Nanua Singh

Cellular Manufacturing Systems Design, Planning and Control

No abstract

A fuzzy logic based approach to reliability improvement estimation during product development

Abstract During early stages of product development process, a vast amount of knowledge and information is generated. However, most of it is subjective (imprecise) in nature and remains unutilized. This paper presents a formal structure for capturing this information and knowledge and utilizing it in reliability improvement estimation. The information is extracted as improvement indices from various design tools, experiments, and design review records and treated as fuzzy numbers or linguistic variables. Fuzzy reasoning method is used to combine and quantify the subjective information to map their impact on product reliability. The crisp output of the fuzzy reasoning process is treated as new evidence and incorporated into a Bayesian framework to update the reliability estimates. A case example is presented to demonstrate the proposed approach.

Hazard rate estimation from incomplete and unclean warranty data

Abstract Warranty data are a rich source of information for feedback on product reliability. However, two-dimensional automobile warranties that include both time and mileage limits, pose two interesting and challenging problems in reliability studies. First, warranty data are restricted only to the reported failures within warranty coverage and such incompleteness can lead to inaccurate estimates of field failure rate or hazard rate. Second, factors such as inexact time/mileage data and vague reported failures in a warranty claim make warranty data unclean that can suppress inherent failure pattern. In this paper we discuss two parameter estimation methods that address the incompleteness issue. We use a simulation-based experiment to study these estimation methods when departure from normality and varying amount of truncation exists. Using a life cycle model of the vehicle, we also highlight and explore issues that lead to warranty data not being very clean. We then propose a five-step methodology to arrive at meaningful component level empirical hazard plots from incomplete and unclean warranty data.

Reliability demonstration test planning: A three dimensional consideration

Increasing customer demand for reliability, fierce market competition on time-to-market and cost, and highly reliable products are making reliability testing more challenging task. This paper presents a systematic approach for identifying critical elements (subsystems and components) of the system and deciding the types of test to be performed to demonstrate reliability. It decomposes the system into three dimensions, (i.e. physical, functional and time) and identifies critical elements in the design by allocating system level reliability to each candidate. The decomposition of system level reliability is achieved by using criticality index. The numerical value of criticality index for each candidate is derived based on the information available from failure mode and effects analysis (FMEA) document or warranty data from a prior system. It makes use of this information to develop reliability demonstration test plan for the identified (critical) failure mechanisms and physical elements. It also highlights the benefits of using prior information in order to locate critical spots in the design and in subsequent development of test plans. A case example is presented to demonstrate the proposed approach.

Creativity and innovation in durable product development

In this paper we are proposing a framework for integrating the creativity and innovation aspects for durable product development. Various creativity and innovation methodologies are discussed.

A modeling framework for assessing the impact of new time/mileage warranty limits on the number and cost of automotive warranty claims

Abstract An automobile with over 7000 parts is a highly complex product. In spite of employing the best quality and reliability practices during product development, manufacturing, and assembly, unexpected failures during warranty period do occur and cost automobile companies billions of dollars annually in warranty alone. Warranty coverage for an automobile is generally stated in terms of mileage (in miles) and time (in months or years). The coverage expires when any of the two limits is crossed. Any change in warranty coverage too, influences warranty cost significantly. However, changes made to warranty coverage are often market driven. In either case, a company needs to plan for maintaining a large cash reserve to pay for the warranty services on their products. In this paper, we present a simple method to assess the impact of new time/mileage warranty limits on the number and cost of warranty claims for components/sub-systems of a new product. We highlight the use of mileage accumulation rates of a population of vehicles to arrive at claims per thousand vehicles, sold with new time/mileage warranty limits. We also discuss the bias in warranty cost estimates that may result in using cumulative cost per repair information. We recommend the use of incremental cost per repair especially when populations with different mileage accumulation rates are under consideration. Application examples are included to illustrate the use of the proposed methodology.

A methodology for integrating design for quality in modular product design

With inspection-based quality control techniques, the quality of a product remains undetermined until the product is built and tested, an expensive process that also delays the release of new products to the market. This paper brings the quality issues at early stages of product development, and enhances the existing work on design for quality by integrating with modular design concepts. Conceptually, modular design theory optimizes product quality at the conceptual phase by considering the underlying principles of axiomatic design and robust design along with the perceived quality of the product. Fuzzy logic is employed to estimate cost and quality performance indices of the candidate modules by analysing ambiguous product information at the conceptual stage. We consider two objectives for product modularization: minimization of modularization costs, and maximization of overall product quality. The Chebychevs goal programming model is used to solve the multi-objective optimization problem. The methodology is demonstrated using an example of a coffeemaker. The results of the case study identify the optimal number of modules, which are intuitive and also offer more design resolution for forming the product development teams.

Customer-Rush Near Warranty Expiration Limit, and Nonparametric Hazard Rate Estimation From Known Mileage Accumulation Rates

Time or mileage data obtained from warranty claims are generally more accurate for hard failures than for soft failures. For soft failures, automobile users sometimes delay reporting the warranty claim until the warranty coverage is about to expire. This results in an unusually high number of warranty claims near the end of warranty coverage. Because such a phenomenon of customer-rush near the warranty expiration limit occurs due to user behavior rather than due to the vehicle design, it creates a bias in the warranty dataset. Design improvement activities that use field reliability studies based on such data can potentially obtain a distorted picture of the reality, and lead to unwarranted, costly design changes. Research in the area of field reliability studies using warranty data provides several methods for warranty claims resulting from hard failures, and assumes reported time or mileage as actual time or mileage at failure. In this article, the phenomenon of customer-rush near the warranty expiration limit is addressed for arriving at nonparametric hazard rate estimates. The proposed methodology involves situations where estimates of mileage accumulation rates in the vehicle population are available. The claims influenced by soft failures are treated as left-censored, and are identified using information in technician comments about the repair carried out plus, if required, a more involved engineering analysis of field returned parts. Maximum likelihood estimates for the hazard function and their confidence limits are then obtained using Turnbulls iterative procedure. An application example illustrates use of the proposed methodology

Integrated product and process design: a multi-objective modeling framework

Abstract In this paper we present an analytical multi-objective framework for the concurrent design of product and processes. The objective is to simultaneously consider the tolerance specification on the product or the component dimensions along with the selection of the manufacturing processes. For this purpose we consider three objectives: to minimize unit cost, to minimize quality loss and to minimize manufacturing lead time. We characterize the properties of the non-dominated solutions. These solutions provide flexibility needed in an agile manufacturing environment. The min–max approach is used to obtain trade-off solutions.

Modeling and analysis of automobile warranty data in presence of bias due to customer-rush near warranty expiration limit

Abstract Automobile users experiencing soft failures, often delay reporting of warranty claims till the coverage is about to expire. This results into a customer-rush near the warranty expiration limit leading to an occurrence of ‘spikes’ in warranty claims towards the end of warranty period and thereby introducing a bias into the dataset. At the same time, an occurrence of manufacturing/assembly defects in addition to the usage related failures, lead to ‘spikes’ in warranty claims near the beginning of the warranty period. When such data are used to capture the field failures for obtaining feedback on product quality/reliability, it may lead product or reliability engineers to potentially obtain a distorted picture of the reality. Although in reliability studies from automobile warranty data, several authors have addressed the well-recognized issues of incomplete and unclean nature of warranty data, the issue of ‘spikes’ has not received much attention. In this article, we address the issue of ‘spikes’ in the presence of the incomplete and unclean nature of warranty data and provide a methodology to arrive at component-level empirical hazard plots from such automobile warranty data.