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

Ph.DDOCTOR OF PHILOSOPH

Some contributions to modeling usage sensitive warranty servicing strategies and their analyses

Providing a warranty as a part of a product\u27s sale is a common practice in industry. Parameters of such warranties (e.g., its duration limits, intensity of use) must be carefully specified to ensure their financial viability. A great deal of effort has been accordingly devoted in attempts to reduce the costs of warranties via appropriately designed strategies to service them. many such strategies, that aim to reduce the total expected costs of the warrantor or / and are appealing in other ways such as being more pragmatic to implement - have been suggested in the literature. Design, analysis and optimization of such servicing strategies is thus a topic of great research interest in many fields. In this dissertation, several warranty servicing strategies in two-dimensional warranty regimes, typically defined by a rectangle in the age-usage plane, have been proposed, analyzed and numerically illustrated. Two different approaches of modeling such usage sensitive warranty strategies are considered in the spirit of Jack, Iskandar and Murthy (2009) and Iskandar (2005). An `Accelerated Failure Time\u27 (AFT) formulation is employed to model product degradation resulting due to excessive usage rate of consumers. The focus of this research is on the analysis of warranty costs borne by the manufacturer (or seller or third party warranty providers) subject to various factors such as product\u27s sale price, consumer\u27s usage rate, types and costs of repair actions. By taking into account the impact of the rate of use of an item on its lifetime, a central focus of our research is on warranty cost models that are sensitive to the usage rate. Specifically, except the model in Chapter 4 where the rate at which an item is used is considered to be a random variable; all other warranty servicing policies that we consider, have usage rate as a fixed parameter, and hence are policies conditional on the rate of use. Such an approach allows us to examine the impact of a consumer\u27s usage rate on the expected warranty costs. For the purpose of designing warranties, exploring such sensitivity analysis may in fact suggest putting an upper limit on the rate of use within the warranty contract, as for example in case of new or leased vehicle warranties. A Bayesian approach of modeling 2-D Pro-rated warranty (PRW) with preventive maintenance is considered and explored in the spirit of Huang and Fang (2008). A decision regarding the optimal PRW proportion (paid by the manufacturer to repair failed item) and optimal warranty period that maximizes the expected profit of the rm under different usage rates of the consumers is explored in this research. A Bayesian updating process used in this context combines expert opinions with market data to improve the accuracy of the parameter estimates. The expected profit model investigated here captures the impact of juggling decision variables of 2-D pro-rated warranty and investigates the sensitivity of the total expected profit to the extent of mis-specification in prior information

A review on maintenance optimization

To this day, continuous developments of technical systems and increasing reliance on equipment have resulted in a growing importance of effective maintenance activities. During the last couple of decades, a substantial amount of research has been carried out on this topic. In this study we review more than two hundred papers on maintenance modeling and optimization that have appeared in the period 2001 to 2018. We begin by describing terms commonly used in the modeling process. Then, in our classification, we first distinguish single-unit and multi-unit systems. Further sub-classification follows, based on the state space of the deterioration process modeled. Other features that we discuss in this review are discrete and continuous condition monitoring, inspection, replacement, repair, and the various types of dependencies that may exist between units within systems. We end with the main developments during the review period and with potential future research directions

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

Towards solutions for assistive technology

Introduction What is assistive technology? The agreed World Health Organisation definition is "Assistive technology can be defined as “any piece of equipment, or product, whether it is acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities” (WHO, 2011) The array of possible assistive technology products and solutions reflects the diversity of the needs of people with disabilities – ranging from digital technologies that can support social engagement, communication, employment, learning, memory, planning and safe guarding services through to products and devices that support mobility and personal care requirements. Typically as the complexities of assistive technology solutions increase, so do the costs and potential risks (if not appropriately set up or maintained). This document is primarily focused on the Assistive Technology solutions derived from aids and equipment. Home and vehicle modifications and prosthetics have not yet been explored in the same level of detail and will be subject of further work. Proposed approach The proposed assistive technology service approach has been developed in line with the strategic goals of the NDIA. It is one aspect of a broader strategic approach the NDIA has to using technologies to enhance its engagement and management of relationships, services and supports with suppliers, providers, participants and the Australian community. The NDIA’s goal is to use technology in its various forms to ensure that services, supports, and communications between all stakeholders are as streamlined as possible and services are timely and effective. This document outlines the elements of a proposed service delivery approach for individuals to access assistive technology solutions and is based on the three key objectives outlined above

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

BIONOMER PILOT PLANT

The purpose of this project is to develop a pilot-scale process for the bacterial production of methacrylic acid (MAA) and methyl ethyl ketone (MEK) from biomass feedstocks and the subsequent purification steps. The pilot plant will also be located on site at a sugar cane refinery in Brazil where the feedstock should be inexpensive and readily available. Although these sugar cane refineries only operate for 9 months each year, molasses can be stored so that the pilot plant runs year-round. To obtain useful information about the feasibility and scalability of the process, 30 M kg/yr of each product will be produced. The products will be tested for purity and samples will be sent out to consumers to demonstrate the quality of the product. The MAA and MEK must be of the same purity generated by current commercial processes. The pilot plant will be designed in three major parts. The first part consists of the bacterial fermentors that are used to produce and scale up MAA and MEK production. Relatively little is currently known about the efficiency of production of MAA and MEK by E. coli and this part of the plant will provide critical data about conditions required for the bacteria as well as production rates. The second part of the plant consists of the MAA purification process. Many options will be considered for the purification steps, many of which will have to be modeled in ASPEN because MAA is usually not produced in the aqueous phase. The final section of the plant will be used for MEK purification. To reduce plant costs, the design will try to share equipment between the two purification processes. The main goal of the plant is to obtain data and demonstrate feasibility, not to demonstrate sustainable profitability. Estimates for total capital investment and show that the plant will not be profitable for the first five years of operation, but the valuable data gained from the operation will be used to design the larger, more efficient, full-scale plant. The total capital investment required for the plant is approximately $ 6.33 million. Returns generated from sales are minimal compared to the capital investment and operating costs. A full scale plant is expected to be profitable over time because of economies of scale and the price of inputs and outputs of the process

