Two competing failure modes were found to dominate motor life; i.e., bearing failures and winding failures. All bearings in the failure bank were of the grease-packed ball bearing type. Separation of failure by failure mode indicated that both failure modes could be described by a Weibull Commulative Distribution. A mathematical model for each failure mode, with dominant variables was developed and a competing risk failure model established.

An existing data failure bank consisting of over 2000 actual fractional horsepower (FHP) motor failures was upgraded and utilized to develop a failure model for FHP motors. Motor failures were dominated by two failure modes: i.w. , winding failures and bearing failures.

A literature survey of bearing failures and winding failures was conducted to verify failure modes and dependent failure variables. The following sections of this report describe the data failure bank, failure modes, literature review and development of the mathematical prediction models.

CONTENTS:

Data Bank Analysis

Bearing Reliability Model

Literature Review of Bearings

Development of Bearing Life Prediction Model

Motor Winding Reliability Model

Literature Review of Electrical Failures

Regression Analysis of Winding Failures

Influence of Altitude on Bearing and Winding Temperature

FHP Motor Failure Model

Failure Rates of FHP Motors

Use of FHP Motor Failure Models

Appendix A

Multiple Linear Regression Analysis Techniques and Examples

Regression Analysis

Use of Regression Analysis

Correlation Coefficients

Correlation Matrix

Correlation Coefficients of Transformed Data

Selecting an “Optimum Set” of Explaining Parameters

A Large Number of Independent Variables

Regression Tables Explained

Examples of Data Analysis Reduction

Appendix B

Recommended Replacement of Reliability Model for Electronic Cooling Devices and FHP Motors for MIL-HDBK-217B

Motor Reliability Prediction Model

Predicting Failure Rate Without Utilizing Tables

Bearing Characteristic Life Resulting from Thermal Cycling

Winding Characteristic Life Resulting from Thermal Cycling

Examples of Motor Failure Rate Prediction

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Systems Engineering Guide:

Considerations for Systems Engineering in a System of Systems Environment

System of Systems -An SoS is “a set or arrangement of systems that results when independent and useful systems are integrated into a larger system that delivers unique capabilities”. DoD has developed SoS in the past but has recently increased its emphasis on such systems to respond to new threats, to address coalition and joint warfare, and to incorporate rapidly changing communications and information technology. SoS complexity has increased dramatically, leading to new challenges in architecture, networks, hardware and software engineering, and human systems integration.

CONTENTS

1.2. Definition of Terms

1.2.1. System of Systems

1.2.2. System of Systems Engineering

1.2.3. Governance, Interoperability, and Asset Management

2. System of Systems Environment   …..Click here to read more