Abstract
Purpose - 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. Design/methodology/approach - 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. Findings - 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. Practical implications - 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. Originality/value - 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.[PUBLICATION ABSTRACT]