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Huang, Zhaofeng

Publications and source records attributed to Huang, Zhaofeng.

10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Addressing Uniqueness and Unison of Reliability and Safety for a Better Integration

Over time, it has been observed that Safety and Reliability have not been clearly differentiated, which leads to confusion, inefficiency, and, sometimes, counter-productive practices in executing each of these two disciplines. It is imperative to address this situation to help Reliability and Safety disciplines improve their effectiveness and efficiency. The paper poses an important question to address, "Safety and Reliability - Are they unique or unisonous?" To answer the question, the paper reviewed several most commonly used analyses from each of the disciplines, namely, FMEA, reliability allocation and prediction, reliability design involvement, system safety hazard analysis, Fault Tree Analysis, and Probabilistic Risk Assessment. The paper pointed out uniqueness and unison of Safety and Reliability in their respective roles, requirements, approaches, and tools, and presented some suggestions for enhancing and improving the individual disciplines, as well as promoting the integration of the two. The paper concludes that Safety and Reliability are unique, but compensating each other in many aspects, and need to be integrated. Particularly, the individual roles of Safety and Reliability need to be differentiated, that is, Safety is to ensure and assure the product meets safety requirements, goals, or desires, and Reliability is to ensure and assure maximum achievability of intended design functions. With the integration of Safety and Reliability, personnel can be shared, tools and analyses have to be integrated, and skill sets can be possessed by the same person with the purpose of providing the best value to a product development.

Huang, Zhaofeng↗
NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.

Safie, Fayssal↗
NASA NTRS2015

Addressing Unison and Uniqueness of Reliability and Safety for Better Integration

For a long time, both in theory and in practice, safety and reliability have not been clearly differentiated, which leads to confusion, inefficiency, and sometime counter-productive practices in executing each of these two disciplines. It is imperative to address the uniqueness and the unison of these two disciplines to help both disciplines become more effective and to promote a better integration of the two for enhancing safety and reliability in our products as an overall objective. There are two purposes of this paper. First, it will investigate the uniqueness and unison of each discipline and discuss the interrelationship between the two for awareness and clarification. Second, after clearly understanding the unique roles and interrelationship between the two in a product design and development life cycle, we offer suggestions to enhance the disciplines with distinguished and focused roles, to better integrate the two, and to improve unique sets of skills and tools of reliability and safety processes. From the uniqueness aspect, the paper identifies and discusses the respective uniqueness of reliability and safety from their roles, accountability, nature of requirements, technical scopes, detailed technical approaches, and analysis boundaries. It is misleading to equate unreliable to unsafe, since a safety hazard may or may not be related to the component, sub-system, or system functions, which are primarily what reliability addresses. Similarly, failing-to-function may or may not lead to hazard events. Examples will be given in the paper from aerospace, defense, and consumer products to illustrate the uniqueness and differences between reliability and safety. From the unison aspect, the paper discusses what the commonalities between reliability and safety are, and how these two disciplines are linked, integrated, and supplemented with each other to accomplish the customer requirements and product goals. In addition to understanding the uniqueness in reliability and safety, a better understanding of unison and commonalities will further help in understanding the interaction between reliability and safety. This paper discusses the unison and uniqueness of reliability and safety. It presents some suggestions for better integration of the two disciplines in terms of technical approaches, tools, techniques, and skills to enhance the role of reliability and safety in supporting a product design and development life cycle. The paper also discusses eliminating the redundant effort and minimizing the overlap of reliability and safety analyses for an efficient implementation of the two disciplines.

Huang, Zhaofeng↗
NASA NTRS2012

Failure detection system risk reduction assessment

A process includes determining a probability of a failure mode of a system being analyzed reaching a failure limit as a function of time to failure limit, determining a probability of a mitigation of the failure mode as a function of a time to failure limit, and quantifying a risk reduction based on the probability of the failure mode reaching the failure limit and the probability of the mitigation.

Aguilar, Robert B.↗
NASA NTRS1995

Computing Tolerance Factors And Noncentral t Distribution

TF, Tolerance Factors and Noncentral t Distribution computer program, computes tolerance factor from normal-distribution sample for arbitrarily specified coverage probability, confidence level, and any positive (integer or noninteger) number of degrees of freedom. Used extensively in engineering and quality analyses. Used in place of reference tables. Written in Microsoft QuickBasic v2.0.

Huang, Zhaofeng↗
NASA NTRS1995

Program Implements Variable-Sampling Procedures

MIL-STD-414 Variable Sampling Procedures (M414) computer program developed to automate calculations and acceptance/rejection procedures of MIL-STD-414, "Sampling Procedures and Tables for Inspection by Variables for Percent Defective." M414 automates entire calculation-and-decision process by use of computational algorithms determining threshold acceptability values for lots. Menu-driven and user-friendly. Reduces burden of manual operations, promoting variable-sampling practice in industry in lieu of "go/no-go" inspection. Written in BASIC.

Huang, Zhaofeng↗
NASA NTRS1994

Inspection planning development: An evolutionary approach using reliability engineering as a tool

This paper proposes an evolutionary approach for inspection planning which introduces various reliability engineering tools into the process and assess system trade-offs among reliability, engineering requirement, manufacturing capability and inspection cost to establish an optimal inspection plan. The examples presented in the paper illustrate some advantages and benefits of the new approach. Through the analysis, reliability and engineering impacts due to manufacturing process capability and inspection uncertainty are clearly understood; the most cost effective and efficient inspection plan can be established and associated risks are well controlled; some inspection reductions and relaxations are well justified; and design feedbacks and changes may be initiated from the analysis conclusion to further enhance reliability and reduce cost. The approach is particularly promising as global competitions and customer quality improvement expectations are rapidly increasing.

Graf, David A.↗
NASA NTRS1991

Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately

The mathematical relationships between the shape parameter Beta and estimates of reliability and a life limit lower bound for the two parameter Weibull distribution are investigated. It is shown that under rather general conditions, both the reliability lower bound and the allowable life limit lower bound (often called a tolerance limit) have unique global minimums over a range of Beta. Hence lower bound solutions can be obtained without assuming or estimating Beta. The existence and uniqueness of these lower bounds are proven. Some real data examples are given to show how these lower bounds can be easily established and to demonstrate their practicality. The method developed here has proven to be extremely useful when using the Weibull distribution in analysis of no-failure or few-failures data. The results are applicable not only in the aerospace industry but anywhere that system reliabilities are high.

Huang, Zhaofeng↗
NASA NTRS1990

Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately

The mathematical relationships between the shape parameter Beta and estimates of reliability and a life limit lower bound for the two parameter Weibull distribution are investigated. It is shown that under rather general conditions, both the reliability lower bound and the allowable life limit lower bound (often called a tolerance limit) have unique global minimums over a range of Beta. Hence lower bound solutions can be obtained without assuming or estimating Beta. The existence and uniqueness of these lower bounds are proven. Some real data examples are given to show how these lower bounds can be easily established and to demonstrate their practicality. The method developed here has proven to be extremely useful when using the Weibull distribution in analysis of no-failure or few-failures data. The results are applicable not only in the aerospace industry but anywhere that system reliabilities are high.

Huang, Zhaofeng↗