Interactive design of storage unit utilizing virtual reality and ergonomic framework for production optimization in manufacturing industry

Azizi, Aydin; Yazdi, Poorya Ghafoorpoor; Hashemipour, Majid

doi:10.1007/s12008-018-0501-9

Cited by 48 publications

(20 citation statements)

References 13 publications

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“…The left slider for short-range transfer had a 9.99% to 15.69% improvement for speed and 1 2 of the actual distance change. Simultaneously, for the long range, there was a 12.66% to 15.71% improvement for modifying the speed to maximum limit and the distance to 1 2 of the actual distance. Table 6 shows the OEE percentage improvement in detail as the result of the optimization method, considering the most effective parameter as the mentioned objective function parameters.…”

Section: Oee Analysis After Optimizationmentioning

confidence: 92%

“…The minimum and maximum values were the result of changing the distances to 2 / 3 and 1 2 of the actual distance. On the other hand, the OEE percentage improvement for the Left slider for a short range is between 4.64% to 7.26% for Speed and 1 2 of the actual distance, respectively. The left slider for short-range transfer had a 9.99% to 15.69% improvement for speed and 1 2 of the actual distance change.…”

Section: Oee Analysis After Optimizationmentioning

confidence: 93%

“…On the other hand, the OEE percentage improvement for the Left slider for a short range is between 4.64% to 7.26% for Speed and 1 2 of the actual distance, respectively. The left slider for short-range transfer had a 9.99% to 15.69% improvement for speed and 1 2 of the actual distance change. Simultaneously, for the long range, there was a 12.66% to 15.71% improvement for modifying the speed to maximum limit and the distance to 1 2 of the actual distance.…”

Section: Oee Analysis After Optimizationmentioning

confidence: 93%

“…Nowadays, having businesses with increasing globalization and rapid technological changes requires more firms known as small-and medium-sized enterprises (SMEs), characterized by tight resources [1]. Industrial and commercial sectors, and large enterprises in particular, are changing due to globalization.…”

Section: Introductionmentioning

confidence: 99%

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

2019

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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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Section: Oee Analysis After Optimizationmentioning

confidence: 92%

Section: Oee Analysis After Optimizationmentioning

confidence: 93%

Section: Oee Analysis After Optimizationmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

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

2019

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“…The examples of car suspension system modeling were presented in this work. The approach of interactive design and production evaluating of a manufacturing cell is described in [17].…”

Section: State Of the Art 21 System Modeling And Hierarchical Represmentioning

confidence: 99%

Conceptual Design Evaluation of Mechatronic Systems

Katrantzis¹,

Moulianitis²,

Miatliuk³

2020

Emerging Trends in Mechatronics

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The definition of the conceptual design phase has been expressed in many different phrasings, but all of them lead to the same conclusion. The conceptual design phase is of the highest importance during the design process, due to the fact that many crucial decisions concerning the progress of the design need to be taken with very little to none information and knowledge about the design object. This implies to very high uncertainty about the effects that these decisions will have later on. During the conceptual design of a mechatronic system, the system to be designed is modeled, and several solutions (alternatives) to the design problem are generated and evaluated so that the most fitting one to the design specifications and requirements is chosen. The purpose of this chapter is to mention some of the most widely used methods of system modeling, mainly through hierarchical representations of their subsystems, and also to present a method for the generation and evaluation of the design alternatives.

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