Achieving productive reliability through applying statistical distribution functions

Abstract

Purpose

The purpose of this paper is to find the proper statistical distribution function, which can cover the failure time of a single machine or a group of machines. To this end, an innovative program is written in an Excel software, capable of assessing at least six statistical distribution functions. This research study intends to show the advantages of applying statistical distribution functions in an integrated model format to create or increase productive reliability machines. Productive reliability is a simultaneous combination of efficiency and effectiveness in reliability.

Design/methodology/approach

The method of theoretical research methodology comprises data collection tools, reference books and articles in addition to exploiting written reports of the Iranian Center for Defence’s Standards. The practical research method includes deploying and assessing the proposed model for a selected machine (in this case a computerized numerical control machine).

Findings

A comprehensive program in an Excel software having the capability of assessing at least six statistical distribution functions was developed to find the most efficient option for covering the failure times of each machine in the shortest time with the highest precision. This is regarded as the most important achievement of the present study. Furthermore, the advantages of applying the developed model are discussed and a large group of which have direct influences on the productivity of equipment reliability.

Originality/value

The originality of the research was ascertained by managers and experts working in maintenance issues at the different levels of the Defense Industries Organization.

Citation

Karbasian, M. and Rostamkhani, R. (2020), "Achieving productive reliability through applying statistical distribution functions", International Journal of Quality & Reliability Management, Vol. 37 No. 8, pp. 1125-1149. https://doi.org/10.1108/IJQRM-11-2018-0298