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This paper reports the findings of an experimental study in which the effect of informational load, direction of move and task difficulty on performance time were investigated. A mathematical model based on the empirical findings is presented.

Various aspects of operator performance during cranking are affected by the variability in crank size, resistance, location and position. Adequate prediction models incorporating these factors are not available to the designers of man‐machine systems. Consequently a set of experiments was conducted using three levels of crank radius, three levels of torque, three levels of plane angle, three levels of crank height, and two turning directions (namely, clockwise and anti‐clockwise) for continuous as well as intermittent cranking. The effect of radius, torque, plane angle and crank height were found to be significant and a subject's anthropometric dimensions and hand‐arm strength influenced cranking performance significantly. Prediction models for the turning rate for continuous and intermittent cranking were developed.

Industrial control tasks can also be called Combined Manual and Decision Tasks (CMDT). It is in the performance of such tasks that the human operator is likely to play an essential role as a decision maker. The findings presented are based on experimental studies in which 20 male subjects performed partial factorial experiments. Models of human performance in a two‐stage CMDT are developed and optimal conditions determined.

Ensuring equipment reliability, preventing human error and preventing accidents are necessary for improving predictable plant capacity. These subjects however, have so far been treated separately whereas an integrated approach is the need of the hour. A typical maintenance system focuses on equipment. However, its goals must include establishment of conditions that reflect an understanding of production plants as a combination of various man‐machine systems. Eliminating accidents and removing causes of production interruptions should be approached from the “man” as well as “machine” side. This paper outlines the relationship that exists between plant productivity, safety, and maintenance activities. An integrated system of activities, which is likely to help in eliminating accidents and maintenance related causes of production interruptions, is presented. This system divides plant operations into “man‐machine” system and management system activities. Activities that assist in eliminating accidents and removing potential causes of production interruptions are presented. Key performance indicators and a methodology for operating a continuous improvement program are outlined.

Maintenance costs are increasing as industry is trying to use automation and take advantage of advances in technology. Management needs to plan and control maintenance costs. Adequate techniques for developing standards for maintenance costs are not available. This article outlines such a technique and suggests means of comparing the maintenance performance efficiency of different plants/companies.

The process capability indices are used to assess the ability of a process to meet the present specification limits. These indices provide an easily understood qualification of a process performance. A fixed value for an ongoing process capability index is generally used. Minimization of statistical process control costs can be achieved by selecting an optimal process capability index. Presents a procedure to find an optimal ongoing process capability index.

Develops a procedure for solving the single period multi‐item inventory problem having budgetary and space constraints. The proposed procedure is simple to implement and allows easy sensitivity analysis with respect to the problem parameters.

Looks at the development of operations management in Pakistan. Notes that 85 per cent of manufacturing companies in the country are small‐ and medium‐sized enterprises (SMEs) with the remainder being branches of multinationals and their affiliates. Considers some of the problems encountered by SMEs in Pakistan, such as lack of trained manpower and insufficient technological capability.