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Examines the results of a questionnaire‐based survey on the use of teach pendants with industrial robots. The main aims of the survey were to ascertain the following: extent of use of teach pendants with industrial robots; methods of robot programming used; possible difficulties of using teach pendants; and the future for teach pendants. Outlines the structure of the survey and evaluates the results from the questionnaire. Concludes that teach pendants are still one of the principal means of programming a robot and that difficulties controlling the motion of robots with teach pendants need to be addressed.

The majority of engineering failures occur because of surface initiated effects such as wear, corrosion and fatigue. Surface treatment/coatings (T/C) offer the potential to prevent failure and often to reduce cost. T/C selection is an important part of design for manufacture (DFM) spectrum and has been a very elusive activity to formalize. With the advent of knowledge‐based systems, provision of T/C selection assistance to the designer early on in the design process has become a practical reality. Reports the development of the TESS (Tribologically Engineered Surface Selection) expert system, which is concerned with the field of Surface T/C and their selection for optimum engineering design solutions. Introduces the T/C selection methodology and also describes the system developed. A logic‐based AI language, Prolog, has been used for the system development and versions of the system have been developed to run on the workstation and PC platforms. The initial work on the system was carried out with SERC support. Further developments are under way in this and other related design for manufacturability areas in this integrated design decision support approach.

The automated manufacturing systems of the future can only be feasible if they have capabilities to recover automatically from faults and errors effectively and efficiently. Reports on the work carried out looking at error recovery problems in manufacturing cell controllers. Cell control systems also invariably manage and schedule work in an automated cell as well as carrying out the general tasks of communications, sequencing and recording. Presents a model for error recovery capability which uses system information, data and prior knowledge of errors to recover from system errors. Elucidates the structure and operation of the cell controller developed. Work so far has shown promise in achieving automatic recovery capability in cell control systems. Finally identifies further developments for future work.