Thomas L. Ward

Fuzzy logic control of aggregate production planning

Abstract Rinks used linguistic variables of the sort proposed by Zadeh for cost, inventory, production, and work force. He operated on these with fuzzy if-ten rules in a manner like that used by Mamdani and Assilan to control a steam engine. The Rinks membership functions and rules were subjective creations. Nevertheless, he obtained results that compared favorably to both prior and subsequent heuristic treatments of the HMMS data. We have developed a C language fuzzy logic controller (FLC) that uses the Rinks discrete membership functions and closely reproduces his results. We have used this FLC to investigate the effect of granularity of the discretization on the quality of solution. We have also used Wang-Mendel learning to improve the rule base. This paper discusses these results and suggests areas for further investigation.

Development of a microcomputer-based expert system for the analysis of manual materials handling tasks in industrial settings

Abstract This paper discusses the framework of a comprehensive knowledge-based expert system (M-LIFTAN) for analysis and design of manual materials handling tasks. The system, built using an expert system shell: ES / P ADVISOR written in Prolog 2, is implemented on a IBM AT® microcomputer. The knowledge base of M-LIFTAN allows the user to perform five different types of job analysis: (1) determination of maximum weights that can be handled manually by industrial workers for a variety of tasks, (2) determination of the NIOSH-based lifting recommendations, (3) prediction of maximum acceptable loads for lifting, (4) evaluation of the risk of overexertion injury while lifting loads under specified conditions, and (5) to seek advice for design/evaluation of complex manual handling tasks. An example of the consultation session illustrates the systems capabilities.

Fuzzy logic control of chip form during turning

Abstract Chips produced during lathe turning should be broken so as to prevent snarling and to enhance heat removal from the tool. At present, conservatively written part programs for computer numerically controlled lathes are fine tuned by a human machine operator to produce desirable chip length. K. W. Yee and coworkers have produced an acoustic emission chip form monitor. The use of such an acoustic emission sensor in a simulated chip length control system is described. In this paper a fuzzy logic controller is then substituted for the conventional linear controller.

Intelligent control of machines and processes

Abstract This review will consider computer based feedback control systems that rely on rule bases, knowledge bases, machine learning, and other artificial intelligence (AI) techniques. Traditional adaptive control is specifically excluded.

COMPUTER RATE OF RETURN ANALYSIS OF MIXED CAPITAL PROJECTS

ABSTRACT Computer codes for the routine implementation of tbe Teichroew-Robicheck-Montalbano (TRM) rate-of-return formulation are presented. Project cash flow sequences are classified as one of the four TRM cases and then analyzed. Project investment rates (PIR) are calculated for user specified minimum attractive rates of return.

Linguistic Design of Nonlinear Controllers

In this article a simplified fuzzy controller implementation is explored and shows clearly that it is an input-output interpolating algorithm derived from a set of production rules. The simplified controller development is similar to that in the literature. Unique to this work is the compelling description of fuzzy controllers as interpolating devices, with the explanation supported analytically. Such a presentation is in contrast to the usual description of a fuzzy controller as a rule-based expert system that bypasses an underlying analytical description of the relationship between input and output produced by the rule base. The reader is given an analysis showing that a fuzzy controller can be viewed as an input-output relationship represented by a breakpoint function, and that the breakpoint function may be obtained directly from the control rules in simple cases. For engineers and others trained in conventional control theory, this article demonstrates that they need not be practiced in fuzzy set theory or fuzzy logic to take advantage of the utility of the fuzzy technique in designing nonlinear controllers.

Continuous-time simulation of semi-orthogonal metal cutting on a lathe

Abstract There has been considerable attention to applications of feedback control to machine tools. Certainly all computer numerically controlled (CNC) machines use servomechanisms for the spindle and feed drives. When feedback control is extended to the metal cutting process itself, there has been an unfortunate tendency to call such systems adaptive controls, for example, adaptive control constraint (ACC) and adaptive control optimization (ACO), even though they have not been adaptive in the sense of modern control theory. A special name, parameter adaptive control, has been proposed to describe the application of truly adaptive control to metal cutting. Even though there is substantial work on adaptive control within the body of modern control theory, there have been few reductions of parameter adaptive control to actual machine tools. It has been suggested that the primary impediments to such application are the lack of mathematical models of manufacturing processes in forms appropriate to the control problem, and the lack of in-process sensing techniques that would be complementary to such models. This paper describes one step in a sequence of research efforts that is intended to lead to the adaptive control of unattended machine tools. Numerical parameters are used to evaluate coefficients of a previously developed state space model of semi-orthogonal metal cutting on a lathe. An Advanced Continuous Simulation Language (ACSL) program is presented.

Continuous-time simulation of metal cutting on a lathe

Abstract Even though there is substantial work on adaptive control within the body of modern control theory, there have been few reductions of parameter adaptive control to actual machine tools on the shop floor. It has been suggested that the primary impediments to such application are the lack of mathematical models of manufacturing processes in forms appropriate to the control problem, and the lack of in-process sensing techniques that would be complementary to such models. This paper describes one step in a sequence of research efforts that is intended to lead to the adaptive control of unattended machine tools. Numerical parameters are used to evaluate coefficients of a previously developed state space model of semi-orthogonal metal cutting on a lathe. An advanced continuous simulation language (ACSL) program is presented.

Adaptive control of machine tools: the past and projected role of numerical control computers

Abstract Unattended operation has placed special demands on controls for machine tools. This paper reviews the research of the past 25 years and summarizes a variety of systems for adaptive control (AC) of machine tools. Special attention is given to the computer used and its role in the system. These systems have not been widely applied because of the high cost of the hardware in comparison to anticipated benefits. With present day computer numerical control (CNC) systems, AC is more easily implemented with lower cost software changes. Further, the increasing importance of unattended operation has greatly increased the expected benefits. Research has shown the need for the development of parameters adaptive systems which are stable and can provide on-line estimates of process parameters. Such control must insure that operations are within the constraints imposed by the machine. Equally important, the control must embody the sensing and measurement required for efficient tool management. That is, the system should measure tool wear and provide for automatic tool replacement. The authors present a state space model and associated methodology to address these issues for a CNC lathe.

Computer observer for in-process measurement of lathe tool wear

Abstract In the laboratory, tool wear is measured by direct visual observation of flank and crater wear dimensions using a tool makers microscope. On the shop floor, the journeyman machinist uses chip appearance, sound, vibration, and surface finish to access tool condition. More precise information can be provided by between pass measurements of work piece dimensions. Although there is a body of research directed toward in-process measurement of tool wear, none has found practical application on the shop floor. This, despite the demands of unattended operation of machine tools in the automated factory. Two of the authors have developed a state space model of metal cutting on a lathe. Operation of that model was experimentally accessed using the Advanced Continuous Simulation Language (ACSL) [1]. The state space model embodied in the simulation is comprised of six state variables. In an actual lathe, four of those variables (spindle speed and torque, and cutting speed and force) would be directly measurable. The other two variables, flank and crater tool wear, would not be measurable. This paper describes a linear observer that reconstructs the two tool wear state variables based on system inputs and the four measurable state variables. In actual use the observer would be implemented using a microcomputer dedicated to the lathe. In this study, the previously developed ACSL model was substituted for the lathe, and the linear observer was incorporated as an extension to the simulation. Operation of the observer, including response to initial errors, is demonstrated.