Matching Items (13)
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- All Subjects: Supply Chain Management
- Creators: Maltz, Arnold
Description
In a healthcare setting, the Sterile Processing Department (SPD) provides ancillary services to the Operating Room (OR), Emergency Room, Labor & Delivery, and off-site clinics. SPD's function is to reprocess reusable surgical instruments and return them to their home departments. The management of surgical instruments and medical devices can impact patient safety and hospital revenue. Any time instrumentation or devices are not available or are not fit for use, patient safety and revenue can be negatively impacted. One step of the instrument reprocessing cycle is sterilization. Steam sterilization is the sterilization method used for the majority of surgical instruments and is preferred to immediate use steam sterilization (IUSS) because terminally sterilized items can be stored until needed. IUSS Items must be used promptly and cannot be stored for later use. IUSS is intended for emergency situations and not as regular course of action. Unfortunately, IUSS is used to compensate for inadequate inventory levels, scheduling conflicts, and miscommunications. If IUSS is viewed as an adverse event, then monitoring IUSS incidences can help healthcare organizations meet patient safety goals and financial goals along with aiding in process improvement efforts. This work recommends statistical process control methods to IUSS incidents and illustrates the use of control charts for IUSS occurrences through a case study and analysis of the control charts for data from a health care provider. Furthermore, this work considers the application of data mining methods to IUSS occurrences and presents a representative example of data mining to the IUSS occurrences. This extends the application of statistical process control and data mining in healthcare applications.
ContributorsWeart, Gail (Author) / Runger, George C. (Thesis advisor) / Li, Jing (Committee member) / Shunk, Dan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Today's competitive markets force companies to constantly engage in the complex task of managing their demand. In make-to-order manufacturing or service systems, the demand of a product is shaped by price and lead times, where high price and lead time quotes ensure profitability for supplier, but discourage the customers from placing orders. Low price and lead times, on the other hand, generally result in high demand, but do not necessarily ensure profitability. The price and lead time quotation problem considers the trade-off between offering high and low prices and lead times. The recent practices in make-to- order manufacturing companies reveal the importance of dynamic quotation strategies, under which the prices and lead time quotes flexibly change depending on the status of the system. In this dissertation, the objective is to model a make-to-order manufacturing system and explore various aspects of dynamic quotation strategies such as the behavior of optimal price and lead time decisions, the impact of customer preferences on optimal decisions, the benefits of employing dynamic quotation in comparison to simpler quotation strategies, and the benefits of coordinating price and lead time decisions. I first consider a manufacturer that receives demand from spot purchasers (who are quoted dynamic price and lead times), as well as from contract customers who have agree- ments with the manufacturer with fixed price and lead time terms. I analyze how customer preferences affect the optimal price and lead time decisions, the benefits of dynamic quo- tation, and the optimal mix of spot purchaser and contract customers. These analyses necessitate the computation of expected tardiness of customer orders at the moment cus- tomer enters the system. Hence, in the second part of the dissertation, I develop method- ologies to compute the expected tardiness in multi-class priority queues. For the trivial single class case, a closed formulation is obtained. For the more complex multi-class case, numerical inverse Laplace transformation algorithms are developed. In the last part of the dissertation, I model a decentralized system with two components. Marketing department determines the price quotes with the objective of maximizing revenues, and manufacturing department determines the lead time quotes to minimize lateness costs. I discuss the ben- efits of coordinating price and lead time decisions, and develop an incentivization scheme to reduce the negative impacts of lack of coordination.
ContributorsHafizoglu, Ahmet Baykal (Author) / Gel, Esma S (Thesis advisor) / Villalobos, Jesus R (Committee member) / Mirchandani, Pitu (Committee member) / Keskinocak, Pinar (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Social shopping has emerged as a popular online retailing segment. Social shopping revolves around online communities that bring consumers together to shop for deals. Online retailers have been making significant investments to encourage consumers to join online communities linked to their websites in the hope that social interactions among consumers will increase consumption rates. However, the assumption that social interactions increase consumption rates in social shopping remains largely untested in empirical settings. Also, the mechanisms of such an effect remain unclear. Moreover, extant literature has overlooked the role played by elements of the marketing mix, including product characteristics and the commercial context, in defining the effect that social interaction mechanisms have on consumption rates in this focused context. Furthermore, common knowledge in the operations management discipline challenges the largely held assumption, in the social interactions literature, that increasing consumption rates will always be beneficial to online retailers. Higher consumption rates may lead to stockouts, leading to lower service levels. This dissertation develops and empirically tests a theoretical framework that addresses these managerially relevant issues. Specifically, the investigation centers on the effects of social interaction mechanisms on consumption rates in social shopping. In turn, it assesses the nature of the relationship between consumption rates and service levels, after controlling for inventory provision. Finally, it assesses the role played by elements of the marketing mix in defining the relationship between social interaction mechanisms and consumption rates in this focused context. The research methodology uses experiments as the primary source of data collection, and employs econometrics techniques to statistically assess the conceptual framework. The results from the empirical analysis provide interesting insights. First, they unveil influential consumers in social shopping according to relational and structural elements of the social network of consumers and time of purchase. Second, the influence of early buyers' purchases on consumption rates becomes weaker when the quality of the products being offered as part of a deal increases, but it becomes stronger when the price of those products increases. Finally, as deals' consumption rates increase, their service levels decrease at a faster pace.
