider capacity to demand. This paper introduces the conditions for the optimal percentage of open-access appointments and the procedure to find the optimal percentage. Furthermore, the sensitivity of the optimal percentage of open-access appointments to provider capacity, no-show rates, and demand distribution is investigated. Our results demonstrate that the optimal percentage of open-access appointments mainly depends on the ratio of the average demand for open-access appointments to provider capacity and the ratio of the show-up rates for prescheduled and open-access appointments.

An analytical model for reverse automotive production planning and pricing

Automotive shredders need a reverse production planning strategy that includes determining at what price to purchase vehicle hulks from different sources. In this paper, we formulate the automotive reverse production planning and pricing problem in a nonlinear programming model, develop an approximate supply function for hulks when adjacent shredders price independently, and compare two hulk pricing strategies in three trends for ferrous metal and hulk prices: constant, increasing and decreasing. The case study results indicate that adjusting purchase price based on hulk composition in coordination with planning for purchasing, storing and processing can increase net revenue by 7-15%.

Viable plastics recycling from end-of-life electronics

Millions of end-of-life (EOL) electronic products represent more than one million tons of engineering thermoplastics. The economically and environmentally sound recovery of engineering thermoplastics from EOL electronics is a challenge to the sustainability of electronics manufacturing. In this paper, we review the technologies to separate and identify pure post-consumer plastics from EOL electronics, which are followed by the comparison of electronic plastics recycling processes and the network models for plastics recycling processes. We also review successful plastics recycling practices for electronics. In addition, further research directions for recycling plastics from EOL electronics are discussed.

An automotive bulk recycling planning model

The automotive recycling infrastructure successfully recovers 75% of the material weight in end-of-life vehicles primarily through ferrous metal separation. However, this industry faces significant challenges as automotive manufacturers increase the use of nonferrous and nonmetallic materials. As the nonferrous content in end-of-life vehicles rises, automotive shredders need to evaluate to what extent to separate nonferrous metals. We propose a recycling planning model for automotive shredders to make short-term tactical decisions regarding to what extent to process and to reprocess materials through multiple passes. In addition, the mixed integer programming model determines whether to combine materials for shipment. In a case study for automotive shredding decisions for the current composition and more polymer-intensive end-of-life vehicles, we use our model to show the sensitivity of the decision to reprocess light nonferrous metal to low and high metal prices. Contrary to observations in practice to mix light and heavy nonferrous metals for shipment, we show multiple scenarios where the model chooses to reprocess and ship separated light and heavy nonferrous metals.

On-Line Content Uniformity Determination of Tablets Using Low-Resolution Raman Spectroscopy

Analytical techniques for rapid and nondestructive content uniformity determination of pharmaceutical solid dosage forms have been studied for several years in an effort to replace the traditional wet chemistry procedures, which are labor intensive and time consuming. Both Raman spectroscopy and near-infrared spectroscopy have been used for this purpose, and predictability errors are approaching those of the traditional techniques. In this study, a low-resolution Raman spectrometer was utilized to demonstrate the feasibility of both rapid at-line and on-line determination of tablet content uniformity. Additionally, sampling statistics were reviewed in an effort to determine how many tablets should be assayed for specific batch sizes. A good correlation was observed between assay values determined by high-performance liquid chromatography and Raman analysis. Due to rapid acquisition times for the Raman data, it was possible to analyze far more samples than with wet chemistry methods, leading to a better statistical description of variation within the batch. For at-line experiments, the sampling volume was increased by rotating the laser beam during the acquisition period. For the on-line experiments, the sampling volume was increased by sampling from a stream of tablets moving underneath the Raman probe on a conveyor system. Finally, an approach is proposed for monitoring content uniformity immediately following the compaction process. In conclusion, Raman spectroscopy has potential as a rapid, nondestructive technique for at- or on-line determination of tablet content uniformity.