Bandas de confianza simultáneas para la estimación de los costos de garantía descontados para sistemas coherentes bajo reparo mínimo

La selección de un programa de garantía para un producto nuevo en el mercado genera al fabricante costos adicionales diferentes a aquellos inherentes al proceso de fabricación. Esto hace que sea necesario establecer los costos de garantía para un periodo de tiempo dado, de manera que el fabricante puede estimar el nivel de reserva necesario para atender los reclamos futuros por garantía. En particular se consideran los costos de garantía denominados descontados. Los modelos desarrollados para este tipo de costos incorporan la edad del producto en el momento del reclamo por garantía y se pueden estudiar a través del proceso estocástico conocido como modelo de tiempo de vida general. En la práctica, la mayoría de los productos son sistemas compuestos por varias componentes. Cuando el producto o sistema es reparable y sobre sus componentes se realizan acciones de mantenimiento que implican costos, resulta de interés modelar el impacto de tales acciones sobre los costos de garantía del sistema. Uno de los atractivos principales del modelo de tiempo de vida general, es que bajo éste, se puede evaluar la evolución del sistema bajo el enfoque conocido como aproximación física, que permite modelar en el tiempo el proceso de falla del sistema o producto bajo diferentes niveles de información, y en particular modelar el proceso de tasa de falla, que es el aspecto más importante de estos modelos. Así, la diferencia primordial entre el modelo de confiabilidad clásico, conocido como aproximación estadística, y la aproximación física, es el nivel de información: mientras que en el segundo se observa el proceso de falla al nivel de las componentes, en el primero sólo se observa la falla del sistema. Esto hace que el proceso de falla cambie de una aproximación a otra, debido a que cambian los procesos de tasas de falla asociados, así, en la aproximación estadística la tasa de falla es una función determinística, mientras que en la aproximación física la tasa de falla es una proceso estocástico. El objetivo principal de este trabajo es desarrollar bandas de confianza simultáneas para el costo medio de garantía descontado en sistemas coherentes bajo reparo mínimo físico, esto es, cuando el sistema es observado al nivel de sus componentes, usando métodos computacionales intensivos basados en remuestreo. Para ello, con base en el marco teórico de los procesos martingala y el teorema de límite central de remuestreo (CLRT) sobre procesos estocásticos, se prueban las condiciones de éste último en los procesos de costos de garantía descontados. Un estudio de simulación Monte Carlo se realiza para evaluar el desempeño en muestras finitas del método propuesto a través de las probabilidades de cobertura alcanzadas. Los resultados en los escenarios considerados muestran que las bandas de confianza basadas en remuestreo tienen probabilidades de cobertura con valores cercanos a los esperados, en particular para aquellas basadas en muestras con más de 100 sistemas donde el número de remuestras usada para la aproximación es grande.Abstract: The selection of a warranty program for a new product on the market generates additional costs to the manufacturer other than those inherent to the manufacturing process, what makes necessary to establish warranty costs for a given period of time, thus, the manufacturer can estimate the required level of reserves to deal with the future warranty claims. Particularly, we consider the so-called discounted warranty costs. The models developed for this kind of costs incorporates the age of the product at the time of the warranty claim and it can be studied through the stochastic process known as the General Lifetime Model. In practice, most of the products are systems consisting of several components. When the product or system is repairable and maintenance actions in the components involving costs are made, it is interesting to model the impact of such actions on the system warranty costs. One of the main appeals of the General Lifetime Model is that it can be evaluated the evolution of the system under the so-called physical approach, which allows to model through the time the failure process of the system or product given different levels of information, in particular, it allows to model the failure rate process, which is the most important aspect of these models. Thus, the main difference between the classical reliability model -known as the statistical approach- and the physical approach is the level of information: while the latter shows the failure process at the level of the components, in the former only the system failure is observed. This differentiates the failure process from an approach to the other, due to that the associated failure rate processes change, so that the failure rate in the statistical approach is a deterministic function, while the failure rate in the physical approach is a stochastic process. The main objective of this thesis is to develop simultaneous confidence bands for the mean of the discounted warranty cost for coherent systems under physical minimum repair, i.e., when the system is observed at the level of its components, using computer intensive methods based on resampling. In doing so, we proof that the discounted warranty cost processes fulfill the conditions of the central limit resampling theorem (CLRT) for stochastic processes, based on the theoretical framework of martingale processes. A Monte Carlo simulation study to evaluate the finite sample performance of the proposed method is performed through the achieved coverage probability. The results show that in the considered scenarios the confidence bands based on resampling have coverage probabilities close to the expected values, in particular, those based on samples sizes with more than 100 systems where the number of resamples used for the approximation is large.Doctorad