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The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title: Evaluating the impact of adopting 3d printing services on the retailers
Author: Rajaei Dehkordi, Sharareh
View Online: njit-etd2017-117
(xiii, 136 pages ~ 5.4 MB pdf)
Department: Department of Mechanical and Industrial Engineering
Degree: Doctor of Philosophy
Program: Industrial Engineering
Document Type: Dissertation
Advisory Committee: Cai, Wenbo (Committee chair)
Abdel-Malek, Layek (Committee member)
Das, Sanchoy K. (Committee member)
Bladikas, Athanassios K. (Committee member)
Shi, Junmin (Committee member)
Date: 2017-12
Keywords: Inventory management
Queueing systems
Markov system
3D printing technology
Substitute products
Retail management
Availability: Unrestricted
Abstract:

As additive manufacturing technology becomes more responsive to consumers’ demand, one important question for the retailers is whether they should provide 3D printing services in their brick-and-mortar store in addition to the traditional off-the-shelf product? If so, what should be the retailers pricing scheme to achieve a higher profit? What should be the optimal inventory level of off-the-shelf products? What is the optimal capacity of 3D printers? In this study, stochastic models are examined to capture the joint optimal 3D product price and capacity of 3D printers to maximize retailer’s expected profit while considering consumer product choices. Moreover, a stochastic model is developed to capture joint optimal pre-made inventory level and 3D product price to maximize retailer’s expected profit considering 3D services are offered in the off-the-shelf stock-out situations as a one-way substitution. Utilizing the Markov Decision Process, a framework for queuing systems is developed to examine the performance of various production/inventory strategies that optimize the system’s performance. Here, four strategies are developed: (i) providing only off-the-shelf products, (ii) providing only 3D printed products, (iii) substituting the shortage of the off-the-shelf products by 3D printed products, and (iv) providing consumers the options of selecting either the off-the-shelf product or the customized product produced by additive manufacturing. In essence, this approach assists decision makers in both capacity planning and inventory management. For all models, analytical results and numerical examples are given in order to demonstrate managerial insights.


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