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This paper reviews the literature relating to concepts and definitions of productivity, utilization, and efficiency. From an analysis of these concepts and definitions, the author derives two unifying formulae, the first relating these factors to one another and the second adding in a quality factor. System improvement strategies are then discussed based on these two equations.

Factory management needs to find the technically feasible point up to which maintenance and quality activity levels of a factory should be selected to achieve highest productivity with a view to fulfil company objectives for higher profitability. This research paper aims to report the development of an analytical relation between maintenance, quality and productivity.

An analytical relation is designed and developed incorporating graphical analysis and regression analysis to support outputs of graphical method, which creates an appropriate model. A mixed research approach is used, including application of a practical case example.

The study displays a wide range of productivity performance profiles with the strategic aim of identifying the technically feasible highest productivity result obtained. It has formulated an important analytical link, and suggested a few recommendations. The formulated model predicts the best possible productivity result out of maintenance and quality‐related practical data of a factory. The analysis enables managers to analyze, compare and identify improvement opportunities in order to enjoy competitive advantages.

Modern factory managers, particularly in food production, who live in a world of rapid changes, extensive interactions and complex situations, and face everyday challenges in a competitive global market, can use this model as a hands‐on tool for measurement, evaluation, logically better and proper realistic planning and implementation of maintenance and quality activities to attain maximum manufacturing productivity for their companies.

The model is the result of an attempt to design and develop, fulfil identified technical managerial needs and offer practical help to make logical decisions. Evidence from the literature confirms that this is a newer outlook on analytical diagnostic tools, which demonstrates the weaknesses in existing factory production system and thus helps in identifying key areas for productivity improvements. Therefore, this research is one step to further the potential and practical value added contribution in food and other industries.

The purpose of this paper is to demonstrate application of the Taguchi method to determine the optimum level of three important parameters (factors) related to the use of a mobile phone for the text message entering task, namely illumination level, noise level and mobile angle that maximizes the performance of mobile phone users.

Three levels of each parameter as available in the literature, except for the mobile angle, were considered. The design of the experiment, as proposed by Genichi Taguchi, was used to conduct nine experiments. A total of 30 male subjects participated in the experimental study. The text message entry task, in the form of Arabic text, was presented to the participating subjects and their performance, measured in terms of mean number of characters entered per minute, was recorded. The signal‐to‐noise (S/N) ratio and the analysis of variance (ANOVA) were employed to investigate the users' performance. Finally, a confirmation test was conducted to verify the validity of the results.

Results showed that, at the illumination level of 475 lux, noise level of 45 dB(A), and mobile angle of 70 degrees, the subjects were quite comfortable, efficient and entered the maximum number of characters in the mobile phone per minute. The noise was found to be the dominant parameter with a contribution of 95.53 percent towards the laid down objective followed by mobile angle, 3.25 percent and illumination level, 0.66 percent.

To the best of the authors' knowledge no study has been conducted in the past to investigate the effect of these parameters on the performance of the mobile phone users. In addition, no attempt has yet been made to find the optimal level of these parameters from a text‐entering viewpoint. The paper represents original research and in the authors' opinion carries significantly important values as it provides new information for those involved in the design of the mobile phone environment.

The purpose of this paper is to demonstrate the use of artificial intelligence methods in quality control and improvement. The paper introduces a systematic approach for the design of fuzzy control charts of tip shear carpets.

There are certain steps for designing fuzzy control charts. All input, state and output variables of the carpet plant and partition of the universe of discourse were first determined. The interval spanned by each variable and the number of fuzzy subsets each assigned with a linguistic label were identified. Then, the adaptive capability of neural network was used to determine the membership functions for each fuzzy subset. The fuzzy relationship functions between the inputs and outputs were assigned to form the fuzzy rule base (controller) in order to normalize the variables and certain intervals. Fuzzification of input parameters and max‐min composition of rules for inferring crisp outputs was the next step. The aggregation of fuzzified outputs and defuzzification of the outputs were the last step of this study, which helped to produce crisp outputs for latex weight.

Fuzzy linguistic terms were employed for overall quality assessment and rating of the end product. The outcomes of neuro‐fuzzy system were good supplements to other statistical process control tools.

Lack of qualified domain experts, knowledge acquisition of process parameters and time limitation for training of neuro‐fuzzy model were primary limitations.

The approach is more flexible and meaningful to identify the quality distribution of a product. The qualitative aspect of human reasoning for decision making was employed in this approach.

The paper is original and the first such work for local industry.

The purpose of this paper is to demonstrate application of the Taguchi method‐based conceptual signal‐to‐noise (S/N) approach and Pareto analysis of variance (ANOVA) to determine optimum level of three important factors related to mobile phone conversation during driving, namely time of drive (day or night), distance between cars, and mobile phone call duration that minimizes drivers' reaction time (RT) in braking response.

Three levels of each factor based on the experience, are considered in the present study. The design of experiment, in the form of an L₁₈ orthogonal array, as proposed by Genichi Taguchi is used to conduct 18 experiments. A total of 27 young male subjects participated in the experimental study. The experimental task involved pressing the brake pedal of the car by the driver upon seeing another car in front while the driver is talking on a mobile phone. Drivers' performance, measured in terms of RT in braking response, is recorded. Conceptual S/N ratio and Pareto ANOVA are employed to investigate the drivers' performance.

Results show that within the test range, drivers' performance, i.e. RT in braking response is optimum (minimum) when they performed the driving task at day time, distance between cars is long (20 meters), and mobile phone call duration is short (30 seconds). Mobile call duration is found to be the dominant parameter with a percentage contribution ratio of 41.882 percent towards the laid down objective followed by time of driving, 32.003 percent and distance between cars, 1.353 percent.

This paper provides valuable information to the drivers with respect to the use of optimum level of these factors in order to minimize their RT in braking response.

To the best of the authors' knowledge, no study has been conducted in the past to investigate the effect of these factors on the performance of drivers when they use mobile phones for conversation during driving. In addition, no attempt has yet been made to find the optimal level of these factors from drivers' performance in braking response view point. This paper is an original research work of authors and in the opinion it carries significantly important values as it provides new information to the persons who talk on mobile phones during driving.

Total quality management is now an established and widely used management process. One of its associated features is the application of statistical quality control techniques. These have been applied to both manufacturing and service industries. This paper presents an application of this methodology to the area of human performance evaluation in a service industry. It describes the data, method of their collection, their analysis, and a subjective evaluation criterion developed to evaluate the performance.