Analysis of the Dynamical Behavior of Firms in a Three Layered Modular Assembly Model

This paper formulate an option model considers supplier's reaction as the profit sharing in module production, and analyses it by the agent theory. A dynamic environment in the model of the system of the production of modules of three layers is assumed, and the maker and the supplier are modeled by the technique of Genetic Programming (GP) as an agent who takes the action of selfoptimization. As result, the condition that the agent can exist continuously in the market is requested. In conclusion, violent competition and the selection of the similar agent are found even in the model of the option to consider the profit sharing and the reaction

Quantifying the efficiency of price-only contracts in push supply chains over demand distributions of known supports

In this paper, we quantify the efficiency of price-only contracts in supply chains with demand distributions by imposing prior knowledge only on the support, namely, those distributions with support [a, b] for 0 < a <_ b < +1. By characterizing the price of anarchy (PoA) under various push supply chain configurations, we enrich the application scope of the PoA concept in supply chain contracts along with complementary managerial insights. One of our major findings is that our quantitative analysis can identify scenarios where the price-only contract actually maintains its efficiency, namely, when the demand uncertainty, measured by the relative range b/a, is relatively low, entailing the price-only contract to be more attractive in this regard

Analysis of the revenue-sharing contract under different power structures with application in the biodiesel niche market

Master'sMASTER OF ENGINEERIN

Strategic Capacity Planning Problems in Revenue‐Sharing Joint Ventures

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154244/1/poms13128_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154244/2/poms13128.pd

Assessing Feasibility of Fostering Productive Energy Use of Swarm Electrified Microgrids in Rural Communities in Developing Countries

Access to affordable sustainable energy is critical for socio-economic human development. Energy poverty is most predominant for populations in rural areas of developing countries, typically the global south. Successful sustainable development requires technology and business innovations to reach these populations and empower them to improve their quality of life. Off-grid electrification strategies and productive energy use (PEU) appliances are a means of increasing energy access, fostering income generating activities. PEU appliances typically range from charging mobile phones to running equipment such as grain milling- or rice husking machines requiring several kilo-watts. Solar home systems (SHS) are an affordable off-grid electrification solution that have reached millions in rural areas. However, SHS has limited tier energy access, whereas microgrid solutions are more often effective in higher energy access but considerably more expensive and difficult to properly size for future energy demands. Swarm electrification is an innovation electrification strategy done by Solshare, that interconnects existing SHS in a community and allows the excess energy of the households SHS to be bought and sold through a bi-directional DC/DC smart controller. A swarm electrified microgrid is scalable and utilizes existing infrastructure while increasing the tier of energy access. The first objective of this thesis was to understand if swarm electrification could benefit from all the same opportunities as SHS for PEU and if it could overcome the limitations. The second objective was to create a robust methodology to economically and technically integrate a small- and a medium-sized PEU appliances into a swarm microgrid. The first objective was accomplished by conducting interviews with stakeholders working directly or indirectly with SHS. Depending on the geographical location of stakeholder operations, the specific incoming-generating benefits, (agriculture, services, industry, etc.) varied, but were all dependent on the capacity of the SHS, which was also repeatedly stated as a critical limitation. Challenges facing SHS for PEUs include financing, component quality, and knowledge of how to effectively use the SHS. The second objective utilized field data from a Selco India designed AC microgrid for Bochai Colony to design a theoretical swarm microgrid. Solshare’s swarm simulation program was used to visualize the energy exchange between households in the designed swarm microgrid. The methodology created was applied on the case study of Bochai, firstly resulting in one 750W and one 7.5kW wheat milling machine selected to be analyzed. The PEU appliances were each integrated into the theoretical swarm microgrid and the simulation results were studied. The small-sized appliance was integrated with 334 days of operation and the medium-sized appliance with 44 days. As part of the methodology, the payback period was assessed and both of the PEU appliances had payback periods under 3 years, which is desired for wheat milling machines. Based on the assumptions and data for Bochai Colony, the PEU appliances were economically and technically integrated into the swarm microgrid. In addition to the two main objectives, the capital cost for the AC microgrid versus swarm microgrid as well as affordability for Bochai community was analyzed. Swarm microgrids with new SHS had same cost order of magnitude as the AC microgrid. The cost of microloans for the SHS in the swarm microgrid was more affordable for households, compared to the electricity tariff paid for the AC microgrid, if the household electrical loads consisted of more than 2 LED lights and a mobile phone charger. Therefore, considering the households electrical demand is likely to increase, it would be more beneficial to implement swarm electrification. The PEU appliance simulation results and the high-level economic cost comparison of the swarm microgrid compared to the AC microgrid for Bochai, were shared with Selco India and Solshare. As a result, Selco is considering implementing a wheat milling machine for Bochai community based on the approximate positive results of the payback periods. Furthermore, because of the results highlighting the opportunities of swarm electrification, Solshare and Selco India will look at completing rural electrification projects together in India in the future

