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The purpose of this paper is to introduce a new design optimization technique for a surface mounted permanent magnet (SMPM) machine to increase sensorless performance at high loadings by compromising with torque capability.

An SMPM parametric machine model was created and analysed by finite element analysis (FEA) software by means of the Matlab environment. Eight geometric parameters of the machine were optimized using genetic algorithms (GAs). The outer volume of the machine, namely copper loss per volume, was kept constant. In order to prevent sensorless performance loss at high loading, an optimization process was realized using two loading stages: maximum torque with minimum ripple at nominal load and maximum self-sensing capability at twice load. In order to show the effectiveness of the proposed technique, the obtained results were compared with the classical one-stage optimization realized for each loading condition separately.

With the proposed technique, fairly good performance results of the optimization were obtained when compared with the one-stage optimizations. Using the proposed technique, sensorless performance of the motor was highly increased by compromising torque capability for high loading. Additionally, this paper shows that the self-sensing properties of a SMPM machine should be considered at the design stage of the machine.

In related literature, design optimization studies for the sensorless capability of SMPM motor are very few. By increasing optimization performance, new proposed technique provides to achieve good result at high load for sensorless performance compromising torque capability.

UNDER the heading of Statistical Control, we are faced with several terms which are still in their infancy as regards scope and definition.

Scheduling of production in a wire rope factory is complicated by several features: (a) the simultaneous requirement for two types of limited resource, machines and bobbins; (b) multi‐stage production with normally two or three stranding and one or two closing operations; (c) queuing at the closing machines; the typical job splits into sub‐batches when passing from the stranding to the closing operation; these sub‐batches usually queue at the closing operations which, being faster than stranding operations, generally receive work from several queues; (d) alternative choices in the selection of machines and bobbin sizes for any given stranding or closing operation; (e) the presence of random elements in the timing of machine breakdowns and repairs. In this case study factory in a developing country, the existing control of production flows was ad hoc rather than according to a specified method. The management needed to know whether a scientific scheduling approach could significantly improve the low utilisation of machines. As a first attempt a strategy was synthesised based on well‐known concepts from the theory of scheduling in static and dynamic environments, taking into consideration certain effects of the complicating factors mentioned above. Simulation revealed that a significant improvement was possible.

Constructs a knowledge‐based simulation model for job shop scheduling simulation techniques to build the initial status of the knowledge base. Uses the simulation experiments to study the effect of technological factors, such as machine loading conditions and criteria of scheduling performance requirements, on the selection of scheduling priority rules. Implements the model with real workshop data to test its validity to cater for real‐world situations such as machine group centres, more than one machine and the availability of operators. The proposed model yields satisfactory results.

DRAUGHTSMEN can make a major contribution to productivity provided they are trained in work study. This fact emerged from a paper presented by Mr. B. A. Dyson, General Manager (Overseas Production) of Hoover Ltd., to a joint work study conference organised by the British Institute of Management.

RANGE in any given vehicle of transport is generally understood to be the distance that it could travel without requiring to stop for any supplies necessary to maintain its normal performance.

This study aims to examine the effect of laundering on the softness and smoothness of terry-cloth towels by different washing machine type, washing temperature, drying method and the use of fabric softener, using a newly developed sound spectrum analysis known as Textile Softness Analyzer.

The experiment was designed to analyze the most significant laundering parameter in the reduction of softness and smoothness of terry cloth during one laundering cycle up to ten cycles by testing samples using TSA machine.

A front-loading washer had a significant effect on reducing softness and smoothness in comparison to a top-loading machine; line-drying resulted in a higher decrease in softness and smoothness than tumble-drying. Washing temperature showed no significant effect, and the use of softener during washing was able to reduce the negative effect of line-drying on the softness and smoothness of terry cloth.

This paper provided information on the laundering parameters that can maintain the softness and smoothness of terry-cloth towels, and this was examined with sound spectrum analysis to measure softness and smoothness of textiles.

WHY is it, may we enquire, that so few work study technicians write about work study?

IN view of the ever‐increasing application of time and motion study techniques in this country it is difficult to understand why so few manufacturers of time and labour‐saving equipment advertise the very items required by work study engineers.

“Productivity Partnerships”, a regulars series of demonstrations held at The 600 Centre in Shepshed, saw the UK launch of a new machine loading robot system by Fanuc Robotics. A description is given of the rail‐mounted 6‐axis robot together with some of the claimed benefits. It is a system that has been well received in the USA and two brief examples of installations from that side of the Atlantic are given.