Robots,CAM and O.R.

Microelectronics have greatly influenced the nature of manufacturing technology and systems. New factories make growing use of microcomputers and microprocessors in robots, C.N.C. machine tools and flexible manufacturing systems. The result is an increasing trend towards fully integrated computer-based manufacturing systems. As a consequence, O.R. software has a newer, more direct role in the modern factory than ever before. Fully integrated CAM systems are implemented by multi-disciplinary teams of engineers and management scientists. The O.R. practitioner can make a major contribution, for example in layout optimisation and plant simulations.     

The Changing Role of O.R.

The authors set out to consider the activities of their own O.R. group at British Airways in the light of Russ Ackoff's papers delivered at the 1978 ORS Conference, but the paper has developed into a discussion of Ackoff's ideas from the viewpoint of an in-house industrial O.R. group that has had considerable success in implementation and has thought a great deal about what it is trying to do. Particularly relevant is the emphasis placed by this O.R. group on highly interactive planning models and systems and on an evolutionary approach to development. Some attempt is made to put Ackoff's ideas into an historical perspective and his main points are discussed one by one. The authors are in sympathy with the direction Ackoff is pressing, but not with the gloom his paper has generated in some quarters.     

Artificial Intelligence—An Overview of Similarities with O.R.

A brief outline of A.I. is provided, noting problems, techniques and objectives which are similar to those found in O.R. It is intended that this will indicate to O.R. workers which A.I. areas might be worth following up as relevant to their own work and which problems in A.I. might be attacked by the O.R. community as part of the development of intelligent support systems.     

A Problem-driven Approach to Expert System Development

Expert system technology can fairly be described as high profile at present. Yet its track record as a useful method for tackling problems is subject to widely differing views. This paper considers the domain of production planning and control, which has been described as a good application area for expert systems a domain where OR has had little success. The authors argue that mainstream expert system methodology is exploratory rather than problem-driven and thus is not suited to the domain. A problem-driven approach to expert system development is presented, an approach which makes use of soft systems methodology. The reasons for such an approach within production planning and control are discussed, and the use of soft systems methodology within the approach is reflected on.     

Programming Languages,Microcomputers and O.R.

The relationship between O.R. and computer programming is considered. The programming languages involved, and their respective roles, are reviewed. Criteria for assessing a programming language for O.R. are discussed, particularly in view of the increasing use of microcomputers within O.R.     

Computational methods for income transfer analysis

The analysis of transfer systems that include both social benefit and taxation programs is complicated by the fact that the component programs comprising those systems interact. This paper develops a mathematical framework for the analysis of such systems at the micro‐level, i.e., using an individual or family as the unit of analysis. The first section describes the importance of income transfer issues and identifies criteria for evaluating proposed methodologies. Subsequent sections address the foundations for appropriate methods from two perspectives. The first perspective examines transfer systems using elementary concepts drawn from set theory, real analysis, and welfare economics; the assumptions and theorems presented allow the derivation of relevant system properties and serve to ensure that the systems discussed are well‐defined. The second perspective concentrates on the numerical methods required to execute income transfer analyses. The final section describes an implementation of this framework and briefly discusses the associated software.     

A review of expert systems

Expert systems have recently become popular and are attracting more and more attention. The high quality performance achieved by some systems in areas previously not considered practical for computational solutions has lead to great interest from many different disciplines. Most expert systems use a subset of techniques from the general area of computer science research known as artificial intelligence. However, some expert systems have been developed that incorporate more traditional mathematical modeling techniques. The combination of artificial intelligence techniques and more traditional mathematical techniques has been shown to be quite effective in developing several high quality performance computer software systems. The techniques used in expert systems may be what is needed to bridge the gap between classical operational research modeling and human decision making processes. This paper addresses how expert systems techniques are being used in problem solving and why someone in operational research might want to use them.     

O.R. and Public Expenditure Planning and Control

The problems of public expenditure planning and control to which O.R. can make a contribution are identified. Suggestions are made for research by those in O.R. both within government and in universities. Recent work in the Treasury on financial models and information systems are discussed in terms of how such work might be applied elsewhere and extended to include measures of achievement. The topics covered include planning for uncertainty and theory development by O.R. in models of inflation and social justice.     

Model and Situation Specific O.R. Methods: Risk Engineering Reliability Analysis of an L.N.G. Facility

A decision situation and model-specific O.R. method developed for reliability analysis of an Arctic liquid natural gas facility is outlined. It was developed by modifying a decision situation and model-specific O.R. method developed earlier for time (schedule or programme) risk analysis of offshore North Sea projects. The role and value of such methods is discussed in relation to general O.R. methods and specific techniques like C.P.M./PERT.     

Intermediate Generality Simulation Software for Production

Simulation has long been a valuable tool in the field of production. With the current and anticipated developments in computing equipment, there is a demand for simulation software, which can be used by managers to investigate specific classes of problems. The O.R. profession should involve itself in the identification of suitable areas and the development of appropriate software. Two such areas where simulation software is being developed are discussed: production planning in a batch environment and the investigation of advanced manufacturing systems.     

Expert Systems for University Admissions

This paper describes the construction of an expert system to help the admissions tutor for a university degree in business and management which receives some 2000 applications for entry each year, using the SAGE shell. What originally began as a ‘demonstrator project’ is shown to be of practical value, in terms of both producing a usable expert system and clarifying and questioning the selection criteria used by the admissions tutor. A particular conclusion emerging from this work which may be relevant to many expert systems applications is that ethical and practical considerations dictated that some questions involving judgement could not be delegated by the admissions tutor to the clerical staff. It thus became necessary to develop two versions of the expert system, one a full ‘admissions-tutor system’, the other a more limited version for day-to-day use.     

