Suraj M. Alexander

Economic design of control charts using the Taguchi loss function

Abstract We embellish Duncans cost model with Taguchis loss function to incorporate losses that result from both inherent variability due to assignable causes. Whereas Duncan applies a penalty cost for operating out of control, he does not show how this cost can be obtained or quantified. We illustrate, analyze, and evaluate this model utilizing hypothetical cost figures and process parameters. We also suggest adjustments to control chart design parameters when there are process improvements over time.

Advisory system for control chart selection

Abstract This paper presents a framework of a computer based advisory system that can be used to assist in the selection, design, and construction of control charts. The system is developed using expert systems technology. This paper illustrates the framework by providing a trace of a demonstration system that has been constructed and shows planned enhancements to the system.

An expert system for the selection of scheduling rules in a job shop

Abstract This paper presents a conceptual framework for the application of expert systems for the selection and development of scheduling rules for a job shop. A portion of the framework is illustrated using an expert system developed using MI™.

The application of expert systems to manufacturing process control

Abstract In recent years the control of the manufacturing process has received prime focus of manufacturers throughout the world. Expert systems technology allows for the implementation of sophisticated and efficient process control systems. This paper provides a framework for the application of expert systems to manufacturing process control. It details the unique features of such a system and explains the constitution of the knowledge base.

A diagnostic expert system prototype for CIM

Abstract This paper describes the Diagnostic System Prototype (DSP), consisting of a deep knowledge base and several shallow knowledge bases, and shows how it works. Based on the theory of hierarchical systems and hybrid diagnostic reasoning, the DSP tries to find a cause(s) for an observed symptom in CIM (Computer-Integrated Manufacturing), using the concept of entropy. The entropy is calculated using test costs and degrees of belief for each rule in the shallow knowledge bases. The DSP is expected to be applicable to different domains other than just the manufacturing environment.

A hybrid diagnostic system with learning capabilities

Abstract Fast and accurate diagnosis of faults in computer integrated manufacturing systems is essential in order to avoid excessive equipment downtime, and to take full advantage of these systems. Traditional approaches to diagnosis have yielded to artificial intelligence approaches over recent years, as system complexity has increased; but results have been mixed. Symptom-based approaches have been too limited, while structural-based approaches have required excessive computational resources. This paper presents a hybrid model for diagnostics that is computationally efficient, and at the same time incorporates the potential to improve its performance with use through a learning scheme.

Continuous Quality Measurement: Restructuring assessment for a new technological and organisational environment

This paper discusses the notion of continuous quality measurement and describes a technology-based continuous Quality Measurement System (QMS) that has been developed and implemented at the University of Louisville. QMS is an enterprisewide model for addressing the major challenges confronting the outcomes assessment movement in higher education. In the Fall of 1998, the University of Louisville developed a partnership with Dey Systems, a Louisville technology company that specialises in quality and measurement solutions, to create a Quality Measurement System for higher education. QMS is a relational, interactive information system that includes data from 273 students, alumni, faculty, staff and employer satisfaction surveys that are linked to corresponding databases at the university. QMS is an on-line information system, operating in a networked, client-server environment that permits licensed users access to designated components of the system at any time from designated desktops at the university. QMS users generate reports and perform advanced statistical analyses drawing from the QMS databases. These data and reports are used to improve academic and support programmes at the university. The paper closes with a discussion of the role of QMS in the universitys quality improvement scheme and its initial impacts on the institution.

Using multi-criteria modeling and simulation to achieve lean goals

Lean principles require the identification of an ideal system state along with an associated policy to achieve that state. This paper discusses the use of multi-criteria models in conjunction with optimization procedures and simulation in order to identify an ideal system state and associated policy. An illustration involving the determination of a replenishment policy for a distribution system is described.

Monitoring, diagnosis and control of industrial processes

We present a framework for monitoring, diagnosis, and control of industrial processes. This framework utilizes the multiresolution analysis capability of wavelet theory. Wavelet coefficient patterns at different scales, under a variety of process conditions, are noted to form process fingerprints, these fingerprints yield process fault diagnosis. This knowledge facilitates efficient control.

An architecture for sensor fusion in intelligent process monitoring

Abstract This paper suggests an architecture for sensor fusion in intelligent process monitoring. The paper reviews the need for sensor fusion in manufacturing process control, describes the architecture and provides an example of its implementation in the laboratory.