Model-based analysis of capacity and service fees for electronics recyclers

By 2010, billions of discarded electronics will require recycling due to concerns over data destruction and electronics recycling legislation. Unlike manufacturing planning that seeks to meet finished goods demand, recycling planning must meet recycling service demand to accept end-of-life electronic products. Motivated by actual electronics recycling problems that were observed, a short-term bulk recycling planning model was developed to determine what products to accept, process, and reprocess. Using data collected from electronics recyclers, an experiment was run including eight scenarios on the analytical recycling planning model that vary the processing capacity, service fee, and storage capacity. Although the results demonstrate that recyclers may improve their material revenues with reprocessing and selection of key product groups, the material revenues do not cover the total costs. Products with higher service fee-to-weight ratios and material output revenues are more attractive for recyclers to accept. Service fee revenues are necessary to cover overhead costs such as capital equipment purchases, administrative costs, and logistics costs. The modeling scenarios also indicate that recyclers could benefit from greater processing and staging space capacity to accept more products that generate service fee revenues and, upon processing, generate material revenues.

Online quality control with Raman spectroscopy in pharmaceutical tablet manufacturing

Quality testing for tablet composition and uniformity at the manufacturing stage is critical to the pharmaceutical industry. However, current off-line, destructive, wet chemistry analysis incurs significant costs and long test times. This paper introduces a methodology to form a population batch size for quality control sampling in tablet manufacturing for an alternative online testing technology, Raman spectroscopy. An approach is presented to determine the minimum testing batch size for quality control sampling based on the desirable confidence level, margin of error, testing rate, and production rate. Experiments with both traditional wet chemistry analysis and Raman spectroscopy are conducted. The results demonstrate that the quality of Raman spectroscopy is comparable to that of wet chemistry analysis. The proposed quality sampling methodology reduces the queue time by orders of magnitude for typical tablet batches of one to four million tablets awaiting test results following the tablet compaction process. Furthermore, it increases the tablet sample size, which subsequently raises the confidence level.

A mean-variance model to optimize the fixed versus open appointment percentages in open access scheduling systems

Although healthcare quality may improve with short-notice scheduling and subsequently higher patient show-up rates, the variability in patient flow may negatively impact the service design. This study demonstrates how to select the percentage for short-notice or open appointments in an open access scheduling system subject to two quality performance metrics. Specifically, we develop a mean-variance model and an efficient solution procedure to help clinic administrators determine the open appointment percentage subject to increasing the average number of patients seen while also reducing the variability. Our numerical results indicate that for cases with high patient demand and high patient no-show rates for fixed appointments, one or more Pareto optimal percentages of open appointments significantly decrease the variability in the number of patients seen with only a negligible decrease in the expected number of patients seen. While our method provides a useful tool for clinic administrators, it also presents a modeling foundation for open access scheduling with quality management objectives to smooth patient flow and improve capacity utilization.

Plastic separation planning for end-of-life electronics

Important challenges remain for sustainable design, manufacture, use, and recycling of electronics including materials selection and disassembly time. This paper examines the value relationship between the quantity of plastics separated and the time required for disassembly and segregation. Labor costs for disassembly can constitute a large portion of the total acquisition cost for a recycled material. We report work measurement studies conducted on the disassembly of 21 computers, 22 printers, and 32 monitors manufactured by 27 producers in the years from 1984 to 2001. Results include the weight per total separation time for each plastic part. Each recovered part is identified according to polymer resin using laser Raman spectroscopy by chemometric reference to a library of standards. We extrapolate time as well as the product input required to accumulate various specific types of plastic. We develop disassembly policies and show that they are effective for a variety of computer, printer, or monitor models, which is typical of the random product streams that arrive at electronics recycling facilities. The results demonstrate how new laser identification technology and work measurement can be used for plastics separation planning.

A review of research towards computer integrated demanufacturing for materials recovery

The recovery of both toxic and non-toxic materials from billions of end-of-life electronics calls for efficient processes and exploration of opportunities for computer integrated demanufacturing for materials recovery. To date, recycling automation for selective disassembly has been limited by the proliferation of product designs, the difficulty of acquiring product feature and material content information, and the lack of integration of collection and demanufacturing processing. Product designs with standard modules and standard fasteners would improve the options for more automated disassembly. Making product structure and material composition information from a product design profile available will support planning models, Petri net algorithms and control models for demanufacturing, as well as integrated manufacturing and demanufacturing. Advances in imaging and materials identification techniques as well as more flexible technologies to separate materials may provide new opportunities for expert Petri net approaches for selective robotic disassembly. Linking end-of-life product service demand information will enhance scheduling for demand-driven demanufacturing. Nonetheless, the random arrival of so many different product sizes and design structures will require new approaches to designing reverse logistics networks and linking their activities. The present paper reviews the research to automate materials recovery planning and control, identifies challenges, and discusses directions for future research.