ContributorsSodero, Annibal (Author) / Rabinovich, Elliot (Thesis advisor) / Sinha, Rajiv (Committee member) / Maltz, Arnold (Committee member) / Arizona State University (Publisher)
Created2012
Description
This piece aims to discuss the roles of emerging geographies within the context of global supply chains, approaching the conversation with a "systems" view, emphasizing three key facets essential to a holistic and interdisciplinary environmental analysis: -The Implications of Governmental & Economic Activities -Supply Chain Enablement Activities, Risk Mitigation in Emerging Nations -Implications Regarding Sustainability, Corporate Social Responsibility In the appreciation of the interdisciplinary implications that stem from participation in global supply networks, supply chain professionals can position their firms for continued success in the proactive construction of robust and resilient supply chains. Across industries, how will supply networks in emerging geographies continue to evolve? Appreciating the inherent nuances related to the political and economic climate of a region, the extent to which enablement activities must occur, and sustainability/CSR tie-ins will be key to acquire this understanding. This deliverable aims to leverage the work of philosophers, researchers and business personnel as these questions are explored. The author will also introduce a novel method of teaching (IMRS) in the undergraduate business classroom that challenges the students to integrate their prior experiences both in the classroom and in the business world as they learn to craft locally relevant solutions to solve complex global problems.
ContributorsVaney, Rachel Lee (Author) / Maltz, Arnold (Thesis director) / Kellso, James (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor)
Created2015-05
DescriptionA look at current 3D printing capabilities, and exploring the potential for additive manufacturing to transform the economy in the future.
ContributorsBennewitz, Chase (Co-author) / Paul, John (Co-author) / Parker, Kerry (Co-author) / Maltz, Arnold (Thesis director) / McDowell, John (Committee member) / Fujinami, Chris (Committee member) / Barrett, The Honors College (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor)
Created2013-05
Description
This paper seeks to provide a comprehensive consideration of the full implications of engaging in real earnings management through 1.) an in-depth literature review of selected studies concerning real earnings management, 2.) supplemental interviews to consider real earnings management from various perspectives including supply chain management, accounting and management, as well as 3.) a final framework of the considerations that must be made to fully understand the implications of real earnings management. Though the ethics of real earnings management will be discussed, no determination will be made to support or discredit its use. The methods of real earnings management are plentiful and would benefit most from being judged on a case-by-case basis before coming to any firm conclusions.
ContributorsWestgard, Kristy Kayan (Author) / Maltz, Arnold (Thesis director) / Leckey, Andrew (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The original goal of this project was to create a case study that would help figure out a way to figure out how to get better food, and more food, to areas where there is little to no logistical infrastructure in place. Specifically, the Navajo Nation in North Eastern Arizona where the road infrastructure is not as developed and without enough stores to saturate the region. A partnership with Peddler's Son Produce, a company who was hoping to expand their distribution services to North-Eastern Arizona and other lesser-served areas across Arizona, allowed for the creation of Logistical Route Simulations which allowed the expanse of what areas could be reached with cross-docking stations in various areas. After all the information of the route simulations was compiled, it was abstracted to a case study. There is no one solution of how to expand a company so what the case study does is give students all of the information for costs and potential routes and then tells them to decide how many stops should be taken at each city in each route, which routes should be taken, and which routes shouldn't, and which cross-docking station, or multiple cross-docking stations the company should choose. The Case Study also includes teaching notes for the professor doing it which have the completed logistic route simulations and all the data and information that was learned but not included in the case study. This case study can now be used to help others figure out how to create profitable logistics routes which serves the original goal of the project.
