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As the increase in manufacturing competitiveness forces organizations to use more sophisticated and complex software, system performance depends on clever systems design, efficient planning and scheduling of the related processes. For these advanced manufacturing systems the dependence on human competence is greater. However, previous studies indicate that the human aspects for successfully implementing such systems have been neglected. The objective here is to test the hypotheses that system complexity is inversely related to performance, and that training of system operators, and the quality of the man/machine interface reduces the negative impact of system complexity. A sample of discreet manufacturing systems from 128 organizations was used to test these hypotheses empirically. Moderated multivariate regression indicates that man/machine interfaces are significant contributors to reducing the negative effect of systems complexity. With a lower level of significance, operator training has a similar impact. For complex manufacturing systems software, it behoves managers to insure that the man/machine interface provides the desirable features outlined in this study.

AS industrial monitor and control systems grow in both size and sophistication, the demands placed upon the man‐machine interface (MMI) increase to the point at which there are significant advantages to be gained from separating the data distribution and display function from the rest of the system. One of the main benefits of such an approach is the elimination of ‘knock‐on’ effects from changes in the way the data is distributed, manipulated and displayed. In a system where data distribution and display are an integral part of the total monitor and control system, changes to one part of the system can result in unexpected and far reaching effects on the whole system. As a result, changes which would improve the MMI aspects of the system are often not implemented.

Automating the welding process for the shipbuilding industry is very challenging and important, as this industry relies heavily on quality welds. Conventional robotic welding systems are seldom used because the welding tasks in shipyards are characterised by non‐standardised workpieces which are large but small in batch sizes. Furthermore, geometries and locations of the workpieces are uncertain. To tackle the problem, a Ship Welding Robot System (SWERS) has been developed for the welding process. The main features of the SWERS include a special teaching procedure that allows the human user to teach the robot welding paths at a much easier and faster pace. In addition, operation of the system is made easier through a custom designed man‐machine interface. Through this interface, only a few buttons need to be pressed to command the robot into different modes. Optimised welding parameters can be selected from a large database through a Graphical User Interface system.

Reviews the Eureka Alasca project. Outlines the pilot assembly cell developed for Zanussi’s washing machine plant. Describes the need for an operator‐friendly man‐machine interface. Explains the difficulties associated with the automated assembly of heavy concrete components lacking in precision.

This paper presents an overview of the main features of GENERIS, a generalised software control system for industrial robots developed by the EC‐JRC and financed by the EC‐DGXIII‐D1. After an introduction reporting the project history and its current development and exploitation state, the author analyses the required capability and quality attributes for a modern motion control system for robotics workshops and how GENERIS matches them. Thereafter, the GENERIS system capabilities and distributed architecture are described. The author concludes with the product organisation and the current and planned development activities.

Examines the development of DSP [digital signal processing] technology which has led to the increasing use of speech synthesis applications in the home, office and factory. Describes how the latest speech synthesizer chip works and outlines the product development cycle from the initial idea through the recording and encoding of the message to the end product: a speech synthesis device which can be used in a wide variety of man‐machine interface applications to warn, inform, instruct or to entertain.

Now that most of the £350 million of Alvey funding has been allocated it is possible to see in what ways sensing technology stands to gain from the research programme.

A great deal has been published recently concerning expert systems and the viability of using expert system shells and a useful feature published in Systems International, April, 1988, pp 23–38, provides a summary of these shells and their market. There is, of course, great activity in all aspects of development of these systems. For example, the European experts systems market alone is said to be growing at a rate of 50 per cent a year and should reach $1 billion by 1991. In an introduction to this summary it is stated that some 40 per cent of expenditure on artificial intelligence (AI) is on software, and of this a third comes from the sale of AI languages. This feature on expert systems looks at the human and organisational problems to be considered when implementing such a system. It also outlines the market for the systems, and surveys some of the products. Finally, the limitations inherent in the rules govering expert systems shells are discussed. In an article in this review Sue Ottley, a psychologist in the human factors group at ICLs Marketing and Technical Strategy Centre, warns of some human and organisational problems to consider when implementing an expert system, from capturing an expert's knowledge to gaining user acceptance. She says that there are wide ranging concerns at the organisational level, which includes changes in the information flow patterns within an organisation, changes that can be brought about to the authority and decision‐making hierarchies and the effects of changing the locus of control and/or authority within an organisation. This latter state can have a strong effect on the acceptance of an expert system and needs to be planned for in advance. Otherwise, unplanned change or uncontrolled change, can, she maintains, be disruptive to even the most well developed and stable organisation.