Om Prakash Yadav

A fuzzy-AHP approach to prioritization of CS attributes in target planning for automotive product development

Understanding customer requirements and incorporating them into the conceptual vehicle design is the first step of automotive product development (PD). However, lack of quantitative data and undefined relationships between the attributes makes it difficult to develop a quantitative model for analyzing subjective customer satisfaction (CS) attributes. While researchers and practitioners have accomplished a significant success in terms of developing tool such as quality function deployment (QFD) to capture the voice of customers, and mathematical models for selecting engineering design alternatives, there is limited precedence in terms of prior works on customer satisfaction driven quality improvement target planning and prioritization of customer satisfaction attributes for target planning. This paper presents a fuzzy set theory based analytic hierarchy process (fuzzy-AHP) framework for prioritizing CS attributes in target planning. Furthermore, unlike prior QFD papers, we consider a broad range of strategic and tactical factors for determining the weights. These weights are then incorporated into target planning by identifying the gap in the current CS level. A case example from automotive industry is presented to demonstrate efficacy of the proposed methodology. The framework has been implemented on MS Excel(R) so that the industry can easily adopt it with limited amount of training and at no additional software cost.

Improving the NPD Process by Applying Lean Principles: A Case Study

Abstract: This article extends the new product development (NPD) literature by presenting a case study of a lean product development (LPD) transformation framework implemented at a U.S. based manufacturing firm. In a departure from typical LPD methods, in this article the design structure matrix and the cause and effect matrix are integrated into the lean transformation framework, allowing analysis of the underlying complexity of a product development (PD) system, and thus facilitating determination of the root causes of wasteful reworks. Several strategies to transform the current PD process into a lean process are discussed. Besides the two-phase improvement plan, a new organizational structure roadmap and a human resources plan are also suggested to support the recommended changes in the NPD process. The results of the first phase show a 32% reduction in PD cycle time due to the proposed NPD process. The article concludes with lessons learned and implications for engineering managers based on the case study.

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.

A review on risk assessment techniques for hydraulic fracturing water and produced water management implemented in onshore unconventional oil and gas production.

The objective of this paper is to review different risk assessment techniques applicable to onshore unconventional oil and gas production to determine the risks to water quantity and quality associated with hydraulic fracturing and produced water management. Water resources could be at risk without proper management of water, chemicals, and produced water. Previous risk assessments in the oil and gas industry were performed from an engineering perspective leaving aside important social factors. Different risk assessment methods and techniques are reviewed and summarized to select the most appropriate one to perform a holistic and integrated analysis of risks at every stage of the water life cycle. Constraints to performing risk assessment are identified including gaps in databases, which require more advanced techniques such as modeling. Discussions on each risk associated with water and produced water management, mitigation strategies, and future research direction are presented. Further research on risks in onshore unconventional oil and gas will benefit not only the U.S. but also other countries with shale oil and gas resources.

Reliability-based robust design optimization: A multi-objective framework using hybrid quality loss function

In this globally competitive business environment, design engineers are constantly striving to establish new and effective tools and techniques to ensure a robust and reliable product design. Robust design (RD) and reliability-based design approaches have shown the potential to deal with variability in the life cycle of a product. This paper explores the possibilities of combining both approaches into a single model and proposes a hybrid quality loss function-based multi-objective optimization model. The model is unique because it uses a hybrid form of quality loss-based objective function that is defined in terms of desirable as well as undesirable deviations to obtain efficient design points with minimum quality loss. The proposed approach attempts to optimize the product design by addressing quality loss, variability, and life-cycle issues simultaneously by combining both reliability-based and RD approaches into a single model with various customer aspirations. The application of the approach is demonstrated using a leaf spring design example. Copyright

Probabilistic Modeling of Fatigue Damage Accumulation for Reliability Prediction

A methodology for probabilistic modeling of fatigue damage accumulation for single stress level and multistress level loading is proposed in this paper. The methodology uses linear damage accumulation model of Palmgren-Miner, a probabilistic - curve, and an approach for a one-to-one transformation of probability density functions to achieve the objective. The damage accumulation is modeled as a nonstationary process as both the expected damage accumulation and its variability change with time. The proposed methodology is then used for reliability prediction under single stress level and multistress level loading, utilizing dynamic statistical model of cumulative fatigue damage. The reliability prediction under both types of loading is demonstrated with examples.

Energy and reliability oriented mapping for regular Networks-on-Chip

We formulate the problem of energy consumption and reliability oriented application mapping on regular Network-on-Chip topologies. We propose a novel branch-and-bound based algorithm to solve this problem. Reliability is estimated by an efficient Monte Carlo algorithm based on the destruction spectrum of the network. Simulation results demonstrate that reliability can be improved without sacrificing much of energy consumption.

A practical reliability allocation method considering modified criticality factors

Reliability allocation is a very critical step of product development process for setting achievable reliability goals. The majority of existing methods allocate system level failure rate target to subsystems or components instead of allocating failure rate reduction (improvement) targets. This approach of reliability allocation often allocates reliability goals lower than existing reliability levels. Further, the existing methods failed to effectively capture potential for improvement and impact of improvement efforts on failure effects while calculating reliability allocation weights. This paper investigates the limitations of existing approaches and proposes a modified criticality measure for allocating system level reliability improvement goal to subsystems. The modified criticality measure is developed considering non-linear phenomena for both severity rating and failure rate to capture potential for improvement. The failure rate reduction targets are assigned in proportion of improvement potential. A case example is presented to demonstrate the effectiveness of the proposed approach.

A Framework for Capturing and Analyzing the Failures Due to System/Component Interactions

To keep up with the speed of globalization and growing customer demands for more technology-oriented products, modern systems are becoming increasingly more complex. This complexity gives rise to unpredictable failure patterns. While there are a number of well-established failure analysis (physics-of-failure) models for individual components, these models do not hold good for complex systems as their failure behaviors may be totally different. Failure analysis of individual components does consider the environmental interactions but is unable to capture the system interaction effects on failure behavior. These models are based on the assumption of independent failure mechanisms. Dependency relationships and interactions of components in a complex system might give rise to some new types of failures that are not considered during the individual failure analysis of that component. This paper presents a general framework for failure modes and effects analysis (FMEA) to capture and analyze component interaction failures. The advantage of the proposed methodology is that it identifies and analyzes the system failure modes due to the interaction between the components. An example is presented to demonstrate the application of the proposed framework for a specific product architecture (PA) that captures interaction failures between different modules. However, the proposed framework is generic and can also be used in other types of PA. Copyright

Optimizing reliability-based robust design model using multi-objective genetic algorithm

Reliability-based robust design optimization (RBRDO) is one of the most important tools developed in recent years to improve both quality and reliability of the products at an early design stage. This paper presents a comparative study of different formulation approaches of RBRDO models and their performances. The paper also proposes an evolutionary multi-objective genetic algorithm (MOGA) to one of the promising hybrid quality loss functions (HQLF)-based RBRDO model. The enhanced effectiveness of the HQLF-based RBRDO model is demonstrated by optimizing suitable examples.