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Within the framework of Supervisory Control Theory, synthesis algorithms enable automatic generation of control rules from behavioural models of the process to be controlled and of goals to be achieved. The paper highlights a pragmatic use of these algorithms within an automation engineering context and focuses on two key issues: process and goals modelling, and supervisory controller implementation. In this way, the approach presented combines the synthesis techniques and algorithms with an object-oriented automation method that supplies guidelines for the analysis, design and implementation of a modular control system. This pragmatic approach is applied to the synthesis and implementation of the control of an assembly station. The paper highlights the difficulties of the modelling step and its great influence on the synthesis result itself, and also demonstrates the feasibility of the synthesis approach through a successful implementation in conformance with the International Electrotechnical Commission...

With new market developments and e-commerce, there is an increased use of and interest in automation for order picking. This paper presents a systematic review and content analysis of the literatur...

In today’s competitive environment with increasingly faster deliveries and smaller order sizes, material handling providers are progressively developing new solutions. A more recent development in automated material-handling technology for unit load storage and retrieval is the autonomous vehicle storage and retrieval system (AVS/RS). The paper investigates the main design trade-offs for this new solution using simulation, and proposes a comprehensive design framework. Using data from a recently implemented AVS/RS, the application of the proposed framework is presented and the key design differences between the two types of AVS/RS configuration (i.e. tier-captive versus tier-to-tier) are identified.

The research reported in this paper is concerned with gaining a better understanding of human factors issues in machining and the automation of manufacturing tasks. Mismatches between operators' performance and the requirements of machining tasks were experimentally studied with respect to the relationships with various human characteristics, including skill, age, work experience, self-confidence and trust. Twelve hypotheses concerning interrelationships between these characteristics were evaluated and important relationships established. It is considered that this increased knowledge of the rate of mismatches and an understanding of the causes is essential for the successful design of new working environments, machines and tasks. Much of this change to the working environment is likely to involve some degree of automation of the operators' tasks and so a second and important aspect of the study was designed to establish the extent to which preferred levels of automation were related to the same human characteristics. Four further hypotheses relating preferred levels of automation to skill, age, work experience, self-confidence and trust were tested with results that, in some cases, were unexpected and in others contradict the findings of previous research. © 2000 Taylor & Francis Ltd.

This paper focuses on the requirements for achieving automated diagnosis and error recovery in a robotic assembly cell, Untended robust operation is the goal which is discussed, and the use of a knowledge-base oriented diagnostic/control system to support on-line error recovery is advocated. It is proposed that error recovery attempts should be made, not only based on information gathered by system sensors, but also by using additional cell-specific knowledge pertaining to recovery strategies. Recovery attempts are to be made even in the absence of complete diagnosis, in order to gather additional information, A control structure developed to implement this approach is presented.