A General Approach to Electrical Vehicle Battery Remanufacturing System Design

One of the major difficulties electrical vehicle (EV) industry facing today is the production and lifetime cost of battery packs. Studies show that using remanufactured batteries can dramatically lower the cost. The major difference between remanufacturing and traditional manufacturing is the supply and demand variabilities and uncertainties differences. The returned core for remanufacturing operations (supply side) can vary considerably in terms of the time of returns and the quality of returned products. On the other hand, because different contracts can be used to regulate suppliers, it is almost always assumed zero uncertainty and variability for traditional manufacturing systems. Similarly, customers demand traditional manufacturers to sell newly produced products in constant high quality. But, remanufacturers usually sell in aftermarket, and the quality of the products demanded can vary depends on the price range, usage, customer segment and many other factors. The key is to match supply and demand side variabilities so the overlapping between them can be maximized. Because of these differences, a new framework is needed for remanufacturing system design. This research aims at developing a new approach to use remanufactured battery packs to fulfill EV warranties and customer aftermarket demands and to match supply and demand side variabilities. First, a market lifetime EV battery return (supply side) forecasting method is develop, and it is validated using Monte Carlo simulation. Second, a discrete event simulation method is developed to estimate EV battery lifetime cost for both customer and manufacturer/remanufacturer. Third, a new remanufacturing business model and a simulation framework are developed so both the quality and quantity aspects of supply and demand can be altered and the lifetime cost for both customer and manufacturer/remanufacturer can be minimized. The business models and methodologies developed in this dissertation provide managerial insights to benefit both the manufacturer/remanufacturer and customers in EV industry. Many findings and methodologies can also be readily used in other remanufacturing settings. The effectiveness of the proposed models is illustrated and validated by case studies.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143955/1/xrliang_1.pd

Alternative scales in reliability models for a repairable system

In an industry, the lifetime of a technical system is often assessed according to its accumulated throughput/usage e.g., the performance of a Blast Furnace in terms of accumulated quantity of its product, the lifetime of a vehicle in terms of accumulated number of miles it has travelled. Most of these systems are repairable systems. The failure process of a repairable system is conventionally measured in the time domain also termed as a time scale in the literature. Nevertheless, the lifetime of some repairable systems and their failures may be measured in terms of their throughput/usage. Therefore, it makes sense to quantify their failure processes in terms of throughput/ usage which may be better indicators than time, of system failure and reliability. Time, usage or a combination of both time and usage may be used as alternative domains/scales of measurement for modelling the failure process of a repairable system. This paper proposes such alternative scales in reliability models for a repairable system. A method is devised in the paper to identify the better alternative scale to model the failure process and thus identify the appropriate scale to assess the system reliability. Industrial failure data are used to illustrate the proposed method

Warranty menu design for a two-dimensional warranty

Fierce competitions in the commercial product market have forced manufacturers to provide customer-friendly warranties with a view to achieving higher customer satisfaction and increasing the market share. This study proposes a strategy that offers customers a two-dimensional warranty menu with a number of warranty choices, called a flexible warranty policy. We investigate the design of a flexible two-dimensional warranty policy that contains a number of rectangular regions. This warranty policy is obtained by dividing customers into several groups according to their use rates and providing each group a germane warranty region. Consumers choose a favorable one from the menu according to their usage behaviors. Evidently, this flexible warranty policy is attractive to users of different usage behaviors, and thus, it gives the manufacturer a good position in advertising the product. When consumers are unaware about their use rates upon purchase, we consider a fixed two-dimensional warranty policy with a stair-case warranty region and show that it is equivalent to the flexible policy. Such an equivalence reveals the inherent relationship between the rectangular warranty policy, the L-shape warranty policy, the step-stair warranty policy and the iso-probability of failure warranty policy that were extensively discussed in the literature

Architecting Fail-Safe Supply Chains / Networks

Disruptions are large-scale stochastic events that rarely happen but have a major effect on supply networks’ topology. Some examples include: air traffic being suspended due to weather or terrorism, labor unions strike, sanctions imposed or lifted, company mergers, etc. Variations are small-scale stochastic events that frequently happen but only have a trivial effect on the efficiency of flow planning in supply networks. Some examples include: fluctuations in market demands (e.g. demand is always stochastic in competitive markets) and performance of production facilities (e.g. there is not any perfect production system in reality). A fail-safe supply network is one that mitigates the impact of variations and disruptions and provides an acceptable level of service. This is achieved by keeping connectivity in its topology against disruptions (structurally fail-safe) and coordinating the flow through the facilities against variations (operationally fail-safe). In this talk, I will show that to have a structurally fail-safe supply network, its topology should be robust against disruptions by positioning mitigation strategies and be resilient in executing these strategies. Considering “Flexibility” as a risk mitigation strategy, I answer the question “What are the best flexibility levels and flexibility speeds for facilities in structurally fail-safe supply networks?” Also, I will show that to have an operationally fail-safe supply network, its flow dynamics should be reliable against demand- and supply-side variations. In the presence of these variations, I answer the question “What is the most profitable flow dynamics throughout a supply network that is reliable against variations?” The method is verified using data from an engine maker. Findings include: i) there is a tradeoff between robustness and resilience in profit-based supply networks; ii) this tradeoff is more stable in larger supply networks with higher product supply quantities; and iii) supply networks with higher reliability in their flow planning require more flexibilities to be robust. Finally, I will touch upon possible extensions of the work into non-profit relief networks for disaster management

