Layout and Material Flow Optimization in Digital Factory

Centobelli, Piera; Cerchione, Roberto; Murino, Teresa

doi:10.2507/ijsimm15(2)3.327

Cited by 49 publications

(32 citation statements)

References 31 publications

(30 reference statements)

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“…Because discrete-event simulations do not have to simulate every time slice, they can, typically, run much faster than the corresponding continuous simulation [11]. Practical examples of discrete systems' simulation are presented in solving scheduling problems using linear programming [14], layout and material flow optimization in a digital factory [8], and on production optimization [25]. The mentioned authors present various simulation methods and approaches, and, in doing so, they discuss a problems that arise with the application of simulation methods.…”

Section: Literature Reviewmentioning

confidence: 99%

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Use of a Simulation Environment and Metaheuristic Algorithm for Human Resource Management in a Cyber-Physical System

Zhang

Buchmeister

Liu

et al. 2019

Springer Series in Advanced Manufacturing

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At the time of Industry 4.0 and the emergence of collaborative workplaces based on the cooperation of robots (machines) and humans, the number of human workplaces in the Industry 4.0 production system is crucial. In this chapter, we present the use of the evolutionary computation methods that use the input data of a real production system and transfer it through the five-stage Cyber-Physical System architecture into the simulation environment in order to determine the optimal number of workers. By using these methods, we confirm the hypothesis of the importance of correctly determining the number of workers in the manufacturing process in Industry 4.0. Number of workers' determination has a key influence on the product flow time, machine utilization and cost-effectiveness of a production system. Research results show the importance and effectiveness of combining evolutionary computation methods and simulation modelling for the purpose of implementing the advanced approaches of Industry 4.0. The demonstrated approach of combining evolutionary computing, simulation environments and methods of Industry 4.0 can be used from mass customization to mass production systems for the purpose of single-criteria or multi-criteria optimization.

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Section: Literature Reviewmentioning

confidence: 99%

“…In Fig. 4, we sort the S to get S', the decision variable 9 is serviced as a separator, the S' can be decoded as worker 1 checks the machines, and its sequence is (4, 3, 2, 1), and worker 2 checks the machines, and its sequence is (6,8,7,5).…”

Section: Solution Codingmentioning

confidence: 99%

Use of a Simulation Environment and Metaheuristic Algorithm for Human Resource Management in a Cyber-Physical System

Zhang

Buchmeister

Liu

et al. 2019

Springer Series in Advanced Manufacturing

View full text Add to dashboard Cite

show abstract

“…The more efficiently the materials can be produced and converted to the desired products, which operate at the required quality, the more improved the productivity of the factories will be; as a result, the living standard of the employees also will improve. Several scientific papers [12][13][14][15][16][17][18] focus on layout design and optimisation of material flow. Each of these publications describe case studies that deal with the optimisation of production systems based on the interpretation of material flow in small and medium-sized factories.…”

Section: Introductionmentioning

confidence: 99%

Concept of Long-Term Sustainable Intralogistics in Plastic Recycling Factory

et al. 2019

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This paper focuses on the sustainability of material flow and intralogistics in factories, two of the primary keys to productivity. In the past ten years, there has been significant interest in the sustainability of intralogistics to increase productivity. The aim of this article is to investigate the consequences of combining two factories into one, followed by the design of new material flows and intralogistics from a long-term perspective and with respect to sustainability. Therefore, this paper outlines sustainability variants of new material flow solutions in factories. Our methods and approaches were chosen because they represent one of the most rapid ways to rationalise material flows and intralogistics in factories to sustain this concept. In comparison with other projects that eliminate problems in the short term, we have focused on the overall long-term and sustainable concept of intralogistics and material flows over the next 10 to 15 years. Our approach has the potential to increase productivity intralogistics and its long-term sustainability. The proposed variants were verified and evaluated using visTable®touch software (v.2.7, plavis GmbH, Chemnitz, Germany). On the basis of these results, the rational variant of material flows was chosen for the factory. This variant has the highest overall improvement of 25%, even after the implementation of factory two into factory one.

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“…However, the variety of information interaction and material transportation in current Manufacturing Systems (MS) [4], which involves up to five car models on the same line in automobile assembly lines, hinder the analysis of this relevant flow. For that purpose, the development of a virtual layout using simulation modelling is worthwhile during the decision-making process of MS reconfigurations [5].…”

Section: Introductionmentioning

confidence: 99%

Using 4-Layer Architecture to Simulate Product and Information Flows in Manufacturing Systems

Saez-Mas¹,

García-Sabater²,

Morant-Llorca³

2018

Int. j. simul. model.

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This work illustrates the application of novel simulation architecture with two case studies where the proposed architecture, the so-called 4-layer, allowed us to address the complexity of the analysed systems. The fundamental objective of this work is to show the structure of layers, how layers interact with one another and with the user, and what benefits this separation proposes. The first case study deals with moving car bodies from the paint plant to the assembly line through a sequencing system that involves distributed decision-making processes in an ASRS. The second case study focuses on analysing a layout of a section used to assemble the engine and transmission set, where the quality of the material flow is evaluated. The work highlights some of the advantages of modelling with 4-layer architecture, and explains the key processes that connect different elements.

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Layout and Material Flow Optimization in Digital Factory

Cited by 49 publications

References 31 publications

Use of a Simulation Environment and Metaheuristic Algorithm for Human Resource Management in a Cyber-Physical System

Use of a Simulation Environment and Metaheuristic Algorithm for Human Resource Management in a Cyber-Physical System

Concept of Long-Term Sustainable Intralogistics in Plastic Recycling Factory

Using 4-Layer Architecture to Simulate Product and Information Flows in Manufacturing Systems

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