Quality Control and Reliability Engineering – Webinar archive

Some Practical Procedures for Quality and Reliability Monitoring of Industrial Processes

A Webinar presented jointly by the Quality Control and Reliability Division and the Manufacturing and Design Division
March 30, 2022
Presenter: Dr. Min Xie

Covid-19 has shown us the drawbacks of our supply chains and exposed our vulnerabilities. "self-sufficiency," can only be realized by making SMMs an integral part of the larger manufacturing ecosystem. Local Manufacturing, a paradigm that relates the local skills, resources, and SMMs is needed for making our country self-sufficient. We show how IIoT, AI&ML, and Networks will become the backbone of such a futuristic manufacturing ecosystem and bring four different areas of research together to pave the foundation for the next generation manufacturing.

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Damage Assessment on Post-Hurricane Imagery

Disaster damage assessment in the U.S. is increasingly important as natural hazard-induced disasters (e.g., hurricanes) are breaking records nearly every year, costing the nation hundreds of billions of dollars per year. However, the current practice of disaster damage assessment is largely dependent on humans (e.g., ground surveys) being slow, costly and error prone.

Reliability for Oil and Gas Downstream Industry

This webcast will focus on the value of developing holistic reliability program with different reliability assessment tools in Refinery Asset Management to identify top bad actors in refinery units and optimize maintenance strategies; and potential challenges to be faced during the reliability program implementation. 

Deviation Modeling in Additive Manufacturing Systems

Geometric shape deviation models constitute an important component in quality control for cyber-physical additive manufacturing (AM) systems. However, specified models have a limited scope of application across the vast spectrum of processes in a system that are characterized by different settings of process variables, and the disparate classes of shapes that are of interest for manufacture.

Smart Additive Manufacturing

This webcast will cover the presenters recent published and ongoing work in in-process monitoring of defects, as well as fundamental thermal modeling of metal Additive Manufacturing processes, such as laser powder bed fusion and directed energy deposition.

Big Data and Reliability Applications: The Complexity Dimension

During this webcast, the intension is to extend that discussion by focusing on how to use data with complicated structures to do reliability analysis. Such data types include high-dimensional sensor data, functional curve data and image streams.  

Accelerated Life Testing: Design of Test Plans and Reliability Prediction

This webinar will cover the fundamentals of accelerated life testing (ALT), types of stresses, load applications, design of test plans and reliability prediction and estimation.  Design of equivalent test plans will also be presented.

Evolution of Deep Learning: New Methods and Applications

Earlier known as neural networks, deep learning saw a remarkable resurgence in the past decade. neural networks did not find enough adopters in the past century due to its limited accuracy in real world applications (due to various reasons) and difficult interpretation. Many of these limitations got resolved in the recent years, and it was re-branded as deep learning.

Participation and Leadership Opportunities: QCRE

This webinar for IISE student members and potential student members will provide an overview of opportunities for student participation and leadership in IISE, Quality Control and Reliability Engineering (QCRE) related research and education areas. 

Data Analytics for IBM's Service Deals: Methodologies and Practical Implications

In this webinar, the presenter will discuss analytical data approaches developed successfully, which reportedly lead to revenue increases for IBM in the range of millions of dollars each quarter, enabling the pricing of solutions in a tiny fraction of the time that this task use to take and in a more accurate and efficient manner, as stated by the VP of global solutions. 

Additive Manufacturing: Capabilities, Research Challenges and Process Monitoring

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.

Structured Approach to Lean Process Management: Beyond the Hype in Lean Implementation

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.

A System Approach to Quality Management: How Quality Supports Business

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 and Availability Considering Uncertainty

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.

Fundamentals of Reliability Engineering - Part 1

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.

Fundamentals of Reliability Engineering - Part 2

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.