Design and fabrication of intelligent material handling system in modern manufacturing with industry 4.0 approaches

Azizi, Aydin; Yazdi, Poorya Ghafoorpoor; Humairi, Ali Al; Alsalmi, Mohammad; Rashdi, Basma Al; Zakwani, Zuwaina Al; ALSheikaili, Sultan

doi:10.15406/iratj.2018.04.00121

Cited by 18 publications

(12 citation statements)

References 30 publications

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“…In the present research, an ANN model was developed to predict the ROP as a function of effective parameters. The neural network is widely used in various engineering fields [51][52][53][54][55][56][57][58][59][60]. In order to train the network, three training functions were used including Levenberg-Markvart (LM), scaled conjugate gradient (SCG), and one-step secant (OSS).…”

Section: 1 Predictionmentioning

confidence: 99%

Applications of Artificial Intelligence Techniques in Optimizing Drilling

Koopialipoor¹,

Noorbakhsh²

2020

Emerging Trends in Mechatronics

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Artificial intelligence has transformed the industrial operations. One of the important applications of artificial intelligence is reducing the computational costs of optimization. Various algorithms based on their assumptions to solve problems have been presented and investigated, each of which having assumptions to solve the problems. In this chapter, firstly, the concept of optimization is fully explained. Then, an artificial bee colony (ABC) algorithm is used on a case study in the drilling industry. This algorithm optimizes the problem of study in combination with ANN modeling. At the end, various models are fully developed and discussed. The results of the algorithm show that by better understanding the drilling data, the conditions can be improved.

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Section: 1 Predictionmentioning

confidence: 99%

Applications of Artificial Intelligence Techniques in Optimizing Drilling

Koopialipoor¹,

Noorbakhsh²

2020

Emerging Trends in Mechatronics

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“…Manajemen pergudangan dirancang untuk kepentingan pengolahan aktivitas pergudangan yang akan berpengaruh terhadap keseluruhan proses produksi. Manajemen pergudangan yang dikelola dengan baik akan mampu meningkatkan efisiensi penanganan bahan atau material handling dalam gudang (Azizi et al, 2018). Ditambah dengan kemajuan teknologi maka penanganan bahan dan persediaan dalam gudang akan semakin cepat dan praktis (Ogbo et al, 2014).…”

Section: Pendahuluanunclassified

Penerapan Warehouse Management System Pada Pt Uniplastindo Interbuana Bali

Putri

Nurcaya

2019

EJMUNUD

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Warehouse Management System is a database-based computer application system, which used to improve warehouse efficiency in maintaining the accuracy of inventory data by recording every transaction in the warehouse. The purpose of this study was to determine efficiency of material handling costs incurred after implementation of warehouse management system. The research was conducted at PT Uniplastindo Interbuana Bali with simulation of implementation warehouse management system. Based on calculations, application of WMS able to increase cost efficiency and time efficiency in material handling because the system is able to provide accurate material placement data. Data during simulation shows a smaller amount of time compared to before simulation, which means less costs are incurred. Existence of system also makes it easy for related admin to collect data on real stock in the field. Data presentation and processing becomes faster and accurate so it can lead to increased performance in company. Keywords: Warehouse Management System (WMS), material handling, cost efficiency

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“…In the first stage of the research, the proposed hybrid methodology was implemented on an educational manufacturing system at the German University of Technology in Oman (GUtech) [50]. Before any changes were made, the system was a semi-automated material handling system for part/product distribution.…”

Section: Take Action To Improve Performancementioning

confidence: 99%

A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs

2019

Self Cite

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The properties of small- and medium-sized enterprises (SMEs) make them one of the most important categories of enterprises for the economics of challenging world. SMEs, in most countries, are still enterprises with marketing and financial challenges. In addition, most of these challenges are related to their production and product characteristics. On the other hand, SMEs should fulfil the costumer’s demands. In order to reach these goals, SMEs must reach the highest level of production quality and quantity and successfully sustain them. Consequently, various manufacturing paradigms have been offered by an Industry 4.0 concept, which offers a variety of solutions to increase the productivity and enhance the performance of SMEs. It should be noted that implementation of these manufacturing paradigms for SMEs is quite difficult and sometimes risky for several reasons. Still, amidst all these difficulties and challenges, the benefits and idealism of the Industry 4.0 paradigms prevail. From productivity to market, it is difficult to deny that SMEs are frightened by the challenges they face and fleeing from the potential of overcoming them. This paper is an extended version of the research by Ghafoorpoor Yazdi et al. (2018) and conducts a hybrid methodology to satisfy the SMEs by validating and verifying any optimization idea before implementing the Industry 4.0 concept. To reach the study goals, an intelligent Material Handling System (MHS) with agent-based control architecture has been developed. The developed MHS has been utilized for auto parts distribution. The system performance has been evaluated, and some solutions have been provided to optimize the performance of system. To evaluate the target system’s performance, an analytical time study method has been utilized. The time study has an Overall Equipment Effectiveness (OEE) standard approach to identifying the matters that need to be resolved and optimized to increase system performance. The other part of the methodology is generating a simulation model of the real system by use of ARENA® software to evaluate the system’s performance before implementing the optimization idea and modifying the real system. Furthermore, as the sustainability strategies create many synergistic effects for SMEs, after evaluating the effects of the optimization ideas on OEE percentage, the influence of the OEE changes on manufacturing sustainability has been investigated. The results show that optimizing the OEE in SMEs with sustainability approaches can create competitive advantages, rather than simply focusing on reducing unsustainability.

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Design and fabrication of intelligent material handling system in modern manufacturing with industry 4.0 approaches

Cited by 18 publications

References 30 publications

Applications of Artificial Intelligence Techniques in Optimizing Drilling

Applications of Artificial Intelligence Techniques in Optimizing Drilling

Penerapan Warehouse Management System Pada Pt Uniplastindo Interbuana Bali

A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs

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