ContributorsFierro, Leticia (Author) / Maltz, Arnold (Thesis director) / Kellso, James (Committee member) / Department of Supply Chain Management (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
This thesis looks at a short-term solution to the truck driver shortage: transitioning U.S. military veterans into truck driver roles. Due to the adoption of self-driving trucks, the shortage is projected to end in 2022; however, freight companies may not be able to keep up with growing freight volumes until then. In the meantime, providing commercial driver's license (CDL) training on military bases has the potential to alleviate the shortage and veteran unemployment. A number of journal articles were read and interviews were conducted to determine the practicality of this solution. This thesis includes those findings and a number of considerations that should be made before implementing it.
ContributorsPatel, Nikhil (Author) / Kellso, James (Thesis director) / Maltz, Arnold (Committee member) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This research focuses and discusses on the Supply Chain process within the mental health industry and its impact on the center for health empowerment education employment recovery. Our first approach was to research background information on mental health sector. With 115 billion dollars on mental health treatment investment annually nationwide, many citizens continues to struggle to find help. Due to such a complex structure of specific industry, we needed to focus more specifically, Arizona. Even within Arizona, we chose one organization to discuss their complex supply chain logistic issues. Through analysis of beneficiaries, technology system, finance management, employer, many educational programs, we were able to identify possible improvements. Through utilizing Supply Chain concepts, my co-author and I came up with few solutions that can greatly benefit the organization.
ContributorsChoi, Jennifer (Co-author) / Malakyan, Sonya (Co-author) / Eftekhar, Mahyar (Thesis director) / Maltz, Arnold (Committee member) / W. P. Carey School of Business (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The complexity of supply chains (SC) has grown rapidly in recent years, resulting in an increased difficulty to evaluate and visualize performance. Consequently, analytical approaches to evaluate SC performance in near real time relative to targets and plans are important to detect and react to deviations in order to prevent major disruptions.
Manufacturing anomalies, inaccurate forecasts, and other problems can lead to SC disruptions. Traditional monitoring methods are not sufficient in this respect, because com- plex SCs feature changes in manufacturing tasks (dynamic complexity) and carry a large number of stock keeping units (detail complexity). Problems are easily confounded with normal system variations.
Motivated by these real challenges faced by modern SC, new surveillance solutions are proposed to detect system deviations that could lead to disruptions in a complex SC. To address supply-side deviations, the fitness of different statistics that can be extracted from the enterprise resource planning system is evaluated. A monitoring strategy is first proposed for SCs featuring high levels of dynamic complexity. This presents an opportunity for monitoring methods to be applied in a new, rich domain of SC management. Then a monitoring strategy, called Heat Map Contrasts (HMC), which converts monitoring into a series of classification problems, is used to monitor SCs with both high levels of dynamic and detail complexities. Data from a semiconductor SC simulator are used to compare the methods with other alternatives under various failure cases, and the results illustrate the viability of our methods.
To address demand-side deviations, a new method of quantifying forecast uncer- tainties using the progression of forecast updates is presented. It is illustrated that a rich amount of information is available in rolling horizon forecasts. Two proactive indicators of future forecast errors are extracted from the forecast stream. This quantitative method re- quires no knowledge of the forecasting model itself and has shown promising results when applied to two datasets consisting of real forecast updates.
Manufacturing anomalies, inaccurate forecasts, and other problems can lead to SC disruptions. Traditional monitoring methods are not sufficient in this respect, because com- plex SCs feature changes in manufacturing tasks (dynamic complexity) and carry a large number of stock keeping units (detail complexity). Problems are easily confounded with normal system variations.
Motivated by these real challenges faced by modern SC, new surveillance solutions are proposed to detect system deviations that could lead to disruptions in a complex SC. To address supply-side deviations, the fitness of different statistics that can be extracted from the enterprise resource planning system is evaluated. A monitoring strategy is first proposed for SCs featuring high levels of dynamic complexity. This presents an opportunity for monitoring methods to be applied in a new, rich domain of SC management. Then a monitoring strategy, called Heat Map Contrasts (HMC), which converts monitoring into a series of classification problems, is used to monitor SCs with both high levels of dynamic and detail complexities. Data from a semiconductor SC simulator are used to compare the methods with other alternatives under various failure cases, and the results illustrate the viability of our methods.
To address demand-side deviations, a new method of quantifying forecast uncer- tainties using the progression of forecast updates is presented. It is illustrated that a rich amount of information is available in rolling horizon forecasts. Two proactive indicators of future forecast errors are extracted from the forecast stream. This quantitative method re- quires no knowledge of the forecasting model itself and has shown promising results when applied to two datasets consisting of real forecast updates.
ContributorsLiu, Lei (Author) / Runger, George C. (Thesis advisor) / Gel, Esma (Committee member) / Pan, Rong (Committee member) / Janakiram, Mani (Committee member) / Arizona State University (Publisher)
Created2015