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.     

O.R. in the Community

For the past eighteen months the authors have been involved in work with a community group attempting to help the unemployed youth of their small city. This paper discusses some of the key differences and similarities they found between this work in the community and more traditional organizations, particularly in terms of client-consultant expectations and their "organizational" context. The authors were made aware of the inadequacy of traditional O.R. techniques for helping their clients and the paper also describes some of the unconventional methods they were forced to turn to in order to offer realistic and relevant help with this complex "mess" of multiple problems, nested feedback loops and subjective, political beliefs not amenable to quantification.     

Pioneering O.R.

This paper describes the critical start-up period of a new Operational Research unit in industry. Four principles for success evolved and are discussed against a background of practical work.     

O.R. Education — A Survey of Young O.R. Workers

This paper presents the results of a survey into O.R. education that was conducted with the help of those attending the Young O.R. Conference (YOR II) held at Nottingham University in March 1982. The results of a workshop debate held at the conference into the direction of O.R. education are also discussed.The conclusions drawn are that O.R. education in this country appears to be quite successful but that it is failing to deal satisfactorily with a number of issues. These issues relate to keeping up-to-date with changes in computer technology and their impact upon O.R. workers; the teaching of methodology to deal with ill-defined problems; preparation for the political and working environment of organizations; and the fostering of desirable personal characteristics.     

Optimal maintenance of systems with Markovian mission and deterioration

We consider the maintenance of a mission-based system that is designed to perform missions consisting of a random sequence of phases or stages with random durations. A finite state Markov process describes the mission process. The age or deterioration process of the system is described by another finite state Markov process whose generator depends on the phases of the mission. We discuss optimal repair and optimal replacement problems, and characterize the optimal policies under some monotonicity assumptions. We also provide numerical illustrations to demonstrate the structure of the optimal policies.     

O. R. in Defence

Journal of the Operational Research Society -     

The impact of process deterioration on production and maintenance policies

This paper examines a single-stage production system that deteriorates with production actions, and improves with maintenance. The condition of the process can be in any of several discrete states, and transitions from state to state follow a semi-Markov process. The firm can produce multiple products, which differ by profit earned, expected processing time, and impact on equipment deterioration. The firm can also perform different maintenance actions, which differ by cost incurred, expected down time, and impact on the process condition. The firm needs to determine the optimal production and maintenance choices in each state in a way that maximizes the long-run expected average reward per unit time.