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Methodologies/Tools That the Auditor Should Be Familiar With
Published in D. H. Stamatis, Automotive Audits, 2021
FMEA is an inductive reasoning (forward logic) single point of failure analysis and is a core task in reliability engineering, safety engineering, and quality engineering. It is a bottom-top approach as opposed to fault tree analysis which is top-bottom.
Introduction
Published in Ron Burch, Resilient Space Systems Design: An Introduction, 2019
Reliability engineering provides designers with the mathematical models to make quantitative predictions of the system reliability based on component failure rate data and the system's design and operation. These reliability estimates are derived from failure rate models based on measured and historical component test and operational data which then become a part of the system's operational availability. The reliability metric is a probability of system (or mission) success (or failure) over some defined time period of interest such as satellite design life. In Chapter 5, a methodology is provided using system design information coupled with a description of external threats to yield an expected value of the residual system capability that can be calculated for a specific threat or threat scenario, similar to a reliability prediction.
Maintenance Professionals
Published in José Baptista, Industrial Maintenance, 2019
The maintenance management function must relate to the following levels of company: Factory floor: encompasses the management of the execution of the maintenance itself including methods, processes, plans, quality control, safety and analysis of operational performance indicators.Maintenance department: economic and strategic management by defining the maintenance strategy, including all aspects of maintenance and reliability engineering, monitoring relevant performance indicators, management of human and material resources, subcontracting policy, legal and regulatory aspects, etc.Executive level: participation in the definition of the corporate plan for the management of physical assets with regard to the policy for the replacement of assets at the end of their useful lives, acquisition of new equipment, development of human resources, etc.
Reliability Analysis of Microgrids: Evaluation of Centralized and Decentralized Control Approaches
Published in Electric Power Components and Systems, 2023
Selahattin Garip, Melih Bilgen, Necmi Altin, Saban Ozdemir, Ibrahim Sefa
Reliability engineering is a field that focuses on designing and improving the reliability of systems and products, using various techniques such as testing, statistical analysis, and modeling. The process of evaluating the reliability of a system or product by analyzing its performance and failure data is called reliability analysis. The goal of reliability analysis is to identify potential failure modes, estimate the probability and frequency of failures, and develop strategies to improve the reliability of the system or product. Reliability analysis can be performed at various stages of the product life cycle, including design, development, testing, and operation. It involves a combination of statistical methods, modeling techniques, and engineering principles to identify and quantify the sources of unreliability and improve the performance and durability of the system or product. The reliability analysis typically involves the data collection, data analysis, failure prediction and improvement strategies steps. The reliability analysis is a critical tool for ensuring the safety, performance, and durability of systems and products.
Quality 4.0—the challenging future of quality engineering
Published in Quality Engineering, 2020
Avigdor Zonnenshain, Ron S. Kenett
Integrating reliability engineering into quality engineering programs can be promoted through training of quality engineers in reliability engineering based on the above models and based on data and engineering models. Quality engineering programs should therefore include reliability engineering programs. For a model linking field data with reliability assessments at the development's stages see Halabi, Kenett, and Sacerdote (2017, 2018). Most of reliability engineering models and practices deal with the assessment of the probability of failure of components and systems and predicting the life span of these components and systems. It is claimed that in the new era of innovative technologies we should analyze and predict the evolution of technologies. The end of life of technologies is not due to physical failure, but due to outdated technology, or replacing technology by a new one of the competitors. This new and challenging area of evolution of technologies are described in Chapter 22 of Kenett, Swarz, and Zonnenshain (2020). It presents an opportunity for the quality and reliability engineering in the fourth industrial revolution.
Examining medical-surgical nurse shift-to-shift handoffs to identify process, failures, and effects
Published in IISE Transactions on Healthcare Systems Engineering, 2019
Katherine Ernst, Sara McComb, Cathaleen Ley
The purpose of this study was to identify a generic process map of the general medical unit nurse shift-to-shift handoff as well as cause and effect relationships resulting from handoff process failures. This purpose supports a broader goal of identifying causal explanations of how the nursing handoff process may impact the nurses’ performance of the handoff task and subsequent direct and indirect nursing care activities. Such impacts may occur immediately or result in latent effects. To conduct this research, failure mode and effects analysis (FMEA) was used as an organizing framework for conducting secondary qualitative analysis on an existing dataset comprised of five focus group discussions with medical-surgical nurses. The discussions focused on nursing shift-to-shift handoff failures and the corresponding effects on subsequent nursing care activities. The process FMEA method, originating from reliability engineering, is a team-based qualitative analysis technique where the process components are mapped and then systematically analyzed to identify cause and effect relationships involved in the process’s failures for the purpose of improving design and function. Analyzing the nurses’ descriptions of the handoff with the FMEA framework as a guide may facilitate a more process-oriented assessment of the handoff and reveal causal linkages. Such causal explanations may prove useful in providing valuable information for the design of handoff improvement efforts and measurement approaches.