This webinar provided an overview of next-generation additive manufacturing (AM) technologies, its capabilities, and research challenges, with particular emphasis on research needs and challenges in process monitoring and quality control.
The discovery of lean production methods used at leading Japanese companies is not a new event. Several American companies that were awarded the Deming Application Prize in the early 1980s by the Union of Japanese Scientists and Engineers (JUSE) had spent significant time studying Japanese management practices related to the process of continual improvement and Hewlett-Packard was one of the pioneers in implementing these methods in its U.S.-based manufacturing facilities in the early 1980s. However, the publication of the MIT study The Machine that Changed the World and other books by academics greatly enhanced the reputation of lean methods and this has caused many organizations to seek productivity improvement through the application of such methods.
Managing for quality requires a systems approach that includes all components of a comprehensive product: hardware, software, service and people processes. Such quality systems are designed using technologies that include: applied statistics, process management, reliability engineering, information systems, and data base management. When problems occur, diagnostic analysis is required to contain the issue as well as develop prompt corrective action as well as effective preventive action to eliminate recurrence of the issue.
Estimation of system reliability is generally based on system structures and component reliability estimates. However, the component reliability estimates are often uncertain due to insufficient failure data or limited testing times, and thus, the associated system reliability estimate exhibits uncertainty as well. The variance is often used to quantify the uncertainty of system reliability estimates. This webinar introduces a non-parametric based modeling approach to estimating the system reliability base on the limited component lifetime data.
This is a two-part webinar series that covers the basics and fundamentals of reliability engineering. Part 1 begins with an introduction of reliability - the definition and reliability characteristics and measurements.
This is the second of a two-part webinar series that covers the basics and fundamentals of reliability engineering. Part 2 covers reliability calculation, estimation of failure rates and understanding of the implications of failure rates on system maintenance and replacements. It will also cover the most important and practical failure time distributions and how to obtain the parameters of the distributions and interpretations of these parameters.