Using simulation to schedule manufacturing resources

Czarnecki, Hank; Schroer, Bernard J.; Rahman, M. Mizzanur

doi:10.1145/268437.268619

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…[5,6]). Even kiln processes, which are very similar to autoclaving, were regarded in research papers ( [7]), but though, no approach concerning energy consumption parameters in discrete event simulation models for achieving an energy efficient material flow through kilns could be found.…”

Section: State Of the Artmentioning

confidence: 99%

Simulation-Based Optimization of the Energy Consumption in the Hardening Process for Calcium Silicate Masonry Units

Donhauser

Ehrhardt

Rackow

et al. 2015

AMM

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Owing to a high cost pressure and the need for a reduction of carbon dioxide emissions for manufacturing calcium silicate masonry units (CS), the CS-industry strives to cut the energy consumption. The most energy consuming process step is the autoclaving. About 87% of the energy is required for this particular process step, where the green bodies are steam-hardened at 200°C.For reducing the energy consumption, most of the alternatives aim at optimizing the complete manufacturing process. In this paper, the focus is put on an optimized loading process for the autoclaves, in consideration of preceding and subsequent process steps. For this purpose, a simulation model is developed, where different strategies of loading are implemented and tested. This model can be used to find optimally scheduled assignments of production orders to the available autoclaves, based on the volume of each manufactured product.The analysis of the tested strategies shows, that it is possible to save up to almost 9 % of the required energy for autoclaving by an optimized assignment of the available autoclaves.

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Section: State Of the Artmentioning

confidence: 99%

Simulation-Based Optimization of the Energy Consumption in the Hardening Process for Calcium Silicate Masonry Units

Donhauser

Ehrhardt

Rackow

et al. 2015

AMM

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“…In the allocation of port equipment, we need to receive higher equipment utilization rate and lower the ship waiting time with the least equipment. Rational allocation of port resources can reduce the ships' queue length and waiting time, ships arrive at the port receive service in time; reduce the rotation cost of the goods at port and the time of ships that stay at port and attract more ships to dock at the port in order to promote the throughput of the port and the economic efficiency [9] .…”

Section: Description Of the Algorithmmentioning

confidence: 99%

Modeling and Simulation on Dynamic Allocation and Scheduling of Multi-resource problem

Hu²,

Cheng³

et al. 2011

JCP

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<p class="Abstract">Resource-constrained project scheduling and configuration determines the progress of the construction and quality. This paper proposes a simulation modeling method based on 0-1 variables according to multi-resource dynamic allocation and scheduling of discrete features, use digital circuit based simulation method to make a 0-1 variables model for multi-resource dynamic allocation and configuration problem. This paper constructs a model for dynamic resources allocation and scheduling based on priority and fuzzy theory. And use ant colony algorithm with trust mechanism to solve it. The algorithm simulates ant feeling of mutual trust and act and is subject to significant interaction between consciousness and unconsciousness in path selection, so that in the initial time to use their own experience, thereafter conditionally accept the trust mechanism for peers to influence the information volume, at the same time modify the amount of information on the path adaptively. In this way have good balance between accelerating the convergence and preventing early-maturing, stagnation. Each ant as an Agent, the autonomy of ant Agent shall be autonomous; each has some control of their own behavior. Through the port logistics scheduling system simulation applications, the results reflect the algorithm has good convergence and meet the actual production.</p>

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“…(1997), Czamecki et al (1997), Drake et al (1996( ), SavCn (1990. According to Banks (1997) these types of simulation are still in their infancy, but show great promise for the future.…”

Section: Emergence Of Operational Simulationmentioning

confidence: 99%

A simulation based decision support approach for operational capacity planning in a customer order driven assembly line

Andersson¹,

Olsson²

1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274)

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This paper reports on a project in the area of simulation based decision support (SBDS) at the operational level of the manufacturing system. The purpose of the project was to explore and describe the possibilities to use a standard discrete event simulation package for capacity planning purpose in a situation where labor was a primary and scarce production resource. This has been done through a case study at a Radio Base Station (RBS) assembly line at Ericsson Radio System, Gavle. Results from the study are a conceptual structure for a SBDS system and a prototype simulation system tailored for the RBS-2OOO assembly line. The system has been tested in a simulated environment and results indicate a delivery precision improvement of eleven percent. Conclusions from the study are that this kind of tool for operational decision support offers a flexible decision support environment and that the need for high quality information and information collecting systems are crucial for the success of such tools.

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Using simulation to schedule manufacturing resources

Abstract: This paper discusses a real-world application of simulation to schedule operator and machine resources in a floor tile manufacturing plant. The paper discusses attempts at using a spread sheet, a simulator, and finally ProModel in the scheduling process.

Cited by 5 publications

References 8 publications

Simulation-Based Optimization of the Energy Consumption in the Hardening Process for Calcium Silicate Masonry Units

Simulation-Based Optimization of the Energy Consumption in the Hardening Process for Calcium Silicate Masonry Units

Modeling and Simulation on Dynamic Allocation and Scheduling of Multi-resource problem

A simulation based decision support approach for operational capacity planning in a customer order driven assembly line

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