Matching Items (13)
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- All Subjects: Supply Chain Management
- Creators: Department of Finance
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
P.F. Chang's China Bistro is a privately-held purveyor of Asian fare in the United States and internationally, known largely for its vibrant atmosphere and lettuce wraps. With hundreds of locations and dozens of menu items, procurement, logistics, and coordination of ingredient delivery to P.F. Chang's restaurants is no small task. Despite their difficulty, supply chain operations from suppliers to customers' plates must run efficiently if P.F. Chang's is to maintain customer loyalty, a trusted brand, and profitability. As such, supply chain initiatives that allow for faster, better, or lower-cost operation are valuable investments for P.F. Chang's. In this project, two initiatives focused on increasing visibility along the value chain (with the hope of creating immediate value and easier implementation for future strategies). The first initiative involved stakeholder interviews and academic research to determine evaluation methods for P.F. Chang's suppliers in the form of a scorecard. The second project required extensive data collection from suppliers to isolate and remove excess cost in the inbound logistics of P.F. Chang's inventory. Both initiatives led to incremental improvement at P.F. Changs and the latter provided substantial cost savings. Further investigation and work is likely to yield continued benefits for the company. The increased use of data in all supply chains to guide decision-making will be easier for P.F. Chang's as it manages ongoing visibility efforts. Although process explanation and general outcomes will be reported here, the proprietary nature of P.F. Chang's data precludes full disclosure of the project results in public documentation.
ContributorsBarger, Michael Richard (Author) / Taylor, Todd (Thesis director) / Miller, Steve (Committee member) / Department of Economics (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This Thesis was written to prepare myself for my career in supply chain management and to take a look at negotiations deeper than SCM 355 and 455 did. It was also written to utilize my internship knowledge as a sourcing supply chain intern at UTC Aerospace Systems. My internship has introduced me to all of the possibilities in the procurement part of supply chain and overall got me very excited about my career. Throughout this paper I used prior knowledge from SCM classes, researched SCM articles, and face-to- face negotiations I have been a part of at my internship. I was very excited to learn more and research about negotiations to help me further in my career as a Commodity Manager at American Airlines.
ContributorsCollinsworth, Amelia Danielle (Author) / Carter, Craig (Thesis director) / Sadusky, Brian (Committee member) / Evers, Justin (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor)
Created2013-05
Description
New Venture Group, a student-run consulting organization at ASU, collaborated with representatives from Intel Corporation to determine current best supplier management practices in the area of capital equipment procurement. The New Venture Group team accomplished this goal by completing the following deliverables: (1) Research and consolidate best practices for managing capital equipment suppliers. (2) Interview suppliers of capital equipment in the semiconductor industry to understand their motivators. (3) Examine top supply chain companies that utilize capital equipment manufacturers within their procurement systems. (4) Gather data and knowledge in conjunction with Intel Corporation's current practices to improve the effectiveness of the company's supplier management techniques regarding capital equipment manufacturers. The thesis report outlines the key insights and recommendations that our team extracted from the research that we performed. Our team analyzed peer-reviewed journal articles, conducted interviews with suppliers of capital equipment to semiconductor manufacturers, and surveyed buyers at top companies to reach important key insights. We then used these insights to develop the following strategies to improve Intel's capital equipment supplier management structure: All Suppliers 1. Allow high-performance suppliers to select one reward from an established portfolio of incentives. 2. Increase measurement frequency for specific metrics. 3. Use collaborative two-way measurement with a corresponding balanced scorecard. Key Suppliers of Critical Products 4. Conduct gap analysis through supplier self-assessments. 5. Implement collaborative target pricing. 6. Delegate an Ombudsman. 7. Create a value map to determine the strengths and incentivize collaboration. 8. Create comparison charts comparing supplier technological competencies versus Intel's product developments. 9. Establish a systematized product development process and strategic sourcing strategy that supports the continuation of Moore's Law.
