Improving the material flow of a manufacturing company via lean, simulation and optimization

Uriarte, Ainhoa Goienetxea; Ng, Amos H. C.; Zúñiga, Enrique Ruiz; Moris, Matías Urenda

doi:10.1109/ieem.2017.8290092

Cited by 13 publications

(4 citation statements)

References 23 publications

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“…Despite decades-long literature and the importance of warehouse planning, several literature reviews have concluded that few scientific journals have addressed the applicable systematic approach [35,62,63]. In fact, the systematic analysis of warehouse design subprocesses themselves is addressed in several studies [63,64], in subprocesses, for example, examining the issue of flight planning or the layout of storage systems [64,65]. In contrast, there is no overlapping study between subprocesses to find a possible optimum.…”

Section: Overview Of the Area Of Storage System Designmentioning

confidence: 99%

Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems

Dobos¹,

Cservenák

Skapinyecz

et al. 2021

Sustainability

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In real life situations, the material handling strategy of on-site storage systems is usually determined during the design of the storage system, which is no longer reviewed later. The strategy is typically determined by the person(s) designing the storage system, without the use of scientific methods, based on previous experience. Without a thorough periodic review of operational strategy, most companies’ warehousing systems have significant logistical losses (e.g., unnecessary material handling, waiting, operations), which also negatively affects the sustainability of the logistics operations. Therefore, eliminating these losses can increase both the competitiveness and the sustainability of companies. For this reason, the aim of this publication is to introduce a gap-filling test method that allows the selection of an optimal material handling strategy covering the total value stream in a demand-driven storage environment, using the opportunities offered by the Industry 4.0 concept, in particular in the field of big data analysis. This integrated approach has so far not emerged in the study of warehouse material handling strategies. Beyond the obvious economic benefits, the application of this method can clearly help companies to achieve a higher level of sustainability in their logistics operations, as it allows storage systems to operate more efficiently while minimizing material handling losses, ultimately resulting in a lesser demand for energy and raw materials. Moreover, this can also result in a reduction in the human and machine resources required to perform the tasks.

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Section: Overview Of the Area Of Storage System Designmentioning

confidence: 99%

Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems

Dobos¹,

Cservenák

Skapinyecz

et al. 2021

Sustainability

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“…The total predicted costs of the 1-th sub-company in case of making the order represented by Z 0 are calculated as follows (25):…”

Section: Mathematical Modelmentioning

confidence: 99%

“…These are parameters that, besides others, are directly linked to the concept of the so-called lean company (or lean manufacturing, lean logistics, etc.) and Kanban [25], [26], [27], [28], [29]). It should be noted that this paper deals with efficiency issues by automatically assuming that discounting or shortening the time of production, distribution or other business processes never leads to a decrease in quality.…”

Section: Introductionmentioning

confidence: 99%

The Cost-Based Lean Approach to the Information Logistics Business System Modelling

2019

CIT. J. comput. inf. technol

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The paper highlights the problems of modelling the complex logistics manufacturing system which is to meet the needs of the contemporary lean approach to manufacturing. It is assumed that the system consists of identically arranged and equipped subsystems, however, each of them is characterised by different operating and fixed costs. The software engineering method used to create the simulator of the discussed system is emphasised to show how the necessary assumptions turn the real manufacturing system into the mathematical model of the logistic-business system, and subsequently into the simulator. Manufacturing strategies as well as heuristic algorithms are introduced in order to control making the order. The case study presents the method of searching for the most adequate manufacturing subsystem for making the order on the basis of cost calculation. The key points responsible for excessive costs are detected. A thorough analysis based on modified operating as well as fixed costs is carried out. ACM CCS (2012) Classification: Computing methodologies → Artificial intelligence → Distributed artificial intelligence → Multi-agent systems Computing methodologies → Modeling and simulation → Model development and analysis → Modeling methodologies

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“…A similar approach was used by Sankaran et al [10] to reduce the cost of the pump manufacturing process, by the means of finding the adequate batch size and interarrival time. Some researchers propose to combine simulation with lean management approach [11][12][13][14]. Combination with Value Stream Map (VSM) tool is also used [15,16], to shorten the production time, reduce work-in-process and increase value-added time for manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Subassembly Production Process Using Simulation

Stevanov¹,

Sremcev²,

Lazarevic³

et al. 2022

Int. j. simul. model.

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Using simulation as a tool for production process optimization represents a useful approach to exploring many optimization options which lie ahead on the process improvement path. Previously published research papers report on combining the simulation with another optimization method or a set of manufacturing practices or digital technology. To avoid the complexity of the developed optimization approach in practical application, this paper presents an approach that focuses on grouping the parts first and then simulating the parts group schedule, batch size, and parts interarrival time options to minimize production process cycle time and maximise the output quantity. The developed algorithm was tested with the data from a real case, for the production of the subassembly for the metal frame used in automotive parts logistics. The experimental results show improvements in defined performance parameters for set optimization goal.

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Improving the material flow of a manufacturing company via lean, simulation and optimization

Cited by 13 publications

References 23 publications

Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems

Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems

The Cost-Based Lean Approach to the Information Logistics Business System Modelling

Optimization of the Subassembly Production Process Using Simulation

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