Simulation and optimization of continuous-flow production systems with a finite buffer by using mathematical programming

Hosseini, Behnaz; Tan, Barış

doi:10.1080/0740817x.2016.1217103

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…We understand the effects of system features such as processing rates and buffer capacities, processing time variability, machine reliability, and material flow on system performance through analytical models of production systems. These models enable us to estimate the performance of a material flow system and optimize design parameters of the system [8].…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation Analysis for in-Line Sorting-and-Washing of Reusable Pallets: A Case Study

Yun

Chae

2022

Teh. vjesn.

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In this study, a system constituting an integral part of a continuous sequence of operations or machines in a line is presented as a form of "in-line" system. Due to the sequential nature of the production line, the throughput rate of the line depends on the slowest process. This paper presents one example of an in-line system that is used for pallet re-use by sorting, washing, and drying in a continuous processing line. Basically, a well-structured in-line system provides high throughput because of the non-stop flow of materials in the system. However, there is a hidden loss in the system efficiency. The object of this paper is to evaluate some of the possible alternatives to solve these hidden inefficiency problems and to improve throughputs through simulated models. The three outcomes from this simulation indicate that exchanging the robotic arm with a sorter and adding additional spin-drying machines could reduce overhead costs and the average waiting time for the spin-drying machine and improve the utilization of the resources in the washing process.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation Analysis for in-Line Sorting-and-Washing of Reusable Pallets: A Case Study

Yun

Chae

2022

Teh. vjesn.

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“…Mathematical techniques and simulation expertise are useful alternatives for analyzing the arising complexity of manufacturing models. For instance, Hosseini and Tan [25] presented an analytical simulation approach to analyze the performance of a continuous production system; their method provided solutions considerably faster than solely evaluating the system dynamics at critical times. They determined time instances of the trajectory of the buffer, stock level dynamics, and changing flow rates.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this table, the rows classify the studies presented in the literature review in five main areas, and the columns present the key factors investigated in these studies. [4] Rivera-Gómez et al [5] Hajej and Rezg [6] (b) Production-quality-maintenance strategies Bouslah et al [7] Fakher et al [8] Cheng et al [9] Abubakar et al [10] Ait-El-Cadi et al [11] Hajej et al [12] (c) Production and subcontracting planning Assid et al [13] Ben-Salem et al [14] Haoues et al [15] Ayed et al [16] Rivera-Gómez et al [17] Kammoun et al [18] (d) Deteriorating systems Boudhar et al [19] Martinod et al [20] Ouaret et al [21] Polotski et al [22] Dellagi et al [23] Magnanini and Tolio [24] (e) Simulation approach Hosseini and Tan [25] Guiras et al [26] Abdolmaleki et al [27] Rivera-Gómez et al [28] Assid et al [29] Ait-El-Cadi et al [30] (f) Additional issues Fathollahi-Fard et al [31] Jian et al [32] Villalonga et al [33] Chen et al [34] Fathollahi-Fard et al [35] Gholizadeh et al [36] Villalonga et al [37] The proposed model…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of Unreliable Subcontracting on Production and Maintenance Planning Considering Quality Decline

Rivera-Gómez

Medina-Marín

Robles³

et al. 2022

Applied Sciences

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Manufacturing systems face several disturbances during production, such as sudden failures, defects, and unreliable subcontractors that reduce their production capacity. Currently, subcontracting represents an efficient alternative to support production decisions. The novelty of the study was the development of a new integrated model that properly coordinates production, subcontracting, and maintenances strategies in the context of stochastic uncertainty, quality deterioration, and random subcontracting availability. Such a set of characteristics has not been addressed before in the literature. A simulation–optimization approach was proposed to address such a stochastic model. A numerical case study was performed as an illustration of the approach and a comprehensive sensitivity analysis was performed to analyze the impact of several costs. Furthermore, the effect of the availability of the subcontractor and the producer was analyzed. The main finding of the study showed that the integrated model led to significant economic cost savings compared to other approaches that address such policies in isolation. The results also indicated that quality deterioration had a strong impact on the subcontracting rate and that the proposed joint control policy adequately coordinated these three key functions. The level of subcontracting participation was directly defined by its availability and the subcontracting cost.

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“…Similarly, Turki et al [24] determined an optimal buffer size for a single-product machine with random failures. In Hosseini and Tan [25], each stage in a two-stage system has different states of processing with general distribution of transition times. The authors developed a mixed-integer linear programming model to determine optimal level of buffer by maximizing profit.…”

Section: Introductionmentioning

confidence: 99%

Optimal Control to Handle Variations in Biomass Feedstock Characteristics and Reactor In-Feed Rate

Kucuksayacigil,

Roni,

Eksioglu

et al. 2021

Preprint

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The variations in feedstock characteristics such as moisture and particle size distribution lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass preprocessing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. A biorefinery can adapt HPC to achieve its design capacity.

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Simulation and optimization of continuous-flow production systems with a finite buffer by using mathematical programming

Cited by 10 publications

References 25 publications

Simulation Analysis for in-Line Sorting-and-Washing of Reusable Pallets: A Case Study

Simulation Analysis for in-Line Sorting-and-Washing of Reusable Pallets: A Case Study

Impact of Unreliable Subcontracting on Production and Maintenance Planning Considering Quality Decline

Optimal Control to Handle Variations in Biomass Feedstock Characteristics and Reactor In-Feed Rate

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