Search Results for quality management

This article provides guidelines for the assessment of model quality in materials science and engineering. It discusses the fundamentals of model quality assessment and the calibration of mechanistic material models. The article reviews the considerations for the model verification during software implementation planning to identify suitable programs, software components, and programming languages. It describes the validity tests used in model validation, including boundary-value tests, degenerate problem tests, sensitivity tests, and benchmarking. The article also presents an example of model calibration, verification, and validation for the prediction of martensite start temperature of steels.

This article describes how design can unfavorably affect product quality. It provides information on the total quality management philosophy, emphasizing the principles of quality management. The article discusses various methods for evaluating a product design for quality. It presents design guidelines that are intended to provide products with a potential for higher levels of quality.

This article defines quality, quality assurance, quality control, and quality management of processes, products, and services. It describes the evolution of quality control and quality assurance in the coatings industry. The article also discusses the standards, quality programs, and certifications in the coatings industry.

Value analysis (VA) is a team problem-solving process to improve the value of a product from the viewpoint of a user. This article presents a comparison between VA and total quality management in materials selection and design. It discusses the key attributes, concepts, and activities of the VA. The application of value engineering in U.S. government contracts and the construction industry is reviewed. The article describes the eight phases of the VA process: preparation, information, analysis, creation, synthesis, development, presentation and report, and implementation and follow-up. It presents case studies that illustrate the materials-related aspects of the VA process.

The purpose of accreditation is to evaluate and assure high-quality results from suppliers of products or services without incurring the costs associated with auditing each supplier. This article describes laboratory accreditation based on the general requirements of International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) Guide 25, "General Requirements for the Competence of Calibration and Testing Laboratories." The Guide 25 is a balanced standard that addresses quality system requirements of ISO 9000 and the technical requirements needed to perform testing or calibration. The article describes an accreditation process that would enhance the international acceptance of test data for mechanical testing laboratories.

The qualification of additive manufacturing (AM) processes and the certification of AM parts is recognized as a significant impediment to the rapid, low-cost deployment of AM manufacturing. The challenges are multifaceted; however, it is an attempt to apply conventional qualification approaches to an inherently different process that has caused the most difficulty. This article examines the conventional qualification methodology and explores how the unique characteristics of AM pose a set of qualification challenges. The extant approach to the qualification of AM processes is described, followed by a discussion on a possible future state.

This article describes the four basic steps of the purchasing process of cast components. These steps include defining requirements and developing a purchasing plan; requesting and evaluating bids from potential sources; selecting a source and negotiating contract terms; and carrying out the contract and pursuing continuous improvement. It provides guidance on purchasing cast components and explains specific issues and approaches that have proven to be useful in purchasing castings. The article presents a list of the most significant considerations when attempting to determine the overall cost and design requirements of a metal casting.

This article aims to provide a basic understanding of the fundamental principles for additive manufacturing (AM) processes, and to give clear definitions for terms and nomenclature associated with AM technology.

The aviation industry has been driving the use of additive manufacturing (AM), moving from one-off demonstrator or pathfinder components toward higher-volume serial production applications. This article presents an introduction to AM in aviation, explaining how aviation requirements apply to AM. It also presents advancements, standards, and future expectations of aviation.

This article briefly introduces the concepts of failure analysis and root cause analysis (RCA), and the role of failure analysis as a general engineering tool for enhancing product quality and failure prevention. It reviews four fundamental categories of physical root causes, namely, design deficiencies, material defects, manufacturing/installation defects, and service life anomalies, with examples. The article describes several common charting methods that may be useful in performing an RCA. It also discusses other failure analysis tools, including review of all sources of input and information, people interviews, laboratory investigations, stress analysis, and fracture mechanics analysis. The article concludes with information on the categories of failure and failure prevention.

Additive manufacturing (AM) creates parts layer by layer directly from three-dimensional computer-aided design data. This article discusses systematic ways to address the challenges in AM data integration by exploring various AM-specific data-integration scenarios that can improve the current AM ecosystem. Representative AM data sources are also described. A reference framework that captures the heterogenous AM data sources and existing data-integration mechanisms are used. General data-integration practices—based on existing manufacturing data and lab information system integration experiences—are recommended to automate AM data flow, operations, and development. Lastly, the article discusses the seven steps in the big-data-integration workflow.

The objective of dimensional management is to create a design and process that absorbs as much variation as possible without affecting the function of the product. This article describes the steps followed by the dimensional management process. These include defining product dimensional requirements, determining process and product requirements, ensuring accurate documentation, developing a measurement plan that validates product requirements, establishing manufacturing capabilities versus design intent, and establishing production-to-design feedback loop. The article discusses the simulation model in terms of a functional feature product model, component part variation, assembly method variation, measurement schemes, and assembly sequences.

This article discusses Allenby's two streams for environmental aspects of design: generic and specific concerns. Generic concerns include guidelines that provide the structure in which specific techniques can be developed and used. Specific methods are environmentally responsible for design and specific information that engineers can use. These methods include life cycle assessment, environmental impact assessment, quality function deployment, design for “X”, failure modes and effects analysis, and design for disassembly.

This article describes design factors for products used in engineering applications. The article groups these factors into three categories: functional requirements, analysis of total life cycle, and other major factors. These categories intersect and overlap, constituting a major challenge in engineering design. Performance specifications, risk and hazard analysis, design process, design for manufacture and assembly, design for quality, reliability in design, and redesign are considered for functional requirements. Life-cycle analysis considers raw-material extraction from the earth and product manufacture, use, recycling (including design for recycling), and disposal. The other major factors considered include evaluation of the current state of the art for a given design, designing to codes and standards, and human factors/ergonomics.

This article presents a background of green chemistry and green coatings, and a summary of the key concerns of the green coating procurement process. It includes a discussion on green marketing and the seven sins of greenwashing, an overview of the environmental certification standards and regulatory environments, and the importance of performance during the duty cycle.

This article briefly introduces the concepts of failure analysis, including root-cause analysis (RCA), and the role of failure analysis as a general engineering tool for enhancing product quality and failure prevention. It initially provides definitions of failure on several different levels, followed by a discussion on the role of failure analysis and the appreciation of quality assurance and user expectations. Systematic analysis of equipment failures reveals physical root causes that fall into one of four fundamental categories: design, manufacturing/installation, service, and material, which are discussed in the following sections along with examples. The tools available for failure analysis are then covered. Further, the article describes the categories of mode of failure: distortion or undesired deformation, fracture, corrosion, and wear. It provides information on the processes involved in RCA and the charting methods that may be useful in RCA and ends with a description of various factors associated with failure prevention.

The basic quality analysis tools are cause-and-effect diagrams, check sheets, control charts, histograms, Pareto charts, scatter diagrams, and run charts. This article reviews how basic quality analysis tools are built upon to become a more advanced set of quality tools. It describes the advanced quality tools: advanced product quality planning, failure mode and effects analysis, control planning, measurement systems analysis, lean tools, statistical process control, production viability and tryout, and Six Sigma.