Predicting and reducing warranty costs by considering customer expectation and product performance

This dissertation develops from quality loss function to warranty loss function in which customer expectation is also considered to be a variable. First, Taguchi\u27s quality loss function for the larger-the-better case, which is different from the smaller-the better and nominal-the-best cases, has been assimilated into the other two by introducing a term called the target-mean ratio. Further topics addressed include the implications of a finite target on the classification of LTB characteristics, a new concept of a Complementary Characteristic , operating window, complexity, and SN ratio based on complexity. A warranty is a buyer\u27s confidence owing to the seller\u27s assurance to the buyer that a product will perform as stated or implied. The quality loss function only accounts for immediate issues within manufacturing facilities, whereas the warranty cost occurs during customer use. Therefore, this dissertation develops a methodology that can predict warranty probability and warranty costs on the basis of customer expectation in addition to product performance for smaller-the-better, nominal-the-best, and larger-the-better cases. In robust engineering, the signal-to-noise ratio is used to improve the robustness of a system. Most products and processes have multiple quality characteristics or output responses. Therefore, this research has been conducted to propose a metric that can be used for multi-response experiments for minimizing quality loss and improving robustness at the same time. The methodology proposed incorporates all three types of characteristics smaller-the-better, nominal-the-best, and larger-the-better and is based on components of quality loss --Abstract, page iii

Simulation of Automotive Warranty Data

This thesis will investigate the prediction of the number of claims in a two dimensional automotive warranty claim model for the case of minimal repair.The method involved fitting marginal distributions for age of claim and mileage of claim seperately. Next, various copulas were fitted to establish the correlation between age and mileage, and assessed for fit. The Gumbel copula is chosen as optimal. From this Gumbel copula, a simulation of warranty claims is undertaken. The method produced a good fit for claim age but performed less well for claim mileage, due to the asymmetry of the correlation between mileage and age. Further research directions to improve the accuracy and usefulness of this model are suggested

Post-Sale Cost Modeling and Optimization Linking Warranty and Preventive Maintenance

Ph.DDOCTOR OF PHILOSOPH

The Effectiveness of Warranties in the Solar Photovoltaic and Automotive Industries

A warranty is an agreement outlined by a manufacturer to a customer that defines performance requirements for a product or service. Although long warranty periods are a useful marketing tool, in 2011 the warranty claims expense was 2.6% of total sales for computer original equipment manufacturers (OEMs) and is over 2% of total sales in many other industries today. Solar PV systems offer inverters with 5-15 year warranties and PV modules with 25-year performance warranties. This is problematic for the return on investment (ROI) of solar PV systems when the modules are still productive and covered under warranty but inverter failures occur due to degradation of electronic components after their warranty has expired. Out-of-warranty inverter failures during the lifetime of solar panels decrease the ROI of solar PV systems significantly and can cause the annual ROI to actually be negative 15-25 years into the lifetime of the system. This thesis analyzes the factors that contribute to designing an optimal warranty period and the relationship between reliability and warranty periods using General Motors (GM) and the solar PV industry as case studies. A return on investment of a solar photovoltaic system is also conducted and the effect of reliability, changing tax credit structures, and failure areas of solar PV systems are analyzed

Enabling effective product launch decisions

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (p. 102-106).The present work looks into the question of optimizing the performance of product launch decisions-in particular, the decisions of product development duration and manufacturing ramp-up. It presents an innovative model for measuring product launch performance and optimizing the decisions by integrating a design structure matrix model for product development, a technical cost model for manufacturing, and revenue and warranty models for customer reaction to product quality into one model using net revenue as a metric. The model shows that overlooking the interactions between product development and manufacturing leads to suboptimal decisions. Furthermore, it points out that product quality is apparently the most important driver for product launch performance and that the effects of product launch decisions on resulting product quality need to be considered. Results from case studies demonstrate that improving firm's tactical strategies will help shorten product launch and improve its performance, while factors such as low reputation or high product failure rate will require lengthening product launch to minimize their impacts. Finally, the model results are analyzed to yield direction for firms relative to strategies that can be implemented to improve product launch performance. The most effective strategy is one that improves the PD capability (higher ability to find and fix problems) and the second most effective is to improve problem solving in manufacturing ramp-up.by Sappinandana Akamphon.Ph.D