|
" Applications of Operations Management in Emerging Technologies "
Arbabian, Mohammad Ebrahim
Moinzadeh, Kamran
| Document Type
|
:
|
Latin Dissertation
|
| Language of Document
|
:
|
English
|
| Record Number
|
:
|
1051770
|
| Doc. No
|
:
|
TL50887
|
| Main Entry
|
:
|
Arbabian, Mohammad Ebrahim
|
| Title & Author
|
:
|
Applications of Operations Management in Emerging Technologies\ Arbabian, Mohammad EbrahimMoinzadeh, Kamran
|
| College
|
:
|
University of Washington
|
| Date
|
:
|
2019
|
| Degree
|
:
|
Ph.D.
|
| student score
|
:
|
2019
|
| Note
|
:
|
175 p.
|
| Abstract
|
:
|
The question of how to match supply and demand, in a supply chain, is crucial because it significantly affects the supply chain's cost management. Therefore, to adopt new technologies, supply chain owners should update their matching supply-demand policies. A common objective of my dissertation is to analyze and develop game-theoretic and stochastic models to propose new policies for supply chains whose supply or demand is influenced by emerging technologies. In particular, in the third chapter, after the introduction and literature review in the first two chapters, with a specific focus on cloud industry, we study markets in which one unit of supply increases the capacity of multiple attributes simultaneously. Working within this type of market can be problematic: since the ratio of the capacities of the attributes in one unit of supply differs from the attributes' demand ratio, balancing supply and demand is challenging and requires new policies. In the fourth chapter, we specifically focus on 3D printing, and investigate how it affects supply chains responsiveness to demand. Due to the unique features of 3D printing technology, 3D printers can be installed in a retail store in order for the retailer to produce a product if he faces demand shortage. Therefore, this technology, can potentially decrease the expected mismatch between supply and demand. We, first, study a capacity expansion problem in cloud industry where the supply of attributes is bundled. The recent surge in demand for cloud services has posed a capacity expansion problem for service providers: while the growth of demand for capacity attributes (e.g., CPU and RAM) are time-varying and disproportionate, replenishment of these attributes are often in pre-configured packages (e.g., server clusters). This problem was originally introduced to us by Microsoft; however, our communications with other cloud companies such as Amazon and eBay indicate that they face similar problems. In the third chapter, we consider demand growths of two attributes (CPU and RAM) and focus on a class of policies consisting of capacity expansion cycles, where excess capacities of both attributes are required to reach a desired minimum level at the start and the end of each cycle. Following Microsoft's demand trends, we specifically focus on exponential demand growth. Using piece-wise linear demand approximation, we partially solve the problem, and to fully solve the problem, we devise a dynamic-programming-based algorithm. We next propose a forward-looking heuristic based on minimizing total cost rate in each cycle. We also examine the problem of cluster selection, given a set of available cluster-types. Last, we conduct a numerical study of the performance of the proposed heuristic. Next, we focus on the effects 3D printing can have on manufacturer-retailer relation in supply chains. 3D printing is a relatively new manufacturing technology that is attracting attention from many firms and governments. However, its impact on operations and firms’ relationships in a supply chain remains unexplored. In the fourth chapter, we investigate the impact of 3D printing, or additive manufacturing, on a supply chain consisting of a manufacturer and a retailer. We study two scenarios: 1) 3D printers are utilized by the manufacturer; and in a more novel situation 2) 3D printing technology is adopted by the retailer. We analyze the equilibrium of Stackelberg games in both cases and compare the results with a benchmark system without 3D printing. In the first scenario, both the retailer and the manufacturer are better off. In the second scenario, however, the retailer might be worse off although he is adopting 3D printing. This is because the supply chain is more responsive to demand, and the manufacturer can set higher wholesale prices for 3D plans and capture higher profits. We next compare the two scenarios. We identify and quantify the positive and negative effects associated with 3D printing for both firms in a supply chain. In many cases, the novel scenario of the retailer producing products, made possible by the unique features of 3D printing, results in the best profit outcomes for both firms.
|
| Descriptor
|
:
|
Operations research
|
| Added Entry
|
:
|
Moinzadeh, Kamran
|
| Added Entry
|
:
|
University of Washington
|
| |