Information and decentralization in inventory, supply chain, and transportation systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.Includes bibliographical references (p. 199-213).This thesis investigates the impact of lack of information and decentralization of decision-making on the performance of inventory, supply chain, and transportation systems. In the first part of the thesis, we study two extensions of a classic single-item, single-period inventory control problem: the "newsvendor problem." We first analyze the newsvendor problem when the demand distribution is only partially specified by some moments and shape parameters. We determine order quantities that are robust, in the sense that they minimize the newsvendor's maximum regret about not acting optimally, and we compute the maximum value of additional information. The minimax regret approach is scalable to solve large practical problems, such as those arising in network revenue management, since it combines an efficient solution procedure with very modest data requirements. We then analyze the newsvendor problem when the inventory decision-making is decentralized. In supply chains, inventory decisions often result from complex negotiations among supply partners and might therefore lead to a loss of efficiency (in terms of profit loss).(cont.) We quantify the loss of efficiency of decentralized supply chains that use price-only contracts under the following configurations: series, assembly, competitive procurement, and competitive distribution. In the second part of the thesis, we characterize the dynamic nature of traffic equilibria in a transportation network. Using the theory of kinematic waves, we derive an analytical model for traffic delays capturing the first-order traffic dynamics and the impact of shock waves. We then incorporate the travel-time model within a dynamic user equilibrium setting and illustrate how the model applies to solve a large network assignment problem.by Guillaume Roels.Ph.D

Research on cost management methods used in new product development and their relationship to strategic priorities and collaborative competences: A systematic literature review and survey of the German manufacturing industry

This doctoral thesis presents a systematic review in both the management accounting as well as the innovation and operation management literature on 15 different methods for cost management. Subsequently, six antecedents of the adoption of cost management methods are identified and empirically analysed. It was found that the antecedents explaining the adoption of this methods during NPD are cost leadership

Demand Modeling And Capacity Planning For Innovative Short Life-Cycle Products

This dissertation focuses on demand modeling and capacity planning for innovative short life-cycle products. We first developed a new model in the class of stochastic Bass formulations that addresses the shortcomings of models from the extant literature. The proposed model considers the common fact that the market potential of a product is not fixed and might change during a life-cycle due to exogenous (e.g., economic- or competitors-related) or endogenous (e.g., quality-related) factors. Allowing this parameter (market potential in the Bass model) to follow a geometric random walk, we have showed that the future demand of a product in each period follows a lognormal distribution with specific mean and variance. We also developed a novel stochastic capacity expansion model that can be used by a make-to-order manufacturer, who faces stochastic stationary/non-stationary demand, in order to optimally determine policies for specifying the sizes of capacity procurement. In addition to the cost of expansion decisions, the proposed risk-neutral expansion model considers procurement lead-times, irreversibility of investments, and the costs associated with lost sales and unutilized capacity. We provide necessary and sufficient conditions for the derived optimal policy. We then present an exact solution method, which is more efficient than classical recursive methods. Additionally, three extensions of the proposed expansion model that can address more complicated settings are presented. The first extension increases the capability of the model in order to tackle capacity planning for a multi-sourcing scenario. Multi-sourcing is a case in which the manufacturer can procure capacity from two supply modes whose marginal expansion costs and lead-times are complementary. The second extension addresses a scenario in which an installed capacity can be used for producing future generations of a product. The last extension accounts for salvage value of the installed capacity in the model and provides the necessary and sufficient conditions for the optimal policy. Finally, using the proposed stochastic Bass model, we present the results and managerial insights gathered from numerical experiments that have been conducted for the stochastic capacity expansion models

Effect of Reconfiguration Characteristics on Manufacturing System Capacity Selection

The increasing frequency of new product introductions force today's companies to continuously upgrade their production capacities. The frequent revision of production capacities and the capacity loss during this period increase the importance of ramp up duration in evaluating capacity investments. This thesis aims to explore how a firm should optimally allocate its capacity investments among different manufacturing systems considering the capacity evolution in ramp up period. The proposed models in this thesis address a production facility making products that has a specific life cycle pattern. In this study, the duration of reconfiguration period for reconfigurable manufacturing system (RMS) is modeled as a function of the amount of capacity change. Through a sensitivity analysis, the impact of reconfiguration on the selection of manufacturing systems has been analyzed with respect to different product life cycle patterns. Through a mixed integer programming model, a various ramp up time patterns are taken into account and a more suitable reconfiguration type for a manufacturer in terms of system layout and response range is analyzed. Finally, the response time of a system is considered in the context of a supply chain network to improve the supply chain responsiveness. The appropriate response speed is selected through a decision tree analysis and based on the expected cost of the supply chain. The results show a faster response speed is a better choice as the failure probability of main supply node increases and/or the recovery of the main supply node decreases