ContributorsSantiago, Bryce (Co-author) / Chen, Jenny (Co-author) / Chang, Karen (Co-author) / Baldridge, Stephen (Co-author) / Laub, Jeffrey (Thesis director) / Brooks, Daniel (Committee member) / Department of Information Systems (Contributor, Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Amazon Prime Air is the innovative new service that promises automated drone delivery in thirty minutes or less. The platform has not yet been brought to market, but there is a plethora compelling data available that suggests it will be a unique and highly disruptive business segment for Amazon. The aim of this thesis is to analyze the framework laid out by Amazon.com, Inc. for their anticipated Prime Air drone delivery platform, and offer our recommendations for what steps the e-commerce giant should take moving forward. Following a brief recap of the company's founding and a breakdown of its various business segments, we will begin our analysis by examining past strategic decisions that Amazon has made which have directly contributed to their current market position. It is our goal to construct a narrative of what events lead the company to begin developing a fleet of automated delivery vehicles. Following this history lesson, we will review and criticize the existing elements of Amazon's Prime Air platform, and explore any possible alternatives that they could have taken to optimize the development of this exciting new technology. Criticisms will touch upon elements such as cost efficiencies, brand management, and utilization of infrastructure to name but a few. These criticisms will be based upon data sourced from Amazon's available material as well as comments from market analysts and journalists. The culminating element of our analysis will be to offer our professional recommendations as to what we believe the next logical steps that Amazon should take for their Prime Air platform. These recommendations will be informed by our criticisms and our understanding of Amazon as a corporation. This chapter will be largely concerned with guiding Amazon towards a fully optimized drone delivery platform. Our recommendations will be based upon our extensive experience concerning cost and logistical efficiencies, as well as our knowledge of Amazon as a corporation. We will offer succinct suggestions for Amazon's immediate needs as well as long-term solutions to lingering obstacles that they may face.
ContributorsMcCaleb, Nicholas (Co-author) / Glynn, Reagan (Co-author) / Choi, Thomas (Thesis director) / Rogers, Dale (Committee member) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The purpose of this thesis is to gain a greater understanding of Ph. D research and how general research in the field of supply chain management and operations is being conducted in 2017. In order to gain a greater understanding, this thesis contains summaries and personal perspectives on four different supply chain management and operations seminars from visiting professors. There is also an expanded examination of the research area from the fourth seminar, process compliance. Multiple literature sources were used to construct a perspective on process development, process standardization, and process compliance origins and current state.
ContributorsBerg, Paul Joseph (Author) / Taylor, Todd (Thesis director) / Printezis, Antonios (Committee member) / Department of Finance (Contributor) / Hugh Downs School of Human Communication (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This thesis investigates the potential of life cycle analysis for more sustainable sourcing strategies in organizations. Using the example of the College of Lake County (CLC) in Illinois, I study how life-cycle analysis can help to improve the procurement of products and services in higher education. Currently, CLC's purchasing team does not understand how sourcing affects operational and environmental performance. In addition, CLC's purchasing team does not communicate effectively with other departments from a product utilization standpoint. The objective of this research is to analyze CLC's current product procurement process and to assess the feasibility of implementing life cycle analysis tools. Further, I evaluate different life cycle analysis tools and provide recommendations to CLC about the applicability of these tools so that they may be implemented into the university in the future. First, I find that both the procurement and IT department at CLC are not familiar with life-cycle analysis tools and hence, do not know about the life cycle of their processes and services. Second, I identify professional life cycle analysis tools relevant for CLC. Two software options, GaBi and SimaPro, are discussed. Finally, I suggest six steps for a successful implementation of life cycle analysis at CLC: (1) form an interdisciplinary team, (2) analyze demand and collect additional data, (3) conduct a product life cycle analysis using a software tool, (4) define which products to analyze further, (5) conduct life cycle costing analysis with the same software tool, and (6) utilize these results for decisions and delegation of responsibility.
ContributorsGotsch, Rachel Lynne (Author) / Wiedmer, Robert (Thesis director) / Kashiwagi, Jacob (Committee member) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Digital identification technology is the unsung hero of the LEAN manufacturing, Six sigma quality, and supply chain management movements. By tethering the physical to the digital world digital identification has helped usher industry into the information age. Today this technology continues to become more pervasive and advanced, in the future it is likely that it will have an even larger role to play. In this paper ten sources of current (last 12 months) academic literature will be reviewed in conjunction with two GE cases taken from personal experience in order to better understand the current applications and future trajectory of digital identification. The basis of this paper will be derived from understanding how the most prevalent form of digital identification, barcode is used to increase the efficiency and effectiveness of internal and external business operations. This "current state" knowledge will act as a benchmark to understand the potential diffusion and impact of future digital tracking technologies. The exploration of "up and coming" technologies will lead into a RFID technology deep dive encompassing its current applications and the frictions preventing widespread (barcode scale) implementation. In conclusion the "future state" of how RFID and more complex embedded communication devices will expand the scope of benefits granted by digital identification through a phenomenon known as the internet of things, along with the factors effecting its adoption will be discussed.
ContributorsCampbell, Ross Bradley (Author) / Printezis, Antonios (Thesis director) / Taylor, Todd (Committee member) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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