Steven W. Holland

CONSIGHT-I: A Vision-Controlled Robot System for Transferring Parts from Belt Conveyors

CONSIGHT-I is a vision-based robot system that picks up parts randomly placed on a moving conveyor belt. The vision subsystem, operating in a visually noisy environment typical of manufacturing plants, determines the position and orientation of parts on the belt. The robot tracks the parts and transfers them to a predetermined location. CONSIGHT-I systems are easily retrainable for a wide class of complex curved parts and are being developed for production plant use.

Health monitoring of electronic products based on Mahalanobis distance and Weibull decision metrics

Abstract This paper presents a novel approach for health monitoring of electronic products using the Mahalanobis distance (MD) and Weibull distribution. The MD value is used as a health index, which has the advantage of both summarizing the multivariate operating parameters and reducing the data set into a fused distance index. The Weibull distribution is used to determine health decision metrics, which are useful in characterizing distributions of MD values. Furthermore, a case study of notebook computer health monitoring system is carried out. The experimental results show that the proposed method is valuable.

Trends in the development of system-level fault Dependency matrices

A Dependency matrix (D-matrix) is a consistent and systematic way to capture hierarchical system-level fault diagnostic information. The D-matrix is derived from a dependency modeling framework to capture the causal relationships between failure modes and symptoms. D-matrices are developed from various sources such as historical field failure data, service documents, engineering schematics, and Failure Modes, Effects and Criticality Analysis (FMECA) data. Here, we survey the existing research work on developing D-matrices from disparate data sources and data formats. We classify the D-matrices based on their data source and the imperfectness of symptoms for both boolean and real-valued [0,1] D-matrices. An industrial perspective is offered to describe the pros and cons of various types of D-matrices along with the challenges faced while developing and applying them for vehicle health management. 1 2

Production Plant CONSIGHT Installations

CONSIGHT is a computer vision based system developed by General Motors which is able to locate and identify parts on moving conveyor belts. Two different factory applications are presented which illustrate CONSIGHTs capabilities and which bring out some of the issues of developing production systems. The first system discussed employs a single vision station and a series of pneumatic kicker devices to sort passing parts into one of 16 bins. The second system employs a single vision station and multiple robot stations to load large castings from a conveyor into shipping containers.

Decision Forest for Root Cause Analysis of Intermittent Faults

Intermittent failures can be problematic in electronic control units (ECUs) such as engine/transmission control modules. When an ECU exhibits an internal performance fault, the ECU may malfunction, while the fault condition is active, and later, it may once again give correct results when conditions change. Due to highly unpredictable nature of intermittent faults, it can be extremely difficult to diagnose them. Therefore, there is a need to enhance the fault diagnosis of intermittent faults in ECUs. In this paper, we propose an off-board, data-driven approach that can assist diagnostic engineers to investigate intermittent faults using fleet-wide field failure data. The field failure data may include a large number of intermittent faults and concomitant operating parameters (e.g., vehicle speed, engine speed, control module voltage, powertrain relay voltage, etc.) recorded at the time when the faults occurred. We describe a decision forest method to identify a reduced set of informative operating parameters, i.e., features that separate or characterize the operating conditions of the intermittent fault from baseline, i.e., classes in feature selection space. A web-based application has been developed to assist the diagnostic engineers. We demonstrate the capabilities of our method using three case studies for an automobile test fleet.

Integrated vehicle health management in the auto industry

The advent of integrated vehicle health management (IVHM) in the auto industry promises to provide significant new capabilities to enhance the total customer experience. General Motors vision and strategy for developing this technology through collaboration with academia and the external technology supply base is explained.

Anomaly detection of notebook computer based on Weibull decision metrics

This paper presents a approach for anomaly detection of electronic products using the Mahalanobis Distance (MD) and Weibull distribution. The MD value is used as a health index, which has the advantage of both summarizing the multivariate operating parameters and reducing the data set into a univariate distance index. The Weibull distribution is used to determine health decision metrics, which are useful in characterizing distributions of MD values. Furthermore, a case study of the proposed notebook computer anomaly detection method is carried out. The experimental results show that the proposed method is valuable.