Multi-objective optimization of job shops with automated guided vehicles: A non-dominated sorting cuckoo search algorithm

Abstract

The reliability of machinery and automated guided vehicle has been one of the most important challenges to enhance production efficiency in several manufacturing systems. Reliability improvement would result in a simultaneous reduction of both production times and transportation costs of the materials, especially in automated guided vehicles. This article aims to conduct a practical multi-objective reliability optimization model for both automated guided vehicles and the machinery involved in a job-shop manufacturing system, where different machines and the storage area through some parallel automated guided vehicles handle materials, parts, and other production needs. While similar machines in each shop are limited to failures based on either an Exponential or a Weibull distribution via a constant rate, the machines in different shops fail based on different failure rates. Meanwhile, as the model does not contain any closed-form equation to measure the machine reliability in the case of Weibull failure, a simulation approach is employed to estimate the shop reliability to be further maximized using the proposed model. Besides, the automated guided vehicles are restricted to failures according to an Exponential distribution. Furthermore, choosing the best locations of the shops is proposed among some potential places. The proposed NP-Hard problem is then solved by designing a novel non-dominated sorting cuckoo search algorithm. Furthermore, a multi-objective teaching-learning-based optimization, as well as a multi-objective invasive weed optimization are designed to validate the results obtained. Ultimately, a novel AHP-TOPSIS method is carried out to rank the algorithms in terms of six performance metrics.

Concurrent Optimization of Reliability, Maintainability and Total Cost in a Job Shop Production System with Multiple Fuzzy Parameters

“…Fazlollahtabar and Niaki [ 32 ] described a comprehensive fault tree analysis based on the critical components of industrial robots [33]. Karimi, Niaki [34] presented A complete classification of the subject literature in this field.…”

The assessment and selection of suppliers using AHP and MABAC with type-2 fuzzy numbers in automotive industry

“…The domain of each fuzzy number describing values of SSCs is defined on the common measurement scale 26 which is defined in the interval [1][2][3][4][5][6][7][8][9]. The value 1 and the value 9 indicate that SSCs have the smallest or the greatest value, respectively.…”

“…5 MCDM methods, in addition to the problem of supplier selection, have been used in the literature in other areas of risk analysis and reliability, such as in the case of determining the level of risk on the workplaces 6 or the reliability of production shops (plants). 7 Taking into account the global business conditions at the end of the second decade in the XXI century induced by the pandemic of covid 19, it seems that standardized methodologies defined by standards IATF16949:2016 and VDA Volume 2 cannot meet all unpredicted conditions. On the other hand, an approach outlined in the paper is based on fuzzy sets and oriented to handling emerging situations and a variety of uncertainties.…”

“…5 MCDM methods, in addition to the problem of supplier selection, have been used in the literature in other areas of risk analysis and reliability, such as in the case of determining the level of risk on the workplaces 6 or the reliability of production shops (plants). 7…”

“…of these IT2TFNs are defined at intervals[1][2][3][4][5][6][7][8][9]. Value 1 denotes the relative importance of the SSC k over SSC k 0 is equal.…”