The Art of Course Planning: Soft O.R. in Action

This article is a case study described from two viewpoints: that of an analyst and that of a ‘decision-maker’. It describes the use of two ‘soft O.R.’ methods in helping the members of a university O.R. group to plan revisions to a postgraduate Diploma course, resulting in the implementation of an improved course. One author conducted the exercise while the other was a member of the client group. Given that case studies are usually written by the analyst alone, it is hoped that a client's eye-view will be useful as feedback for practitioners and can also introduce some of the concepts and terminology of soft O.R. to those engaged in more mathematical O.R. activities.     

The Impact of Operational Research on Agriculture

The paper shows that agriculture is one of the United Kingdom's largest industries. It would therefore be expected that O.R. could have made a significant contribution to decision making. But achievements in practice have been disappointingly small. The industry comprises of a large number of small individual businesses which do not permit specialisation in management functions. Consequently, technical advice and much R and D is provided from public funds. O.R. applications for agriculture have mainly been developed by Universities, Colleges, State Advisory Services and QUANGOS.The paper discusses some techniques used in agriculture—linear programming, dynamic programming and simulation—and outlines some problems encountered with these. Other techniques have had limited uptake and application. Reasons for the disappointing impact of O.R. are discussed as a set of problems-those specific to farmers and their systems; those specific to computer use; problems in recruiting and training O.R. specialists and problems in communication.     

Linking Discrete-Event Simulation Models with Expert Systems

This paper describes experiments designed to test the feasibility of linking discrete-event simulation models with expert systems. Two microcomputer systems are used: one contains the simulation model, while the other contains the expert system. The paper shows that by linking a simulation model with an expert system, it is possible to use the combination for simulation parameter learning, expert system development and expert system control of a simulation model.     

O.R. and Micros: O.R. Workers,Information Systems Analysts and the Challenge of the Micro

An assessment of the effects of microcomputing on O.R. should take account of the impact of micros on other professional groups involved in the provision of information and analysis to managers. The paper examines the likely changes in the role of information systems analysts associated with present trends in computer-based information systems and, by concentrating on the decision support systems area, argues that O.R. workers and systems analysts may find themselves competing for new roles in ways which make if difficult to set out the contribution of each in terms of what they do at present. A modest proposal is made for a new form of team for the development of decision support systems. This incorporates a division of skills which cuts across existing lines of differentiation and foresees an increased contribution on the part of user-managers.     

基于故障诊断专家数据库系统的模糊模式识别

本文分析了模糊逻辑方法进行诊断的不足,提出了基于广义贴近度的模糊模式识别方法,建立并讨论了相应的故障诊断专家数据库系统     

An Interactive Dynamic Inventory-Production Control System

The development and evaluation of an interactive model for controlling inventories and scheduling production in a high technology batch production environment are discussed. The model allows the use of expert knowledge and company policy for matters such as customer service and safety stocks, in an interactive way. Production of a large number of products has to be scheduled for a number of time periods and a modified Wagner-Whitin algorithm is used for developing good schedules. A versatile data and information management system is a part of the developed software which has been implemented using a standard microcomputer. An evaluation suggests that the system is a practical one for use by busy managers. Further, it results in substantial cost savings and increased customer service.     

O.R. Applications in Industry and Problems of Industrialisation of a Developing Economy with Special Reference to India

The paper has two distinct parts. The first part reviews industrial applications of O.R. in developing countries in general and India in particular. Based on the analysis, the paper suggests concrete steps for further use of operational research in industry.The second part of the paper deals critically with the problems of industrialisation leading to a specific industrial structure in the economy of a developing country. Analysing various relevant criteria for industrialisation of developing economies the paper outlines a methodology suitable for modelling the problem. It then attempts to identify the prerequisites for successful use of O.R. in the multicriteria problem of industrialisation. The paper also discusses the role that national and international agencies can play in bringing about more meaningful applications of O.R. in developing economies.     

Expert systems for planning and scheduling manufacturing systems

In this paper, research and applications of expert systems in production planning and scheduling are reviewed. Components of expert systems are briefly discussed. Relationship between expert system and operations research approaches are presented. Integration of operations research and expert system techniques is explored.     

Integrated decision support for aviation safety inspectors

This paper presents a systems viewpoint for developing an advanced decision support system for aircraft safety inspectors. Research results from a Federal Aviation Administration (FAA) sponsored project to use neural network and expert systems technology to analyze aircraft maintenance databases are summarized. One of the main objectives of this research is to define more refined “alert” indicators for national comparison purposes that can signal potential problem areas by aircraft type for safety inspector consideration.

Integration aspects are addressed on two levels: (1) integration of the various technical components of the decision support system, and (2) integration of the decision support system with individual behavior, management systems and organizational structure, as well as corporate culture across both formal and informal dimensions. The paper summarizes the creation of strategic “inspection profiles” for aging aircraft and reliability curve fitting for structural components both based upon using neural network technology. Also, the potential use of a model-based expert system to facilitate field inspection diagnostics is presented. Finally, a framework for developing an intelligent decision system to support aircraft safety inspections is proposed that links expert systems, neural networks, as well as a paradigm of the decision making process typically used in unstructured situations.