Optimizing Reconfigurable Manufacturing Systems for Fluctuating Production Volumes: A Simulation-Based Multi-Objective Approach

Díaz, Carlos Alberto Barrera; Aslam, Tehseen; Ng, Amos H. C.

doi:10.1109/access.2021.3122239

Cited by 19 publications

(15 citation statements)

References 47 publications

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“…Recently, more and more scholars have integrated metaheuristic algorithms into simulation to analyze the resource allocation problem of the production line, so as to predict and optimize system performance [19,20]. For the resource configuration of the reconfigurable manufacturing systems, Diaz et al [21] proposed a simulation method based on the Non-dominated Sequential Genetic Algorithm (NSGA-Il) to get the optimal allocation of work tasks and workstations. Yegul et al [22] studied the resource allocation problem of electric vehicle component production lines.…”

Section: Simulation-based Methods For Resource Configuration Of Manuf...mentioning

confidence: 99%

Order-Driven Dynamic Resource Configuration Based on a Metamodel for an Unbalanced Assembly Line

2022

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Resource-constrained product general assembly lines with complex processes face significant challenges in delivering orders on time. Accurate and efficient resources allocation of assembly lines remain a critical factor for punctual order delivery, full use of resources and associated customer satisfaction in complex production systems. In order to quickly solve the order-based dynamic resource allocation problem, in this paper a metamodel-based, multi-response optimization method is proposed for a complex product assembly line, which has the characteristics of order-based production, long working time of processes, multiple work area re-entry and restricted operator quantity. Considering the complexity of the assembly line and the uncertainty of orders, the correlation between system performance indicators and resource parameters is investigated. Multiple metamodels are constructed by the Response Surface Methodology to predict and optimize the system performance. The adequacy of the constructed metamodels is verified and validated based on the bootstrap resampling method. Under the condition of ensuring the throughput demand of the assembly line, the desirability function is applied to simultaneously optimize the multi-response, and the resource allocation solution is generated. The method in this paper can be used to rapidly adjust the resource configuration of the assembly line when considering the order changes.

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Section: Simulation-based Methods For Resource Configuration Of Manuf...mentioning

confidence: 99%

Order-Driven Dynamic Resource Configuration Based on a Metamodel for an Unbalanced Assembly Line

2022

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“…In addition, the unavailability of the resources in RMS is usually neglected. Some of the prior publications that have considered the availability of the resources of the system and employed SMO towards RMS such as, [17,18], have studied the systems for specific availability. Against this backdrop, this paper proposes using SMO to study how different availability considerations impact RMS.…”

Section: Simulation-based Multi-objective Optimizationmentioning

confidence: 99%

Availability Analysis of Reconfigurable Manufacturing System Using Simulation-Based Multi-Objective Optimization

Díaz

Navarro

Perez

et al. 2022

Advances in Transdisciplinary Engineering

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Nowadays, manufacturing companies face an increasing number of challenges that can cause unpredictable market changes. These challenges are derived from a fiercely competitive market. These challenges create unforeseen variations and uncertainties, including new regional requirements or regulations, new technologies and materials, new market segments, increasing demand for new product features, etc. To cope with the challenges above, companies must reinvent themselves and design manufacturing systems that seek to produce quality products while responding to the changes faced. These capabilities are encompassed in Reconfigurable Manufacturing Systems (RMS), capable of dealing with uncertainties quickly and economically. The availability of RMS is a crucial factor in establishing the production capacity of a system that considers all events that could interrupt the planned production. The impact of the availability in RMS is influenced by the configuration of the systems, including the number of resources used. This paper presents a case study in which a simulation-based multi-objective optimization (SMO) method is used to find machines’ optimal task allocation and assignment to workstations under different scenarios of availability. It has been shown that considering the availability of the machines affects the optimal configuration, including the number of resources needed, such as machines and buffers. This study demonstrates the importance of the availability consideration during the design of RMS.

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“…Differently, when DES becomes impractical due to the size and complexity of the RMS, modelling several different configurations becomes unattainable. This problem has been overcome in studies such as [20] and [21], combining DES and optimization enabling the advantages of both techniques.…”

Section: Reconfigurable Manufacturing Systems and Discrete-event Simu...mentioning

confidence: 99%

Reconfiguration Assessment for Production Volume Changes Using Discrete-Event Simulation: A Large-Size Highly-Customized Product Case Study

Zúñiga

Díaz

Navarro

et al. 2022

Advances in Transdisciplinary Engineering

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Globalization and mass customization are commonly translated into increased levels of complexity in manufacturing systems. One of the main reasons is the increased number of variables, parameters, and interrelations on the shop floor. This intrinsic complexity can grow exponentially when considering the manufacture of large-size products with high levels of variability and variants: the mass production of large recreational motorboats with high levels of customization and low production volumes, mass customization. With the increasing role of sustainability and concepts of Industry 5.0, focusing not just on improving production systems but also human wellbeing, quick decision making becomes essential. Data and digitalization are becoming the cornerstone for system improvement, and digital data availability and analysis can facilitate the utilization of computerized tools to support decision making and maximize the performance of complex systems. For that purpose, simulation can be a powerful analytical tool to design, maintain, and improve complex manufacturing systems. Simulation techniques usually allow handling the size and complexity commonly associated with manufacturing systems. However, in systems with highly customized and large-size products, manual processes, and limited floor space, the implementation of simulation techniques is not straightforward, especially considering the aspects of variability, data collection, model validation, and system reconfiguration. With a particular focus on large-size products and limitations of a constrained existing facility layout, this paper presents the implementation of a simulation-based reconfiguration assessment considering manual production, assembly, and internal logistics requirements. Going through an industrial case study of large recreational motorboats manufacturing, the paper analyses the system analysis, data collection, implementation, and validation of the methodology step by step. Considering different what-if scenarios, the focus is on the capacity reconfiguration using Discrete-Event Simulation. The results can serve as a guideline for decision-makers and stakeholders working with complex mass customization manufacturing systems and space-constrained facility layouts.

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Optimizing Reconfigurable Manufacturing Systems for Fluctuating Production Volumes: A Simulation-Based Multi-Objective Approach

Cited by 19 publications

References 47 publications

Order-Driven Dynamic Resource Configuration Based on a Metamodel for an Unbalanced Assembly Line

Order-Driven Dynamic Resource Configuration Based on a Metamodel for an Unbalanced Assembly Line

Availability Analysis of Reconfigurable Manufacturing System Using Simulation-Based Multi-Objective Optimization

Reconfiguration Assessment for Production Volume Changes Using Discrete-Event Simulation: A Large-Size Highly-Customized Product Case Study

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